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https://github.com/thousandeyes/thousandeyes-sdk-python.git
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[GitHub Bot] Generated python SDK
This commit is contained in:
API Team
parent
b34d33213f
commit
ea00257913
@ -12,7 +12,7 @@ This API provides the following operations to manage your organization:
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This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
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- API version: 7.0.58
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- API version: 7.0.62
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- Generator version: 7.6.0
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- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
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@ -5,7 +5,7 @@ Manage Cloud and Enterprise Agents available to your account in ThousandEyes.
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This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
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|
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- API version: 7.0.58
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- API version: 7.0.62
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- Generator version: 7.6.0
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- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
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@ -4,6 +4,7 @@ README.md
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docs/Alert.md
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docs/AlertDetail.md
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docs/AlertDirection.md
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docs/AlertEmbedded.md
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docs/AlertGroupType.md
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docs/AlertLinks.md
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docs/AlertMeta.md
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@ -22,6 +23,7 @@ docs/AlertTestType.md
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docs/AlertType.md
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docs/Alerts.md
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docs/AlertsApi.md
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docs/Asn.md
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docs/BaseAlert.md
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docs/BaseAlertSuppressionWindow.md
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docs/BaseRule.md
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@ -73,6 +75,7 @@ src/thousandeyes_sdk/alerts/models/__init__.py
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src/thousandeyes_sdk/alerts/models/alert.py
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src/thousandeyes_sdk/alerts/models/alert_detail.py
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src/thousandeyes_sdk/alerts/models/alert_direction.py
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src/thousandeyes_sdk/alerts/models/alert_embedded.py
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src/thousandeyes_sdk/alerts/models/alert_group_type.py
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src/thousandeyes_sdk/alerts/models/alert_links.py
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src/thousandeyes_sdk/alerts/models/alert_meta.py
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@ -88,6 +91,7 @@ src/thousandeyes_sdk/alerts/models/alert_suppression_windows.py
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src/thousandeyes_sdk/alerts/models/alert_test_type.py
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src/thousandeyes_sdk/alerts/models/alert_type.py
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src/thousandeyes_sdk/alerts/models/alerts.py
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src/thousandeyes_sdk/alerts/models/asn.py
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src/thousandeyes_sdk/alerts/models/base_alert.py
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src/thousandeyes_sdk/alerts/models/base_alert_suppression_window.py
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src/thousandeyes_sdk/alerts/models/base_rule.py
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@ -12,7 +12,7 @@ For more information about the alerts, see [Alerts](https://docs.thousandeyes.co
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This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
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- API version: 7.0.62
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||||
- Generator version: 7.6.0
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- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
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@ -123,6 +123,7 @@ Class | Method | HTTP request | Description
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- [Alert](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/Alert.md)
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- [AlertDetail](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/AlertDetail.md)
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- [AlertDirection](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/AlertDirection.md)
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- [AlertEmbedded](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/AlertEmbedded.md)
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- [AlertGroupType](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/AlertGroupType.md)
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- [AlertLinks](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/AlertLinks.md)
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- [AlertMeta](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/AlertMeta.md)
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@ -138,6 +139,7 @@ Class | Method | HTTP request | Description
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- [AlertTestType](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/AlertTestType.md)
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- [AlertType](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/AlertType.md)
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- [Alerts](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/Alerts.md)
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- [Asn](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/Asn.md)
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- [BaseAlert](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/BaseAlert.md)
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- [BaseAlertSuppressionWindow](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/BaseAlertSuppressionWindow.md)
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- [BaseRule](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-alerts/docs/BaseRule.md)
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@ -19,6 +19,7 @@ Name | Type | Description | Notes
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**alert_state** | [**State**](State.md) | | [optional]
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**alert_severity** | [**Severity**](Severity.md) | | [optional]
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**details** | [**List[AlertMetricDetail]**](AlertMetricDetail.md) | | [optional]
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**embedded** | [**AlertEmbedded**](AlertEmbedded.md) | | [optional]
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## Example
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30
thousandeyes-sdk-alerts/docs/AlertEmbedded.md
Normal file
30
thousandeyes-sdk-alerts/docs/AlertEmbedded.md
Normal file
@ -0,0 +1,30 @@
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# AlertEmbedded
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Container for embedded resources in alert responses (HATEOAS).
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## Properties
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Name | Type | Description | Notes
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------------ | ------------- | ------------- | -------------
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**asn** | [**Asn**](Asn.md) | | [optional]
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## Example
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```python
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from thousandeyes_sdk.alerts.models.alert_embedded import AlertEmbedded
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# TODO update the JSON string below
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json = "{}"
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# create an instance of AlertEmbedded from a JSON string
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alert_embedded_instance = AlertEmbedded.from_json(json)
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# print the JSON string representation of the object
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print(AlertEmbedded.to_json())
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# convert the object into a dict
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alert_embedded_dict = alert_embedded_instance.to_dict()
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# create an instance of AlertEmbedded from a dict
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alert_embedded_from_dict = AlertEmbedded.from_dict(alert_embedded_dict)
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```
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[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
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32
thousandeyes-sdk-alerts/docs/Asn.md
Normal file
32
thousandeyes-sdk-alerts/docs/Asn.md
Normal file
@ -0,0 +1,32 @@
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# Asn
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Autonomous System Number (ASN) information for network outage alerts.
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## Properties
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Name | Type | Description | Notes
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------------ | ------------- | ------------- | -------------
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**id** | **str** | ASN identifier. | [optional]
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**name** | **str** | Autonomous system name. | [optional]
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**type** | **str** | Resource type. | [optional]
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## Example
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```python
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from thousandeyes_sdk.alerts.models.asn import Asn
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# TODO update the JSON string below
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json = "{}"
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# create an instance of Asn from a JSON string
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asn_instance = Asn.from_json(json)
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# print the JSON string representation of the object
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print(Asn.to_json())
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# convert the object into a dict
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asn_dict = asn_instance.to_dict()
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# create an instance of Asn from a dict
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asn_from_dict = Asn.from_dict(asn_dict)
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```
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[[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
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@ -23,6 +23,7 @@ from thousandeyes_sdk.alerts.api.alerts_api import AlertsApi
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from thousandeyes_sdk.alerts.models.alert import Alert
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from thousandeyes_sdk.alerts.models.alert_detail import AlertDetail
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from thousandeyes_sdk.alerts.models.alert_direction import AlertDirection
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from thousandeyes_sdk.alerts.models.alert_embedded import AlertEmbedded
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from thousandeyes_sdk.alerts.models.alert_group_type import AlertGroupType
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from thousandeyes_sdk.alerts.models.alert_links import AlertLinks
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from thousandeyes_sdk.alerts.models.alert_meta import AlertMeta
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@ -38,6 +39,7 @@ from thousandeyes_sdk.alerts.models.alert_suppression_windows import AlertSuppre
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from thousandeyes_sdk.alerts.models.alert_test_type import AlertTestType
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from thousandeyes_sdk.alerts.models.alert_type import AlertType
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from thousandeyes_sdk.alerts.models.alerts import Alerts
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from thousandeyes_sdk.alerts.models.asn import Asn
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from thousandeyes_sdk.alerts.models.base_alert import BaseAlert
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from thousandeyes_sdk.alerts.models.base_alert_suppression_window import BaseAlertSuppressionWindow
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from thousandeyes_sdk.alerts.models.base_rule import BaseRule
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@ -16,6 +16,7 @@
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from thousandeyes_sdk.alerts.models.alert import Alert
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from thousandeyes_sdk.alerts.models.alert_detail import AlertDetail
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from thousandeyes_sdk.alerts.models.alert_direction import AlertDirection
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from thousandeyes_sdk.alerts.models.alert_embedded import AlertEmbedded
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from thousandeyes_sdk.alerts.models.alert_group_type import AlertGroupType
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from thousandeyes_sdk.alerts.models.alert_links import AlertLinks
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from thousandeyes_sdk.alerts.models.alert_meta import AlertMeta
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@ -31,6 +32,7 @@ from thousandeyes_sdk.alerts.models.alert_suppression_windows import AlertSuppre
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from thousandeyes_sdk.alerts.models.alert_test_type import AlertTestType
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from thousandeyes_sdk.alerts.models.alert_type import AlertType
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from thousandeyes_sdk.alerts.models.alerts import Alerts
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from thousandeyes_sdk.alerts.models.asn import Asn
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from thousandeyes_sdk.alerts.models.base_alert import BaseAlert
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from thousandeyes_sdk.alerts.models.base_alert_suppression_window import BaseAlertSuppressionWindow
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from thousandeyes_sdk.alerts.models.base_rule import BaseRule
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@ -19,6 +19,7 @@ import json
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from datetime import datetime
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from pydantic import BaseModel, ConfigDict, Field, StrictBool, StrictInt, StrictStr
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from typing import Any, ClassVar, Dict, List, Optional
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from thousandeyes_sdk.alerts.models.alert_embedded import AlertEmbedded
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from thousandeyes_sdk.alerts.models.alert_links import AlertLinks
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from thousandeyes_sdk.alerts.models.alert_meta import AlertMeta
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from thousandeyes_sdk.alerts.models.alert_metric_detail import AlertMetricDetail
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@ -46,7 +47,8 @@ class AlertDetail(BaseModel):
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alert_state: Optional[State] = Field(default=None, alias="alertState")
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alert_severity: Optional[Severity] = Field(default=None, alias="alertSeverity")
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details: Optional[List[AlertMetricDetail]] = None
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__properties: ClassVar[List[str]] = ["id", "alertType", "startDate", "endDate", "violationCount", "duration", "suppressed", "meta", "_links", "state", "severity", "alertState", "alertSeverity", "details"]
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embedded: Optional[AlertEmbedded] = Field(default=None, alias="_embedded")
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__properties: ClassVar[List[str]] = ["id", "alertType", "startDate", "endDate", "violationCount", "duration", "suppressed", "meta", "_links", "state", "severity", "alertState", "alertSeverity", "details", "_embedded"]
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model_config = ConfigDict(
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populate_by_name=True,
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@ -107,6 +109,9 @@ class AlertDetail(BaseModel):
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if _item:
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_items.append(_item.to_dict())
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_dict['details'] = _items
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# override the default output from pydantic by calling `to_dict()` of embedded
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if self.embedded:
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_dict['_embedded'] = self.embedded.to_dict()
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return _dict
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@classmethod
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@ -132,7 +137,8 @@ class AlertDetail(BaseModel):
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"severity": obj.get("severity"),
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"alertState": obj.get("alertState"),
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"alertSeverity": obj.get("alertSeverity"),
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"details": [AlertMetricDetail.from_dict(_item) for _item in obj["details"]] if obj.get("details") is not None else None
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"details": [AlertMetricDetail.from_dict(_item) for _item in obj["details"]] if obj.get("details") is not None else None,
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"_embedded": AlertEmbedded.from_dict(obj["_embedded"]) if obj.get("_embedded") is not None else None
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})
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return _obj
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@ -0,0 +1,91 @@
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# coding: utf-8
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"""
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Alerts API
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You can manage the following alert functionalities on the ThousandEyes platform using the Alerts API: * **Alerts**: Retrieve alert details. Alerts are assigned to tests through alert rules. * **Alert Rules**: Conditions that you configure in order to highlight or be notified of events of interest in your ThousandEyes tests. When an alert rule’s conditions are met, the associated alert is triggered and the alert becomes active. It remains active until the alert is cleared. Alert rules are reusable across multiple tests.. * **Alert Suppression Windows**: Suppress alerts for tests during periods such as planned maintenance. Windows can be one-time events or recurring events to handle periodic occurrences such as monthly downtime for maintenance. For more information about the alerts, see [Alerts](https://docs.thousandeyes.com/product-documentation/alerts).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
Do not edit the class manually.
|
||||
""" # noqa: E501
|
||||
|
||||
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from __future__ import annotations
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import pprint
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import re # noqa: F401
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import json
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from pydantic import BaseModel, ConfigDict
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from typing import Any, ClassVar, Dict, List, Optional
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from thousandeyes_sdk.alerts.models.asn import Asn
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from typing import Optional, Set
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from typing_extensions import Self
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class AlertEmbedded(BaseModel):
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"""
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Container for embedded resources in alert responses (HATEOAS).
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""" # noqa: E501
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asn: Optional[Asn] = None
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__properties: ClassVar[List[str]] = ["asn"]
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model_config = ConfigDict(
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populate_by_name=True,
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validate_assignment=True,
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protected_namespaces=(),
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extra="allow",
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)
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def to_str(self) -> str:
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"""Returns the string representation of the model using alias"""
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return pprint.pformat(self.model_dump(by_alias=True))
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def to_json(self) -> str:
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"""Returns the JSON representation of the model using alias"""
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# TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
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return self.model_dump_json(by_alias=True, exclude_unset=True, exclude_none=True)
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@classmethod
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def from_json(cls, json_str: str) -> Optional[Self]:
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"""Create an instance of AlertEmbedded from a JSON string"""
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return cls.from_dict(json.loads(json_str))
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def to_dict(self) -> Dict[str, Any]:
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"""Return the dictionary representation of the model using alias.
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This has the following differences from calling pydantic's
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`self.model_dump(by_alias=True)`:
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* `None` is only added to the output dict for nullable fields that
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were set at model initialization. Other fields with value `None`
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are ignored.
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"""
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excluded_fields: Set[str] = set([
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])
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_dict = self.model_dump(
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by_alias=True,
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exclude=excluded_fields,
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exclude_none=True,
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)
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# override the default output from pydantic by calling `to_dict()` of asn
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if self.asn:
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_dict['asn'] = self.asn.to_dict()
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return _dict
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@classmethod
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def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
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"""Create an instance of AlertEmbedded from a dict"""
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if obj is None:
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return None
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if not isinstance(obj, dict):
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return cls.model_validate(obj)
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_obj = cls.model_validate({
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"asn": Asn.from_dict(obj["asn"]) if obj.get("asn") is not None else None
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})
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return _obj
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@ -0,0 +1,91 @@
|
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# coding: utf-8
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|
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"""
|
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Alerts API
|
||||
|
||||
You can manage the following alert functionalities on the ThousandEyes platform using the Alerts API: * **Alerts**: Retrieve alert details. Alerts are assigned to tests through alert rules. * **Alert Rules**: Conditions that you configure in order to highlight or be notified of events of interest in your ThousandEyes tests. When an alert rule’s conditions are met, the associated alert is triggered and the alert becomes active. It remains active until the alert is cleared. Alert rules are reusable across multiple tests.. * **Alert Suppression Windows**: Suppress alerts for tests during periods such as planned maintenance. Windows can be one-time events or recurring events to handle periodic occurrences such as monthly downtime for maintenance. For more information about the alerts, see [Alerts](https://docs.thousandeyes.com/product-documentation/alerts).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
Do not edit the class manually.
|
||||
""" # noqa: E501
|
||||
|
||||
|
||||
from __future__ import annotations
|
||||
import pprint
|
||||
import re # noqa: F401
|
||||
import json
|
||||
|
||||
from pydantic import BaseModel, ConfigDict, Field, StrictStr
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||||
from typing import Any, ClassVar, Dict, List, Optional
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from typing import Optional, Set
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from typing_extensions import Self
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class Asn(BaseModel):
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"""
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Autonomous System Number (ASN) information for network outage alerts.
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""" # noqa: E501
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id: Optional[StrictStr] = Field(default=None, description="ASN identifier.")
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name: Optional[StrictStr] = Field(default=None, description="Autonomous system name.")
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type: Optional[StrictStr] = Field(default=None, description="Resource type.")
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__properties: ClassVar[List[str]] = ["id", "name", "type"]
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|
||||
model_config = ConfigDict(
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populate_by_name=True,
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validate_assignment=True,
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||||
protected_namespaces=(),
|
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extra="allow",
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||||
)
|
||||
|
||||
|
||||
def to_str(self) -> str:
|
||||
"""Returns the string representation of the model using alias"""
|
||||
return pprint.pformat(self.model_dump(by_alias=True))
|
||||
|
||||
def to_json(self) -> str:
|
||||
"""Returns the JSON representation of the model using alias"""
|
||||
# TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
|
||||
return self.model_dump_json(by_alias=True, exclude_unset=True, exclude_none=True)
|
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|
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@classmethod
|
||||
def from_json(cls, json_str: str) -> Optional[Self]:
|
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"""Create an instance of Asn from a JSON string"""
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return cls.from_dict(json.loads(json_str))
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""Return the dictionary representation of the model using alias.
|
||||
|
||||
This has the following differences from calling pydantic's
|
||||
`self.model_dump(by_alias=True)`:
|
||||
|
||||
* `None` is only added to the output dict for nullable fields that
|
||||
were set at model initialization. Other fields with value `None`
|
||||
are ignored.
|
||||
"""
|
||||
excluded_fields: Set[str] = set([
|
||||
])
|
||||
|
||||
_dict = self.model_dump(
|
||||
by_alias=True,
|
||||
exclude=excluded_fields,
|
||||
exclude_none=True,
|
||||
)
|
||||
return _dict
|
||||
|
||||
@classmethod
|
||||
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
|
||||
"""Create an instance of Asn from a dict"""
|
||||
if obj is None:
|
||||
return None
|
||||
|
||||
if not isinstance(obj, dict):
|
||||
return cls.model_validate(obj)
|
||||
|
||||
_obj = cls.model_validate({
|
||||
"id": obj.get("id"),
|
||||
"name": obj.get("name"),
|
||||
"type": obj.get("type")
|
||||
})
|
||||
return _obj
|
||||
|
||||
|
||||
@ -81,6 +81,13 @@ class TestAlertsApi(unittest.TestCase):
|
||||
"alertSeverity" : "major",
|
||||
"duration" : 60,
|
||||
"violationCount" : 2,
|
||||
"_embedded" : {
|
||||
"asn" : {
|
||||
"name" : "Cisco Webex LLC",
|
||||
"id" : "13445",
|
||||
"type" : "asn"
|
||||
}
|
||||
},
|
||||
"meta" : {
|
||||
"version" : 1
|
||||
},
|
||||
|
||||
@ -9,7 +9,7 @@ For more information about monitors, see [Inside-Out BGP Visibility](https://doc
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -13,7 +13,7 @@ For more information about credentials, see [Working With Secure Credentials](ht
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@ Manage ThousandEyes Dashboards.
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -9,7 +9,7 @@ To access Emulation API operations, the following permissions are required:
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -5,7 +5,7 @@ For more information about Endpoint Agents, see [Endpoint Agents](https://docs.t
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -16,6 +16,7 @@ Name | Type | Description | Notes
|
||||
**location_subdivision1_code** | **List[str]** | Filter using the code for the first level administrative division within the country. In US/Canada this is the State, in UK it's the country e.g. `ENG` | [optional]
|
||||
**location_city** | **List[str]** | This is a prefix match on the city name field. The endpoint expects this to contain the name of the city in English. e.g. 'Paris' or '' | [optional]
|
||||
**license_type** | [**List[AgentLicenseType]**](AgentLicenseType.md) | Filter on the agent's license type | [optional]
|
||||
**any_connect_device_id** | **List[str]** | IDs of devices that has the Cisco Secure Client deployed with the Internet Security module. Returns only agents that have at least one matching `anyConnectDeviceId`. | [optional]
|
||||
|
||||
## Example
|
||||
|
||||
|
||||
@ -5,7 +5,7 @@
|
||||
|
||||
Name | Type | Description | Notes
|
||||
------------ | ------------- | ------------- | -------------
|
||||
**key** | **str** | Name or identifier of the external metadata property. | [optional]
|
||||
**key** | **str** | ID of the device that has the Cisco Secure Client deployed with the Internet Security module. | [optional]
|
||||
**value** | **str** | Value of the external metadata property. | [optional]
|
||||
|
||||
## Example
|
||||
|
||||
@ -38,7 +38,8 @@ class AgentSearchFilters(BaseModel):
|
||||
location_subdivision1_code: Optional[List[StrictStr]] = Field(default=None, description="Filter using the code for the first level administrative division within the country. In US/Canada this is the State, in UK it's the country e.g. `ENG` ", alias="locationSubdivision1Code")
|
||||
location_city: Optional[List[StrictStr]] = Field(default=None, description="This is a prefix match on the city name field. The endpoint expects this to contain the name of the city in English. e.g. 'Paris' or '' ", alias="locationCity")
|
||||
license_type: Optional[List[AgentLicenseType]] = Field(default=None, description="Filter on the agent's license type ", alias="licenseType")
|
||||
__properties: ClassVar[List[str]] = ["id", "agentName", "computerName", "username", "userPrincipalName", "platform", "osVersion", "locationCountryISO", "locationSubdivision1Code", "locationCity", "licenseType"]
|
||||
any_connect_device_id: Optional[List[StrictStr]] = Field(default=None, description="IDs of devices that has the Cisco Secure Client deployed with the Internet Security module. Returns only agents that have at least one matching `anyConnectDeviceId`. ", alias="anyConnectDeviceId")
|
||||
__properties: ClassVar[List[str]] = ["id", "agentName", "computerName", "username", "userPrincipalName", "platform", "osVersion", "locationCountryISO", "locationSubdivision1Code", "locationCity", "licenseType", "anyConnectDeviceId"]
|
||||
|
||||
model_config = ConfigDict(
|
||||
populate_by_name=True,
|
||||
@ -102,7 +103,8 @@ class AgentSearchFilters(BaseModel):
|
||||
"locationCountryISO": obj.get("locationCountryISO"),
|
||||
"locationSubdivision1Code": obj.get("locationSubdivision1Code"),
|
||||
"locationCity": obj.get("locationCity"),
|
||||
"licenseType": obj.get("licenseType")
|
||||
"licenseType": obj.get("licenseType"),
|
||||
"anyConnectDeviceId": obj.get("anyConnectDeviceId")
|
||||
})
|
||||
return _obj
|
||||
|
||||
|
||||
@ -25,7 +25,7 @@ class ExternalMetadataItem(BaseModel):
|
||||
"""
|
||||
ExternalMetadataItem
|
||||
""" # noqa: E501
|
||||
key: Optional[StrictStr] = Field(default=None, description="Name or identifier of the external metadata property.")
|
||||
key: Optional[StrictStr] = Field(default=None, description="ID of the device that has the Cisco Secure Client deployed with the Internet Security module.")
|
||||
value: Optional[StrictStr] = Field(default=None, description="Value of the external metadata property.")
|
||||
__properties: ClassVar[List[str]] = ["key", "value"]
|
||||
|
||||
|
||||
@ -383,6 +383,7 @@ class TestEndpointAgentsApi(unittest.TestCase):
|
||||
"licenseType" : [ "essentials", "essentials" ],
|
||||
"osVersion" : [ "Version 10.15.2", "Version 10.15.2" ],
|
||||
"computerName" : [ "DESKTOP-45AE8", "DESKTOP-45AE8" ],
|
||||
"anyConnectDeviceId" : [ "JDLKSLFEIJER004334F" ],
|
||||
"locationCountryISO" : [ "FR", "FR" ],
|
||||
"agentName" : [ "myagent-1234", "myagent-1234" ],
|
||||
"locationSubdivision1Code" : [ "ENG", "ENG" ],
|
||||
|
||||
@ -13,7 +13,7 @@ The URLs for these API test data endpoints are provided within the test definiti
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -4,7 +4,7 @@ Manage labels applied to endpoint agents using this API.
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@ Retrieve results for scheduled and dynamic tests on endpoint agents.
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
@ -113,7 +113,7 @@ Class | Method | HTTP request | Description
|
||||
*NetworkEndpointScheduledTestResultsApi* | [**filter_scheduled_tests_network_results**](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-endpoint-test-results/docs/NetworkEndpointScheduledTestResultsApi.md#filter_scheduled_tests_network_results) | **POST** /endpoint/test-results/scheduled-tests/network/filter | Retrieve network scheduled test results from multiple tests
|
||||
*NetworkEndpointScheduledTestResultsApi* | [**get_scheduled_test_path_vis_agent_round_results**](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-endpoint-test-results/docs/NetworkEndpointScheduledTestResultsApi.md#get_scheduled_test_path_vis_agent_round_results) | **GET** /endpoint/test-results/scheduled-tests/{testId}/path-vis/agent/{agentId}/round/{roundId} | Retrieve path visualization network scheduled test results details
|
||||
*NetworkEndpointScheduledTestResultsApi* | [**get_scheduled_test_path_vis_results**](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-endpoint-test-results/docs/NetworkEndpointScheduledTestResultsApi.md#get_scheduled_test_path_vis_results) | **GET** /endpoint/test-results/scheduled-tests/{testId}/path-vis | Retrieve path visualization network scheduled test results
|
||||
*RealUserEndpointTestResultsApi* | [**filter_real_user_tests_network_results**](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-endpoint-test-results/docs/RealUserEndpointTestResultsApi.md#filter_real_user_tests_network_results) | **POST** /endpoint/test-results/real-user-tests/networks/filter | List endpoint real user tests
|
||||
*RealUserEndpointTestResultsApi* | [**filter_real_user_tests_network_results**](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-endpoint-test-results/docs/RealUserEndpointTestResultsApi.md#filter_real_user_tests_network_results) | **POST** /endpoint/test-results/real-user-tests/networks/filter | List endpoint real user tests networks
|
||||
*RealUserEndpointTestResultsApi* | [**filter_real_user_tests_results**](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-endpoint-test-results/docs/RealUserEndpointTestResultsApi.md#filter_real_user_tests_results) | **POST** /endpoint/test-results/real-user-tests/filter | List endpoint real user tests
|
||||
*RealUserEndpointTestResultsApi* | [**filter_real_user_tests_visited_pages_results**](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-endpoint-test-results/docs/RealUserEndpointTestResultsApi.md#filter_real_user_tests_visited_pages_results) | **POST** /endpoint/test-results/real-user-tests/pages/filter | List endpoint real user tests visited pages
|
||||
*RealUserEndpointTestResultsApi* | [**get_real_user_test_page_results**](https://github.com/thousandeyes/thousandeyes-sdk-python//tree/main/thousandeyes-sdk-endpoint-test-results/docs/RealUserEndpointTestResultsApi.md#get_real_user_test_page_results) | **GET** /endpoint/test-results/real-user-tests/{id}/pages/{pageId} | Retrieve endpoint real user test page
|
||||
|
||||
@ -4,7 +4,7 @@ All URIs are relative to *https://api.thousandeyes.com/v7*
|
||||
|
||||
Method | HTTP request | Description
|
||||
------------- | ------------- | -------------
|
||||
[**filter_real_user_tests_network_results**](RealUserEndpointTestResultsApi.md#filter_real_user_tests_network_results) | **POST** /endpoint/test-results/real-user-tests/networks/filter | List endpoint real user tests
|
||||
[**filter_real_user_tests_network_results**](RealUserEndpointTestResultsApi.md#filter_real_user_tests_network_results) | **POST** /endpoint/test-results/real-user-tests/networks/filter | List endpoint real user tests networks
|
||||
[**filter_real_user_tests_results**](RealUserEndpointTestResultsApi.md#filter_real_user_tests_results) | **POST** /endpoint/test-results/real-user-tests/filter | List endpoint real user tests
|
||||
[**filter_real_user_tests_visited_pages_results**](RealUserEndpointTestResultsApi.md#filter_real_user_tests_visited_pages_results) | **POST** /endpoint/test-results/real-user-tests/pages/filter | List endpoint real user tests visited pages
|
||||
[**get_real_user_test_page_results**](RealUserEndpointTestResultsApi.md#get_real_user_test_page_results) | **GET** /endpoint/test-results/real-user-tests/{id}/pages/{pageId} | Retrieve endpoint real user test page
|
||||
@ -14,7 +14,7 @@ Method | HTTP request | Description
|
||||
# **filter_real_user_tests_network_results**
|
||||
> RealUserEndpointTestNetworkResults filter_real_user_tests_network_results(aid=aid, window=window, start_date=start_date, end_date=end_date, cursor=cursor, real_user_endpoint_test_results_request=real_user_endpoint_test_results_request)
|
||||
|
||||
List endpoint real user tests
|
||||
List endpoint real user tests networks
|
||||
|
||||
Returns a list of all endpoint real user tests. Sessions from the last round are provided unless an explicit start and end is provided with `startDate`, `endDate` or `window` optional parameters. ## Request body filters This endpoint supports complex filtering using the request body. It is important these filters remain unaltered when making use of pagination, otherwise the results will not be coherent with the original request. ### Multiple filter fields When multiple filter fields are provided, a logical `AND` is applied between the filters. ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"platform\": [ \"mac\" ], \"domain\": [ \"thousandeyes.com\" ] }}' ``` ### Filter field with multiple values When a filter field contains multiple values, a logical `OR` is applied between the filter values. ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"networkId\": [ \"660b34109d12\", \"660b34109d15\" ] }}' ``` ### Combination of request parameters and body filters ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter?window=1w' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"platform\": [ \"mac\" ], \"domain\": [ \"thousandeyes.com\" ], \"networkId\": [ \"660b34109d12\", \"660b34109d15\" ] }}' ``` Returns a `results` array of endpoint real user tests. Network sessions shown are from the latest round, or based on the time range specified.
|
||||
|
||||
@ -57,7 +57,7 @@ with thousandeyes_sdk.core.ApiClient(configuration) as api_client:
|
||||
real_user_endpoint_test_results_request = thousandeyes_sdk.endpoint_test_results.RealUserEndpointTestResultsRequest() # RealUserEndpointTestResultsRequest | (optional)
|
||||
|
||||
try:
|
||||
# List endpoint real user tests
|
||||
# List endpoint real user tests networks
|
||||
api_response = api_instance.filter_real_user_tests_network_results(aid=aid, window=window, start_date=start_date, end_date=end_date, cursor=cursor, real_user_endpoint_test_results_request=real_user_endpoint_test_results_request)
|
||||
print("The response of RealUserEndpointTestResultsApi->filter_real_user_tests_network_results:\n")
|
||||
pprint(api_response)
|
||||
|
||||
@ -71,7 +71,7 @@ class RealUserEndpointTestResultsApi:
|
||||
_headers: Optional[Dict[StrictStr, Any]] = None,
|
||||
_host_index: Annotated[StrictInt, Field(ge=0, le=0)] = 0,
|
||||
) -> RealUserEndpointTestNetworkResults:
|
||||
"""List endpoint real user tests
|
||||
"""List endpoint real user tests networks
|
||||
|
||||
Returns a list of all endpoint real user tests. Sessions from the last round are provided unless an explicit start and end is provided with `startDate`, `endDate` or `window` optional parameters. ## Request body filters This endpoint supports complex filtering using the request body. It is important these filters remain unaltered when making use of pagination, otherwise the results will not be coherent with the original request. ### Multiple filter fields When multiple filter fields are provided, a logical `AND` is applied between the filters. ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"platform\": [ \"mac\" ], \"domain\": [ \"thousandeyes.com\" ] }}' ``` ### Filter field with multiple values When a filter field contains multiple values, a logical `OR` is applied between the filter values. ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"networkId\": [ \"660b34109d12\", \"660b34109d15\" ] }}' ``` ### Combination of request parameters and body filters ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter?window=1w' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"platform\": [ \"mac\" ], \"domain\": [ \"thousandeyes.com\" ], \"networkId\": [ \"660b34109d12\", \"660b34109d15\" ] }}' ``` Returns a `results` array of endpoint real user tests. Network sessions shown are from the latest round, or based on the time range specified.
|
||||
|
||||
@ -166,7 +166,7 @@ class RealUserEndpointTestResultsApi:
|
||||
_headers: Optional[Dict[StrictStr, Any]] = None,
|
||||
_host_index: Annotated[StrictInt, Field(ge=0, le=0)] = 0,
|
||||
) -> ApiResponse[RealUserEndpointTestNetworkResults]:
|
||||
"""List endpoint real user tests
|
||||
"""List endpoint real user tests networks
|
||||
|
||||
Returns a list of all endpoint real user tests. Sessions from the last round are provided unless an explicit start and end is provided with `startDate`, `endDate` or `window` optional parameters. ## Request body filters This endpoint supports complex filtering using the request body. It is important these filters remain unaltered when making use of pagination, otherwise the results will not be coherent with the original request. ### Multiple filter fields When multiple filter fields are provided, a logical `AND` is applied between the filters. ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"platform\": [ \"mac\" ], \"domain\": [ \"thousandeyes.com\" ] }}' ``` ### Filter field with multiple values When a filter field contains multiple values, a logical `OR` is applied between the filter values. ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"networkId\": [ \"660b34109d12\", \"660b34109d15\" ] }}' ``` ### Combination of request parameters and body filters ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter?window=1w' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"platform\": [ \"mac\" ], \"domain\": [ \"thousandeyes.com\" ], \"networkId\": [ \"660b34109d12\", \"660b34109d15\" ] }}' ``` Returns a `results` array of endpoint real user tests. Network sessions shown are from the latest round, or based on the time range specified.
|
||||
|
||||
@ -261,7 +261,7 @@ class RealUserEndpointTestResultsApi:
|
||||
_headers: Optional[Dict[StrictStr, Any]] = None,
|
||||
_host_index: Annotated[StrictInt, Field(ge=0, le=0)] = 0,
|
||||
) -> RESTResponseType:
|
||||
"""List endpoint real user tests
|
||||
"""List endpoint real user tests networks
|
||||
|
||||
Returns a list of all endpoint real user tests. Sessions from the last round are provided unless an explicit start and end is provided with `startDate`, `endDate` or `window` optional parameters. ## Request body filters This endpoint supports complex filtering using the request body. It is important these filters remain unaltered when making use of pagination, otherwise the results will not be coherent with the original request. ### Multiple filter fields When multiple filter fields are provided, a logical `AND` is applied between the filters. ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"platform\": [ \"mac\" ], \"domain\": [ \"thousandeyes.com\" ] }}' ``` ### Filter field with multiple values When a filter field contains multiple values, a logical `OR` is applied between the filter values. ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"networkId\": [ \"660b34109d12\", \"660b34109d15\" ] }}' ``` ### Combination of request parameters and body filters ``` curl --location --request POST 'https://api.thousandeyes.com/v7/endpoint/test-results/real-user-tests/networks/filter?window=1w' --header 'Authorization: Bearer $token' --header 'Content-Type: application/json' --data-raw '{ \"searchFilters\": { \"platform\": [ \"mac\" ], \"domain\": [ \"thousandeyes.com\" ], \"networkId\": [ \"660b34109d12\", \"660b34109d15\" ] }}' ``` Returns a `results` array of endpoint real user tests. Network sessions shown are from the latest round, or based on the time range specified.
|
||||
|
||||
|
||||
@ -5,7 +5,7 @@ Manage endpoint agent dynamic and scheduled tests using the Endpoint Tests API.
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -12,7 +12,7 @@ With the Events API, you can perform the following tasks on the ThousandEyes pla
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -6,7 +6,7 @@ The response does not include the immediate test results. Use the Test Results e
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -54,7 +54,7 @@ Name | Type | Description | Notes
|
||||
**override_proxy_id** | **str** | ID of the proxy to be used if the default proxy is overridden. | [optional]
|
||||
**collect_proxy_network_data** | **bool** | Indicates whether network data to the proxy should be collected. | [optional] [default to False]
|
||||
**emulated_device_id** | **str** | ID of the emulated device, if specified when the test was created. | [optional]
|
||||
**target_time** | **int** | Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior). | [optional]
|
||||
**target_time** | **int** | Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value. | [optional] [default to 10]
|
||||
**time_limit** | **int** | Time limit for transaction in seconds. | [optional] [default to 30]
|
||||
**transaction_script** | **str** | JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ). |
|
||||
**block_domains** | **str** | Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests. | [optional]
|
||||
|
||||
@ -54,7 +54,7 @@ Name | Type | Description | Notes
|
||||
**override_proxy_id** | **str** | ID of the proxy to be used if the default proxy is overridden. | [optional]
|
||||
**collect_proxy_network_data** | **bool** | Indicates whether network data to the proxy should be collected. | [optional] [default to False]
|
||||
**emulated_device_id** | **str** | ID of the emulated device, if specified when the test was created. | [optional]
|
||||
**target_time** | **int** | Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior). | [optional]
|
||||
**target_time** | **int** | Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value. | [optional] [default to 10]
|
||||
**time_limit** | **int** | Time limit for transaction in seconds. | [optional] [default to 30]
|
||||
**transaction_script** | **str** | JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ). |
|
||||
**block_domains** | **str** | Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests. | [optional]
|
||||
|
||||
@ -54,7 +54,7 @@ Name | Type | Description | Notes
|
||||
**override_proxy_id** | **str** | ID of the proxy to be used if the default proxy is overridden. | [optional]
|
||||
**collect_proxy_network_data** | **bool** | Indicates whether network data to the proxy should be collected. | [optional] [default to False]
|
||||
**emulated_device_id** | **str** | ID of the emulated device, if specified when the test was created. | [optional]
|
||||
**target_time** | **int** | Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior). | [optional]
|
||||
**target_time** | **int** | Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value. | [optional] [default to 10]
|
||||
**time_limit** | **int** | Time limit for transaction in seconds. | [optional] [default to 30]
|
||||
**transaction_script** | **str** | JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ). |
|
||||
**block_domains** | **str** | Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests. | [optional]
|
||||
|
||||
@ -41,7 +41,7 @@ Name | Type | Description | Notes
|
||||
**override_proxy_id** | **str** | ID of the proxy to be used if the default proxy is overridden. | [optional]
|
||||
**collect_proxy_network_data** | **bool** | Indicates whether network data to the proxy should be collected. | [optional] [default to False]
|
||||
**emulated_device_id** | **str** | ID of the emulated device, if specified when the test was created. | [optional]
|
||||
**target_time** | **int** | Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior). | [optional]
|
||||
**target_time** | **int** | Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value. | [optional] [default to 10]
|
||||
**time_limit** | **int** | Time limit for transaction in seconds. | [optional] [default to 30]
|
||||
**transaction_script** | **str** | JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ). |
|
||||
**block_domains** | **str** | Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests. | [optional]
|
||||
|
||||
@ -88,7 +88,7 @@ class WebTransactionInstantTest(BaseModel):
|
||||
override_proxy_id: Optional[StrictStr] = Field(default=None, description="ID of the proxy to be used if the default proxy is overridden.", alias="overrideProxyId")
|
||||
collect_proxy_network_data: Optional[StrictBool] = Field(default=False, description="Indicates whether network data to the proxy should be collected.", alias="collectProxyNetworkData")
|
||||
emulated_device_id: Optional[StrictStr] = Field(default=None, description="ID of the emulated device, if specified when the test was created.", alias="emulatedDeviceId")
|
||||
target_time: Optional[Annotated[int, Field(le=60, strict=True, ge=0)]] = Field(default=None, description="Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior).", alias="targetTime")
|
||||
target_time: Optional[Annotated[int, Field(le=180, strict=True, ge=0)]] = Field(default=10, description="Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value.", alias="targetTime")
|
||||
time_limit: Optional[Annotated[int, Field(le=180, strict=True, ge=5)]] = Field(default=30, description="Time limit for transaction in seconds.", alias="timeLimit")
|
||||
transaction_script: StrictStr = Field(description="JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ).", alias="transactionScript")
|
||||
block_domains: Optional[StrictStr] = Field(default=None, description="Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests.", alias="blockDomains")
|
||||
@ -251,7 +251,7 @@ class WebTransactionInstantTest(BaseModel):
|
||||
"overrideProxyId": obj.get("overrideProxyId"),
|
||||
"collectProxyNetworkData": obj.get("collectProxyNetworkData") if obj.get("collectProxyNetworkData") is not None else False,
|
||||
"emulatedDeviceId": obj.get("emulatedDeviceId"),
|
||||
"targetTime": obj.get("targetTime"),
|
||||
"targetTime": obj.get("targetTime") if obj.get("targetTime") is not None else 10,
|
||||
"timeLimit": obj.get("timeLimit") if obj.get("timeLimit") is not None else 30,
|
||||
"transactionScript": obj.get("transactionScript"),
|
||||
"blockDomains": obj.get("blockDomains"),
|
||||
|
||||
@ -87,7 +87,7 @@ class WebTransactionInstantTestRequest(BaseModel):
|
||||
override_proxy_id: Optional[StrictStr] = Field(default=None, description="ID of the proxy to be used if the default proxy is overridden.", alias="overrideProxyId")
|
||||
collect_proxy_network_data: Optional[StrictBool] = Field(default=False, description="Indicates whether network data to the proxy should be collected.", alias="collectProxyNetworkData")
|
||||
emulated_device_id: Optional[StrictStr] = Field(default=None, description="ID of the emulated device, if specified when the test was created.", alias="emulatedDeviceId")
|
||||
target_time: Optional[Annotated[int, Field(le=60, strict=True, ge=0)]] = Field(default=None, description="Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior).", alias="targetTime")
|
||||
target_time: Optional[Annotated[int, Field(le=180, strict=True, ge=0)]] = Field(default=10, description="Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value.", alias="targetTime")
|
||||
time_limit: Optional[Annotated[int, Field(le=180, strict=True, ge=5)]] = Field(default=30, description="Time limit for transaction in seconds.", alias="timeLimit")
|
||||
transaction_script: StrictStr = Field(description="JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ).", alias="transactionScript")
|
||||
block_domains: Optional[StrictStr] = Field(default=None, description="Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests.", alias="blockDomains")
|
||||
@ -240,7 +240,7 @@ class WebTransactionInstantTestRequest(BaseModel):
|
||||
"overrideProxyId": obj.get("overrideProxyId"),
|
||||
"collectProxyNetworkData": obj.get("collectProxyNetworkData") if obj.get("collectProxyNetworkData") is not None else False,
|
||||
"emulatedDeviceId": obj.get("emulatedDeviceId"),
|
||||
"targetTime": obj.get("targetTime"),
|
||||
"targetTime": obj.get("targetTime") if obj.get("targetTime") is not None else 10,
|
||||
"timeLimit": obj.get("timeLimit") if obj.get("timeLimit") is not None else 30,
|
||||
"transactionScript": obj.get("transactionScript"),
|
||||
"blockDomains": obj.get("blockDomains"),
|
||||
|
||||
@ -89,7 +89,7 @@ class WebTransactionInstantTestResponse(BaseModel):
|
||||
override_proxy_id: Optional[StrictStr] = Field(default=None, description="ID of the proxy to be used if the default proxy is overridden.", alias="overrideProxyId")
|
||||
collect_proxy_network_data: Optional[StrictBool] = Field(default=False, description="Indicates whether network data to the proxy should be collected.", alias="collectProxyNetworkData")
|
||||
emulated_device_id: Optional[StrictStr] = Field(default=None, description="ID of the emulated device, if specified when the test was created.", alias="emulatedDeviceId")
|
||||
target_time: Optional[Annotated[int, Field(le=60, strict=True, ge=0)]] = Field(default=None, description="Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior).", alias="targetTime")
|
||||
target_time: Optional[Annotated[int, Field(le=180, strict=True, ge=0)]] = Field(default=10, description="Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value.", alias="targetTime")
|
||||
time_limit: Optional[Annotated[int, Field(le=180, strict=True, ge=5)]] = Field(default=30, description="Time limit for transaction in seconds.", alias="timeLimit")
|
||||
transaction_script: StrictStr = Field(description="JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ).", alias="transactionScript")
|
||||
block_domains: Optional[StrictStr] = Field(default=None, description="Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests.", alias="blockDomains")
|
||||
@ -260,7 +260,7 @@ class WebTransactionInstantTestResponse(BaseModel):
|
||||
"overrideProxyId": obj.get("overrideProxyId"),
|
||||
"collectProxyNetworkData": obj.get("collectProxyNetworkData") if obj.get("collectProxyNetworkData") is not None else False,
|
||||
"emulatedDeviceId": obj.get("emulatedDeviceId"),
|
||||
"targetTime": obj.get("targetTime"),
|
||||
"targetTime": obj.get("targetTime") if obj.get("targetTime") is not None else 10,
|
||||
"timeLimit": obj.get("timeLimit") if obj.get("timeLimit") is not None else 30,
|
||||
"transactionScript": obj.get("transactionScript"),
|
||||
"blockDomains": obj.get("blockDomains"),
|
||||
|
||||
@ -71,7 +71,7 @@ class WebTransactionProperties(BaseModel):
|
||||
override_proxy_id: Optional[StrictStr] = Field(default=None, description="ID of the proxy to be used if the default proxy is overridden.", alias="overrideProxyId")
|
||||
collect_proxy_network_data: Optional[StrictBool] = Field(default=False, description="Indicates whether network data to the proxy should be collected.", alias="collectProxyNetworkData")
|
||||
emulated_device_id: Optional[StrictStr] = Field(default=None, description="ID of the emulated device, if specified when the test was created.", alias="emulatedDeviceId")
|
||||
target_time: Optional[Annotated[int, Field(le=60, strict=True, ge=0)]] = Field(default=None, description="Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior).", alias="targetTime")
|
||||
target_time: Optional[Annotated[int, Field(le=180, strict=True, ge=0)]] = Field(default=10, description="Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value.", alias="targetTime")
|
||||
time_limit: Optional[Annotated[int, Field(le=180, strict=True, ge=5)]] = Field(default=30, description="Time limit for transaction in seconds.", alias="timeLimit")
|
||||
transaction_script: StrictStr = Field(description="JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ).", alias="transactionScript")
|
||||
block_domains: Optional[StrictStr] = Field(default=None, description="Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests.", alias="blockDomains")
|
||||
@ -186,7 +186,7 @@ class WebTransactionProperties(BaseModel):
|
||||
"overrideProxyId": obj.get("overrideProxyId"),
|
||||
"collectProxyNetworkData": obj.get("collectProxyNetworkData") if obj.get("collectProxyNetworkData") is not None else False,
|
||||
"emulatedDeviceId": obj.get("emulatedDeviceId"),
|
||||
"targetTime": obj.get("targetTime"),
|
||||
"targetTime": obj.get("targetTime") if obj.get("targetTime") is not None else 10,
|
||||
"timeLimit": obj.get("timeLimit") if obj.get("timeLimit") is not None else 30,
|
||||
"transactionScript": obj.get("transactionScript"),
|
||||
"blockDomains": obj.get("blockDomains"),
|
||||
|
||||
@ -14,7 +14,7 @@ For more information about Internet Insights, see the [Internet Insights](https:
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@ Creates a new test snapshot in ThousandEyes.
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -10,12 +10,12 @@ detail, filter, and push the data to the customer-configured endpoints, dependin
|
||||
* Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client
|
||||
configuration.
|
||||
|
||||
For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -14,7 +14,7 @@ Name | Type | Description | Notes
|
||||
**stream_endpoint_url** | **str** | The URL ThousandEyes sends data stream to. For a URL to be valid, it needs to: - Be syntactically correct. - Be reachable. - Use the HTTPS protocol. - When using the `grpc` endpointType, streamEndpointUrl cannot contain paths: - Valid . `grpc` - `https://example.com` - Invalid . `grpc` - `https://example.com/collector`. - Valid . `http` - `https://example.com/collector`. - When using the `http` endpointType, the operation must match the exact final full URL (including the path if there is one) to which the data will be sent. Examples below: - `https://api.honeycomb.io:443/v1/metrics` - `https://ingest.eu0.signalfx.com/v2/datapoint/otlp` | [optional]
|
||||
**data_model_version** | [**DataModelVersion**](DataModelVersion.md) | | [optional]
|
||||
**custom_headers** | **Dict[str, str]** | Custom headers. | [optional]
|
||||
**tag_match** | [**List[TagMatch]**](TagMatch.md) | A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. | [optional]
|
||||
**tag_match** | [**List[TagMatch]**](TagMatch.md) | A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. Tags are invalid if the tag key includes characters that are not allowed by the [OpenTelemetry naming recommendations for attributes](https://opentelemetry.io/docs/specs/semconv/general/naming/#recommendations-for-application-developers). | [optional]
|
||||
**test_match** | [**List[TestMatch]**](TestMatch.md) | A collection of tests to be included in the data stream. | [optional]
|
||||
**filters** | [**Filters**](Filters.md) | | [optional]
|
||||
**exporter_config** | [**ExporterConfig**](ExporterConfig.md) | | [optional]
|
||||
|
||||
@ -14,7 +14,7 @@ Name | Type | Description | Notes
|
||||
**stream_endpoint_url** | **str** | The URL ThousandEyes sends data stream to. For a URL to be valid, it needs to: - Be syntactically correct. - Be reachable. - Use the HTTPS protocol. - When using the `grpc` endpointType, streamEndpointUrl cannot contain paths: - Valid . `grpc` - `https://example.com` - Invalid . `grpc` - `https://example.com/collector`. - Valid . `http` - `https://example.com/collector`. - When using the `http` endpointType, the operation must match the exact final full URL (including the path if there is one) to which the data will be sent. Examples below: - `https://api.honeycomb.io:443/v1/metrics` - `https://ingest.eu0.signalfx.com/v2/datapoint/otlp` | [optional]
|
||||
**data_model_version** | [**DataModelVersion**](DataModelVersion.md) | | [optional]
|
||||
**custom_headers** | **Dict[str, str]** | Custom headers. | [optional]
|
||||
**tag_match** | [**List[TagMatch]**](TagMatch.md) | A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. | [optional]
|
||||
**tag_match** | [**List[TagMatch]**](TagMatch.md) | A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. Tags are invalid if the tag key includes characters that are not allowed by the [OpenTelemetry naming recommendations for attributes](https://opentelemetry.io/docs/specs/semconv/general/naming/#recommendations-for-application-developers). | [optional]
|
||||
**test_match** | [**List[TestMatch]**](TestMatch.md) | A collection of tests to be included in the data stream. | [optional]
|
||||
**filters** | [**Filters**](Filters.md) | | [optional]
|
||||
**exporter_config** | [**ExporterConfig**](ExporterConfig.md) | | [optional]
|
||||
|
||||
@ -7,7 +7,7 @@ Name | Type | Description | Notes
|
||||
------------ | ------------- | ------------- | -------------
|
||||
**custom_headers** | **Dict[str, str]** | Custom headers. | [optional]
|
||||
**stream_endpoint_url** | **str** | The URL ThousandEyes sends data stream to. For a URL to be valid, it needs to: - Be syntactically correct. - Be reachable. - Use the HTTPS protocol. - When using the `grpc` endpointType, streamEndpointUrl cannot contain paths: - Valid . `grpc` - `https://example.com` - Invalid . `grpc` - `https://example.com/collector`. - Valid . `http` - `https://example.com/collector`. - When using the `http` endpointType, the operation must match the exact final full URL (including the path if there is one) to which the data will be sent. Examples below: - `https://api.honeycomb.io:443/v1/metrics` - `https://ingest.eu0.signalfx.com/v2/datapoint/otlp` | [optional]
|
||||
**tag_match** | [**List[TagMatch]**](TagMatch.md) | A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. | [optional]
|
||||
**tag_match** | [**List[TagMatch]**](TagMatch.md) | A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. Tags are invalid if the tag key includes characters that are not allowed by the [OpenTelemetry naming recommendations for attributes](https://opentelemetry.io/docs/specs/semconv/general/naming/#recommendations-for-application-developers). | [optional]
|
||||
**test_match** | [**List[TestMatch]**](TestMatch.md) | A collection of tests to be included in the data stream. | [optional]
|
||||
**enabled** | **bool** | Flag to enable or disable the stream integration. | [optional]
|
||||
**filters** | [**Filters**](Filters.md) | | [optional]
|
||||
|
||||
@ -7,7 +7,7 @@ Name | Type | Description | Notes
|
||||
------------ | ------------- | ------------- | -------------
|
||||
**custom_headers** | **Dict[str, str]** | Custom headers. | [optional]
|
||||
**stream_endpoint_url** | **str** | The URL ThousandEyes sends data stream to. For a URL to be valid, it needs to: - Be syntactically correct. - Be reachable. - Use the HTTPS protocol. - When using the `grpc` endpointType, streamEndpointUrl cannot contain paths: - Valid . `grpc` - `https://example.com` - Invalid . `grpc` - `https://example.com/collector`. - Valid . `http` - `https://example.com/collector`. - When using the `http` endpointType, the operation must match the exact final full URL (including the path if there is one) to which the data will be sent. Examples below: - `https://api.honeycomb.io:443/v1/metrics` - `https://ingest.eu0.signalfx.com/v2/datapoint/otlp` | [optional]
|
||||
**tag_match** | [**List[TagMatch]**](TagMatch.md) | A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. | [optional]
|
||||
**tag_match** | [**List[TagMatch]**](TagMatch.md) | A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. Tags are invalid if the tag key includes characters that are not allowed by the [OpenTelemetry naming recommendations for attributes](https://opentelemetry.io/docs/specs/semconv/general/naming/#recommendations-for-application-developers). | [optional]
|
||||
**test_match** | [**List[TestMatch]**](TestMatch.md) | A collection of tests to be included in the data stream. | [optional]
|
||||
**enabled** | **bool** | Flag to enable or disable the stream integration. | [optional]
|
||||
**filters** | [**Filters**](Filters.md) | | [optional]
|
||||
|
||||
@ -5,7 +5,7 @@
|
||||
|
||||
Name | Type | Description | Notes
|
||||
------------ | ------------- | ------------- | -------------
|
||||
**key** | **str** | The name of the tag key to match | [optional]
|
||||
**key** | **str** | The name of the tag key to match. The key is invalid if it includes characters that are not allowed by the [OpenTelemetry naming recommendations for attributes](https://opentelemetry.io/docs/specs/semconv/general/naming/#recommendations-for-application-developers). | [optional]
|
||||
**value** | **str** | The value of the tag to match | [optional]
|
||||
|
||||
## Example
|
||||
|
||||
@ -5,7 +5,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -4,7 +4,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
@ -45,7 +45,7 @@ class CreateStreamResponse(BaseModel):
|
||||
stream_endpoint_url: Optional[StrictStr] = Field(default=None, description="The URL ThousandEyes sends data stream to. For a URL to be valid, it needs to: - Be syntactically correct. - Be reachable. - Use the HTTPS protocol. - When using the `grpc` endpointType, streamEndpointUrl cannot contain paths: - Valid . `grpc` - `https://example.com` - Invalid . `grpc` - `https://example.com/collector`. - Valid . `http` - `https://example.com/collector`. - When using the `http` endpointType, the operation must match the exact final full URL (including the path if there is one) to which the data will be sent. Examples below: - `https://api.honeycomb.io:443/v1/metrics` - `https://ingest.eu0.signalfx.com/v2/datapoint/otlp`", alias="streamEndpointUrl")
|
||||
data_model_version: Optional[DataModelVersion] = Field(default=None, alias="dataModelVersion")
|
||||
custom_headers: Optional[Dict[str, StrictStr]] = Field(default=None, description="Custom headers.", alias="customHeaders")
|
||||
tag_match: Optional[List[TagMatch]] = Field(default=None, description="A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics.", alias="tagMatch")
|
||||
tag_match: Optional[List[TagMatch]] = Field(default=None, description="A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. Tags are invalid if the tag key includes characters that are not allowed by the [OpenTelemetry naming recommendations for attributes](https://opentelemetry.io/docs/specs/semconv/general/naming/#recommendations-for-application-developers).", alias="tagMatch")
|
||||
test_match: Optional[List[TestMatch]] = Field(default=None, description="A collection of tests to be included in the data stream.", alias="testMatch")
|
||||
filters: Optional[Filters] = None
|
||||
exporter_config: Optional[ExporterConfig] = Field(default=None, alias="exporterConfig")
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
@ -45,7 +45,7 @@ class GetStreamResponse(BaseModel):
|
||||
stream_endpoint_url: Optional[StrictStr] = Field(default=None, description="The URL ThousandEyes sends data stream to. For a URL to be valid, it needs to: - Be syntactically correct. - Be reachable. - Use the HTTPS protocol. - When using the `grpc` endpointType, streamEndpointUrl cannot contain paths: - Valid . `grpc` - `https://example.com` - Invalid . `grpc` - `https://example.com/collector`. - Valid . `http` - `https://example.com/collector`. - When using the `http` endpointType, the operation must match the exact final full URL (including the path if there is one) to which the data will be sent. Examples below: - `https://api.honeycomb.io:443/v1/metrics` - `https://ingest.eu0.signalfx.com/v2/datapoint/otlp`", alias="streamEndpointUrl")
|
||||
data_model_version: Optional[DataModelVersion] = Field(default=None, alias="dataModelVersion")
|
||||
custom_headers: Optional[Dict[str, StrictStr]] = Field(default=None, description="Custom headers.", alias="customHeaders")
|
||||
tag_match: Optional[List[TagMatch]] = Field(default=None, description="A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics.", alias="tagMatch")
|
||||
tag_match: Optional[List[TagMatch]] = Field(default=None, description="A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. Tags are invalid if the tag key includes characters that are not allowed by the [OpenTelemetry naming recommendations for attributes](https://opentelemetry.io/docs/specs/semconv/general/naming/#recommendations-for-application-developers).", alias="tagMatch")
|
||||
test_match: Optional[List[TestMatch]] = Field(default=None, description="A collection of tests to be included in the data stream.", alias="testMatch")
|
||||
filters: Optional[Filters] = None
|
||||
exporter_config: Optional[ExporterConfig] = Field(default=None, alias="exporterConfig")
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
@ -31,7 +31,7 @@ class PutStream(BaseModel):
|
||||
""" # noqa: E501
|
||||
custom_headers: Optional[Dict[str, StrictStr]] = Field(default=None, description="Custom headers.", alias="customHeaders")
|
||||
stream_endpoint_url: Optional[StrictStr] = Field(default=None, description="The URL ThousandEyes sends data stream to. For a URL to be valid, it needs to: - Be syntactically correct. - Be reachable. - Use the HTTPS protocol. - When using the `grpc` endpointType, streamEndpointUrl cannot contain paths: - Valid . `grpc` - `https://example.com` - Invalid . `grpc` - `https://example.com/collector`. - Valid . `http` - `https://example.com/collector`. - When using the `http` endpointType, the operation must match the exact final full URL (including the path if there is one) to which the data will be sent. Examples below: - `https://api.honeycomb.io:443/v1/metrics` - `https://ingest.eu0.signalfx.com/v2/datapoint/otlp`", alias="streamEndpointUrl")
|
||||
tag_match: Optional[List[TagMatch]] = Field(default=None, description="A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics.", alias="tagMatch")
|
||||
tag_match: Optional[List[TagMatch]] = Field(default=None, description="A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. Tags are invalid if the tag key includes characters that are not allowed by the [OpenTelemetry naming recommendations for attributes](https://opentelemetry.io/docs/specs/semconv/general/naming/#recommendations-for-application-developers).", alias="tagMatch")
|
||||
test_match: Optional[List[TestMatch]] = Field(default=None, description="A collection of tests to be included in the data stream.", alias="testMatch")
|
||||
enabled: Optional[StrictBool] = Field(default=None, description="Flag to enable or disable the stream integration.")
|
||||
filters: Optional[Filters] = None
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
@ -35,7 +35,7 @@ class Stream(BaseModel):
|
||||
""" # noqa: E501
|
||||
custom_headers: Optional[Dict[str, StrictStr]] = Field(default=None, description="Custom headers.", alias="customHeaders")
|
||||
stream_endpoint_url: Optional[StrictStr] = Field(default=None, description="The URL ThousandEyes sends data stream to. For a URL to be valid, it needs to: - Be syntactically correct. - Be reachable. - Use the HTTPS protocol. - When using the `grpc` endpointType, streamEndpointUrl cannot contain paths: - Valid . `grpc` - `https://example.com` - Invalid . `grpc` - `https://example.com/collector`. - Valid . `http` - `https://example.com/collector`. - When using the `http` endpointType, the operation must match the exact final full URL (including the path if there is one) to which the data will be sent. Examples below: - `https://api.honeycomb.io:443/v1/metrics` - `https://ingest.eu0.signalfx.com/v2/datapoint/otlp`", alias="streamEndpointUrl")
|
||||
tag_match: Optional[List[TagMatch]] = Field(default=None, description="A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics.", alias="tagMatch")
|
||||
tag_match: Optional[List[TagMatch]] = Field(default=None, description="A collection of tags that determine what tests are included in the data stream. These tag values are also included as attributes in the data stream metrics. Tags are invalid if the tag key includes characters that are not allowed by the [OpenTelemetry naming recommendations for attributes](https://opentelemetry.io/docs/specs/semconv/general/naming/#recommendations-for-application-developers).", alias="tagMatch")
|
||||
test_match: Optional[List[TestMatch]] = Field(default=None, description="A collection of tests to be included in the data stream.", alias="testMatch")
|
||||
enabled: Optional[StrictBool] = Field(default=None, description="Flag to enable or disable the stream integration.")
|
||||
filters: Optional[Filters] = None
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
@ -25,7 +25,7 @@ class TagMatch(BaseModel):
|
||||
"""
|
||||
TagMatch
|
||||
""" # noqa: E501
|
||||
key: Optional[StrictStr] = Field(default=None, description="The name of the tag key to match")
|
||||
key: Optional[StrictStr] = Field(default=None, description="The name of the tag key to match. The key is invalid if it includes characters that are not allowed by the [OpenTelemetry naming recommendations for attributes](https://opentelemetry.io/docs/specs/semconv/general/naming/#recommendations-for-application-developers).")
|
||||
value: Optional[StrictStr] = Field(default=None, description="The value of the tag to match")
|
||||
__properties: ClassVar[List[str]] = ["key", "value"]
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
"""
|
||||
ThousandEyes for OpenTelemetry API
|
||||
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [documentation](https://docs.thousandeyes.com/product-documentation/api/opentelemetry).
|
||||
ThousandEyes for OpenTelemetry provides machine-to-machine integration between ThousandEyes and its customers. It allows you to export ThousandEyes telemetry data in OTel format, which is widely used in the industry. With ThousandEyes for OTel, you can leverage frameworks widely used in the observability domain - such as Splunk, Grafana, and Honeycomb - to capture and analyze ThousandEyes data. Any client that supports OTel can use ThousandEyes for OpenTelemetry. ThousandEyes for OTel is made up of the following components: * Data streaming APIs that you can use to configure and enable your ThousandEyes tests with OTel-compatible streams, in particular to configure how ThousandEyes telemetry data is exported to client integrations. * A set of streaming pipelines called _collectors_ that actively fetch ThousandEyes network test data, enrich the data with some additional detail, filter, and push the data to the customer-configured endpoints, depending on what you configure via the public APIs. * Third-party OTel collectors that receive, transform, filter, and export different metrics to client applications such as AppD, or any other OTel-capable client configuration. For more information about ThousandEyes for OpenTelemetry, see the [product documentation](https://docs.thousandeyes.com/product-documentation/integration-guides/opentelemetry).
|
||||
|
||||
Generated by OpenAPI Generator (https://openapi-generator.tech)
|
||||
|
||||
|
||||
@ -16,7 +16,7 @@ Things to note with the ThousandEyes Tags API:
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@ Get test result metrics for Network and Application Synthetics tests.
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -4,7 +4,7 @@ This API allows you to list, create, edit, and delete Network and Application Sy
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
@ -55,7 +55,7 @@ Name | Type | Description | Notes
|
||||
**override_proxy_id** | **str** | ID of the proxy to be used if the default proxy is overridden. | [optional]
|
||||
**collect_proxy_network_data** | **bool** | Indicates whether network data to the proxy should be collected. | [optional] [default to False]
|
||||
**emulated_device_id** | **str** | ID of the emulated device, if specified when the test was created. | [optional]
|
||||
**target_time** | **int** | Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior). | [optional]
|
||||
**target_time** | **int** | Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value. | [optional] [default to 10]
|
||||
**time_limit** | **int** | Time limit for transaction in seconds. | [optional] [default to 30]
|
||||
**transaction_script** | **str** | JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ). |
|
||||
**block_domains** | **str** | Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests. | [optional]
|
||||
|
||||
@ -54,7 +54,7 @@ Name | Type | Description | Notes
|
||||
**override_proxy_id** | **str** | ID of the proxy to be used if the default proxy is overridden. | [optional]
|
||||
**collect_proxy_network_data** | **bool** | Indicates whether network data to the proxy should be collected. | [optional] [default to False]
|
||||
**emulated_device_id** | **str** | ID of the emulated device, if specified when the test was created. | [optional]
|
||||
**target_time** | **int** | Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior). | [optional]
|
||||
**target_time** | **int** | Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value. | [optional] [default to 10]
|
||||
**time_limit** | **int** | Time limit for transaction in seconds. | [optional] [default to 30]
|
||||
**transaction_script** | **str** | JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ). |
|
||||
**block_domains** | **str** | Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests. | [optional]
|
||||
|
||||
@ -41,7 +41,7 @@ Name | Type | Description | Notes
|
||||
**override_proxy_id** | **str** | ID of the proxy to be used if the default proxy is overridden. | [optional]
|
||||
**collect_proxy_network_data** | **bool** | Indicates whether network data to the proxy should be collected. | [optional] [default to False]
|
||||
**emulated_device_id** | **str** | ID of the emulated device, if specified when the test was created. | [optional]
|
||||
**target_time** | **int** | Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior). | [optional]
|
||||
**target_time** | **int** | Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value. | [optional] [default to 10]
|
||||
**time_limit** | **int** | Time limit for transaction in seconds. | [optional] [default to 30]
|
||||
**transaction_script** | **str** | JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ). |
|
||||
**block_domains** | **str** | Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests. | [optional]
|
||||
|
||||
@ -58,7 +58,7 @@ Name | Type | Description | Notes
|
||||
**override_proxy_id** | **str** | ID of the proxy to be used if the default proxy is overridden. | [optional]
|
||||
**collect_proxy_network_data** | **bool** | Indicates whether network data to the proxy should be collected. | [optional] [default to False]
|
||||
**emulated_device_id** | **str** | ID of the emulated device, if specified when the test was created. | [optional]
|
||||
**target_time** | **int** | Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior). | [optional]
|
||||
**target_time** | **int** | Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value. | [optional] [default to 10]
|
||||
**time_limit** | **int** | Time limit for transaction in seconds. | [optional] [default to 30]
|
||||
**transaction_script** | **str** | JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ). |
|
||||
**block_domains** | **str** | Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests. | [optional]
|
||||
|
||||
@ -58,7 +58,7 @@ Name | Type | Description | Notes
|
||||
**override_proxy_id** | **str** | ID of the proxy to be used if the default proxy is overridden. | [optional]
|
||||
**collect_proxy_network_data** | **bool** | Indicates whether network data to the proxy should be collected. | [optional] [default to False]
|
||||
**emulated_device_id** | **str** | ID of the emulated device, if specified when the test was created. | [optional]
|
||||
**target_time** | **int** | Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior). | [optional]
|
||||
**target_time** | **int** | Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value. | [optional] [default to 10]
|
||||
**time_limit** | **int** | Time limit for transaction in seconds. | [optional] [default to 30]
|
||||
**transaction_script** | **str** | JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ). |
|
||||
**block_domains** | **str** | Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests. | [optional]
|
||||
|
||||
@ -58,7 +58,7 @@ Name | Type | Description | Notes
|
||||
**override_proxy_id** | **str** | ID of the proxy to be used if the default proxy is overridden. | [optional]
|
||||
**collect_proxy_network_data** | **bool** | Indicates whether network data to the proxy should be collected. | [optional] [default to False]
|
||||
**emulated_device_id** | **str** | ID of the emulated device, if specified when the test was created. | [optional]
|
||||
**target_time** | **int** | Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior). | [optional]
|
||||
**target_time** | **int** | Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value. | [optional] [default to 10]
|
||||
**time_limit** | **int** | Time limit for transaction in seconds. | [optional] [default to 30]
|
||||
**transaction_script** | **str** | JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ). |
|
||||
**block_domains** | **str** | Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests. | [optional]
|
||||
|
||||
@ -89,7 +89,7 @@ class UnexpandedWebTransactionTest(BaseModel):
|
||||
override_proxy_id: Optional[StrictStr] = Field(default=None, description="ID of the proxy to be used if the default proxy is overridden.", alias="overrideProxyId")
|
||||
collect_proxy_network_data: Optional[StrictBool] = Field(default=False, description="Indicates whether network data to the proxy should be collected.", alias="collectProxyNetworkData")
|
||||
emulated_device_id: Optional[StrictStr] = Field(default=None, description="ID of the emulated device, if specified when the test was created.", alias="emulatedDeviceId")
|
||||
target_time: Optional[Annotated[int, Field(le=60, strict=True, ge=0)]] = Field(default=None, description="Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior).", alias="targetTime")
|
||||
target_time: Optional[Annotated[int, Field(le=180, strict=True, ge=0)]] = Field(default=10, description="Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value.", alias="targetTime")
|
||||
time_limit: Optional[Annotated[int, Field(le=180, strict=True, ge=5)]] = Field(default=30, description="Time limit for transaction in seconds.", alias="timeLimit")
|
||||
transaction_script: StrictStr = Field(description="JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ).", alias="transactionScript")
|
||||
block_domains: Optional[StrictStr] = Field(default=None, description="Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests.", alias="blockDomains")
|
||||
@ -237,7 +237,7 @@ class UnexpandedWebTransactionTest(BaseModel):
|
||||
"overrideProxyId": obj.get("overrideProxyId"),
|
||||
"collectProxyNetworkData": obj.get("collectProxyNetworkData") if obj.get("collectProxyNetworkData") is not None else False,
|
||||
"emulatedDeviceId": obj.get("emulatedDeviceId"),
|
||||
"targetTime": obj.get("targetTime"),
|
||||
"targetTime": obj.get("targetTime") if obj.get("targetTime") is not None else 10,
|
||||
"timeLimit": obj.get("timeLimit") if obj.get("timeLimit") is not None else 30,
|
||||
"transactionScript": obj.get("transactionScript"),
|
||||
"blockDomains": obj.get("blockDomains"),
|
||||
|
||||
@ -88,7 +88,7 @@ class WebTransactionInstantTest(BaseModel):
|
||||
override_proxy_id: Optional[StrictStr] = Field(default=None, description="ID of the proxy to be used if the default proxy is overridden.", alias="overrideProxyId")
|
||||
collect_proxy_network_data: Optional[StrictBool] = Field(default=False, description="Indicates whether network data to the proxy should be collected.", alias="collectProxyNetworkData")
|
||||
emulated_device_id: Optional[StrictStr] = Field(default=None, description="ID of the emulated device, if specified when the test was created.", alias="emulatedDeviceId")
|
||||
target_time: Optional[Annotated[int, Field(le=60, strict=True, ge=0)]] = Field(default=None, description="Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior).", alias="targetTime")
|
||||
target_time: Optional[Annotated[int, Field(le=180, strict=True, ge=0)]] = Field(default=10, description="Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value.", alias="targetTime")
|
||||
time_limit: Optional[Annotated[int, Field(le=180, strict=True, ge=5)]] = Field(default=30, description="Time limit for transaction in seconds.", alias="timeLimit")
|
||||
transaction_script: StrictStr = Field(description="JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ).", alias="transactionScript")
|
||||
block_domains: Optional[StrictStr] = Field(default=None, description="Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests.", alias="blockDomains")
|
||||
@ -251,7 +251,7 @@ class WebTransactionInstantTest(BaseModel):
|
||||
"overrideProxyId": obj.get("overrideProxyId"),
|
||||
"collectProxyNetworkData": obj.get("collectProxyNetworkData") if obj.get("collectProxyNetworkData") is not None else False,
|
||||
"emulatedDeviceId": obj.get("emulatedDeviceId"),
|
||||
"targetTime": obj.get("targetTime"),
|
||||
"targetTime": obj.get("targetTime") if obj.get("targetTime") is not None else 10,
|
||||
"timeLimit": obj.get("timeLimit") if obj.get("timeLimit") is not None else 30,
|
||||
"transactionScript": obj.get("transactionScript"),
|
||||
"blockDomains": obj.get("blockDomains"),
|
||||
|
||||
@ -71,7 +71,7 @@ class WebTransactionProperties(BaseModel):
|
||||
override_proxy_id: Optional[StrictStr] = Field(default=None, description="ID of the proxy to be used if the default proxy is overridden.", alias="overrideProxyId")
|
||||
collect_proxy_network_data: Optional[StrictBool] = Field(default=False, description="Indicates whether network data to the proxy should be collected.", alias="collectProxyNetworkData")
|
||||
emulated_device_id: Optional[StrictStr] = Field(default=None, description="ID of the emulated device, if specified when the test was created.", alias="emulatedDeviceId")
|
||||
target_time: Optional[Annotated[int, Field(le=60, strict=True, ge=0)]] = Field(default=None, description="Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior).", alias="targetTime")
|
||||
target_time: Optional[Annotated[int, Field(le=180, strict=True, ge=0)]] = Field(default=10, description="Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value.", alias="targetTime")
|
||||
time_limit: Optional[Annotated[int, Field(le=180, strict=True, ge=5)]] = Field(default=30, description="Time limit for transaction in seconds.", alias="timeLimit")
|
||||
transaction_script: StrictStr = Field(description="JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ).", alias="transactionScript")
|
||||
block_domains: Optional[StrictStr] = Field(default=None, description="Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests.", alias="blockDomains")
|
||||
@ -186,7 +186,7 @@ class WebTransactionProperties(BaseModel):
|
||||
"overrideProxyId": obj.get("overrideProxyId"),
|
||||
"collectProxyNetworkData": obj.get("collectProxyNetworkData") if obj.get("collectProxyNetworkData") is not None else False,
|
||||
"emulatedDeviceId": obj.get("emulatedDeviceId"),
|
||||
"targetTime": obj.get("targetTime"),
|
||||
"targetTime": obj.get("targetTime") if obj.get("targetTime") is not None else 10,
|
||||
"timeLimit": obj.get("timeLimit") if obj.get("timeLimit") is not None else 30,
|
||||
"transactionScript": obj.get("transactionScript"),
|
||||
"blockDomains": obj.get("blockDomains"),
|
||||
|
||||
@ -96,7 +96,7 @@ class WebTransactionTest(BaseModel):
|
||||
override_proxy_id: Optional[StrictStr] = Field(default=None, description="ID of the proxy to be used if the default proxy is overridden.", alias="overrideProxyId")
|
||||
collect_proxy_network_data: Optional[StrictBool] = Field(default=False, description="Indicates whether network data to the proxy should be collected.", alias="collectProxyNetworkData")
|
||||
emulated_device_id: Optional[StrictStr] = Field(default=None, description="ID of the emulated device, if specified when the test was created.", alias="emulatedDeviceId")
|
||||
target_time: Optional[Annotated[int, Field(le=60, strict=True, ge=0)]] = Field(default=None, description="Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior).", alias="targetTime")
|
||||
target_time: Optional[Annotated[int, Field(le=180, strict=True, ge=0)]] = Field(default=10, description="Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value.", alias="targetTime")
|
||||
time_limit: Optional[Annotated[int, Field(le=180, strict=True, ge=5)]] = Field(default=30, description="Time limit for transaction in seconds.", alias="timeLimit")
|
||||
transaction_script: StrictStr = Field(description="JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ).", alias="transactionScript")
|
||||
block_domains: Optional[StrictStr] = Field(default=None, description="Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests.", alias="blockDomains")
|
||||
@ -283,7 +283,7 @@ class WebTransactionTest(BaseModel):
|
||||
"overrideProxyId": obj.get("overrideProxyId"),
|
||||
"collectProxyNetworkData": obj.get("collectProxyNetworkData") if obj.get("collectProxyNetworkData") is not None else False,
|
||||
"emulatedDeviceId": obj.get("emulatedDeviceId"),
|
||||
"targetTime": obj.get("targetTime"),
|
||||
"targetTime": obj.get("targetTime") if obj.get("targetTime") is not None else 10,
|
||||
"timeLimit": obj.get("timeLimit") if obj.get("timeLimit") is not None else 30,
|
||||
"transactionScript": obj.get("transactionScript"),
|
||||
"blockDomains": obj.get("blockDomains"),
|
||||
|
||||
@ -93,7 +93,7 @@ class WebTransactionTestRequest(BaseModel):
|
||||
override_proxy_id: Optional[StrictStr] = Field(default=None, description="ID of the proxy to be used if the default proxy is overridden.", alias="overrideProxyId")
|
||||
collect_proxy_network_data: Optional[StrictBool] = Field(default=False, description="Indicates whether network data to the proxy should be collected.", alias="collectProxyNetworkData")
|
||||
emulated_device_id: Optional[StrictStr] = Field(default=None, description="ID of the emulated device, if specified when the test was created.", alias="emulatedDeviceId")
|
||||
target_time: Optional[Annotated[int, Field(le=60, strict=True, ge=0)]] = Field(default=None, description="Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior).", alias="targetTime")
|
||||
target_time: Optional[Annotated[int, Field(le=180, strict=True, ge=0)]] = Field(default=10, description="Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value.", alias="targetTime")
|
||||
time_limit: Optional[Annotated[int, Field(le=180, strict=True, ge=5)]] = Field(default=30, description="Time limit for transaction in seconds.", alias="timeLimit")
|
||||
transaction_script: StrictStr = Field(description="JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ).", alias="transactionScript")
|
||||
block_domains: Optional[StrictStr] = Field(default=None, description="Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests.", alias="blockDomains")
|
||||
@ -254,7 +254,7 @@ class WebTransactionTestRequest(BaseModel):
|
||||
"overrideProxyId": obj.get("overrideProxyId"),
|
||||
"collectProxyNetworkData": obj.get("collectProxyNetworkData") if obj.get("collectProxyNetworkData") is not None else False,
|
||||
"emulatedDeviceId": obj.get("emulatedDeviceId"),
|
||||
"targetTime": obj.get("targetTime"),
|
||||
"targetTime": obj.get("targetTime") if obj.get("targetTime") is not None else 10,
|
||||
"timeLimit": obj.get("timeLimit") if obj.get("timeLimit") is not None else 30,
|
||||
"transactionScript": obj.get("transactionScript"),
|
||||
"blockDomains": obj.get("blockDomains"),
|
||||
|
||||
@ -97,7 +97,7 @@ class WebTransactionTestResponse(BaseModel):
|
||||
override_proxy_id: Optional[StrictStr] = Field(default=None, description="ID of the proxy to be used if the default proxy is overridden.", alias="overrideProxyId")
|
||||
collect_proxy_network_data: Optional[StrictBool] = Field(default=False, description="Indicates whether network data to the proxy should be collected.", alias="collectProxyNetworkData")
|
||||
emulated_device_id: Optional[StrictStr] = Field(default=None, description="ID of the emulated device, if specified when the test was created.", alias="emulatedDeviceId")
|
||||
target_time: Optional[Annotated[int, Field(le=60, strict=True, ge=0)]] = Field(default=None, description="Target completion time. The default is 50% of the specified time limit in seconds. (Set to 0 to use the default behavior).", alias="targetTime")
|
||||
target_time: Optional[Annotated[int, Field(le=180, strict=True, ge=0)]] = Field(default=10, description="Target completion time, in seconds. Defaults to 10. Cannot exceed the `timeLimit` value.", alias="targetTime")
|
||||
time_limit: Optional[Annotated[int, Field(le=180, strict=True, ge=5)]] = Field(default=30, description="Time limit for transaction in seconds.", alias="timeLimit")
|
||||
transaction_script: StrictStr = Field(description="JavaScript of a web transaction test. Quotes must be escaped (precede \" characters with \\ ).", alias="transactionScript")
|
||||
block_domains: Optional[StrictStr] = Field(default=None, description="Domains or full object URLs to be excluded from metrics and waterfall data for transaction tests.", alias="blockDomains")
|
||||
@ -292,7 +292,7 @@ class WebTransactionTestResponse(BaseModel):
|
||||
"overrideProxyId": obj.get("overrideProxyId"),
|
||||
"collectProxyNetworkData": obj.get("collectProxyNetworkData") if obj.get("collectProxyNetworkData") is not None else False,
|
||||
"emulatedDeviceId": obj.get("emulatedDeviceId"),
|
||||
"targetTime": obj.get("targetTime"),
|
||||
"targetTime": obj.get("targetTime") if obj.get("targetTime") is not None else 10,
|
||||
"timeLimit": obj.get("timeLimit") if obj.get("timeLimit") is not None else 30,
|
||||
"transactionScript": obj.get("transactionScript"),
|
||||
"blockDomains": obj.get("blockDomains"),
|
||||
|
||||
@ -17,7 +17,7 @@ Refer to the Usage API operations for detailed usage instructions and optional p
|
||||
|
||||
This Python package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
|
||||
|
||||
- API version: 7.0.58
|
||||
- API version: 7.0.62
|
||||
- Generator version: 7.6.0
|
||||
- Build package: com.thousandeyes.api.codegen.ThousandeyesPythonGenerator
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user