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102 lines
6.2 KiB
Python
102 lines
6.2 KiB
Python
# coding: utf-8
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"""
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Cloud Insights Integrations API
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**Note:** All Cloud Insights APIs are not available for ThousandEyes for Government instance. The Cloud Insights Integrations API lets you programmatically manage **AWS** and **Azure** monitoring integrations in ThousandEyes. ### What You Can Do - **List** all integrations. - **Get** details for a specific integration. - **Delete** an existing integration. - **Create** integrations for: - **AWS**: inventory monitoring and flow logs monitoring. - **Azure**: inventory monitoring and flow logs monitoring. - **Update** integrations for: - **Azure**: inventory monitoring and flow logs monitoring. - **Fetch AWS IAM policy documents** required to configure AWS inventory and flow-logs integrations. - **Retrieve** the current AWS and Azure integration policy settings to understand which AWS and Azure resource groups, AWS regions, Azure subscription rules are enabled and whether CloudTrail is enabled for Cloud Insights for inventory monitoring. - **Update** policy settings to change the approved AWS resource groups, AWS regions, and Azure subscription rules that ThousandEyes should inventory. ### Scope and Tenancy All operations are scoped to the authenticated account group. Responses include only resources associated with that group. ### Payloads and formats - **Requests:** `application/json` - **Responses:** primarily `application/hal+json` for resource representations and `application/json` for policy documents. - HAL responses include `_links` with a `self` relation for direct navigation. ### Integration Types - **Inventory monitoring** - AWS: reads inventory and network topology via read-only IAM permissions. - Azure: authenticates with a Service Principal to read inventory and network topology. - **Flow logs monitoring** - AWS: reads flow logs from S3 buckets and uses SNS for notifications. - Azure: reads flow logs via **Service Bus Queue** (`serviceBusQueueUrl`). ### Policy Helpers (AWS) Dedicated endpoints return **Trusted Policy**, **Permissions Policy**, and **SNS Topic Access Policy** documents to simplify role setup for inventory and flow logs integrations. ### Notes - All example values in this specification are **fictitious**. For more information about Cloud Insights, see [Cloud Insights](https://docs.thousandeyes.com/product-documentation/cloud-insights).
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Generated by OpenAPI Generator (https://openapi-generator.tech)
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Do not edit the class manually.
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""" # 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, Field, StrictBool, 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 Link(BaseModel):
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"""
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A hyperlink from the containing resource to a URI.
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""" # noqa: E501
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href: StrictStr = Field(description="Its value is either a URI [RFC3986] or a URI template [RFC6570].")
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templated: Optional[StrictBool] = Field(default=None, description="Should be true when the link object's \"href\" property is a URI template.")
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type: Optional[StrictStr] = Field(default=None, description="Used as a hint to indicate the media type expected when dereferencing the target resource.")
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deprecation: Optional[StrictStr] = Field(default=None, description="Its presence indicates that the link is to be deprecated at a future date. Its value is a URL that should provide further information about the deprecation.")
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name: Optional[StrictStr] = Field(default=None, description="Its value may be used as a secondary key for selecting link objects that share the same relation type.")
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profile: Optional[StrictStr] = Field(default=None, description="A URI that hints about the profile of the target resource.")
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title: Optional[StrictStr] = Field(default=None, description="Intended for labelling the link with a human-readable identifier")
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hreflang: Optional[StrictStr] = Field(default=None, description="Indicates the language of the target resource")
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__properties: ClassVar[List[str]] = ["href", "templated", "type", "deprecation", "name", "profile", "title", "hreflang"]
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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 Link 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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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 Link 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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"href": obj.get("href"),
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"templated": obj.get("templated"),
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"type": obj.get("type"),
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"deprecation": obj.get("deprecation"),
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"name": obj.get("name"),
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"profile": obj.get("profile"),
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"title": obj.get("title"),
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"hreflang": obj.get("hreflang")
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})
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return _obj
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