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azure-monitor-ingestion-py Skill

AI Agent SkillCloud & DevOpsTypeScriptOpen source

Azure Monitor Ingestion SDK for Python. Use for sending custom logs to Log Analytics workspace via Logs Ingestion API. Triggers: "azure-monitor-ingestion", "LogsIngestionClient", "custom logs", "DCR", "data collection rule", "Log Analytics". Published by microsoft in skills.

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Best for

Data analysis, Includes SKILL.md, Reusable instructions

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Setup

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Project health

2 months ago · MIT license

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What is azure-monitor-ingestion-py Skill?

Azure Monitor Ingestion SDK for Python. Use for sending custom logs to Log Analytics workspace via Logs Ingestion API. Triggers: "azure-monitor-ingestion", "LogsIngestionClient", "custom logs", "DCR", "data collection rule", "Log Analytics". Published by microsoft in skills. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
85/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Data analysis
  • Data analysis use cases

Declared skill metadata

  • Declared author: Microsoft
  • Declared license: MIT
  • Source file: .github/plugins/azure-sdk-python/skills/azure-monitor-ingestion-py/SKILL.md

These fields retain source and confidence evidence from the indexed SKILL.md.

Compatibility and setup

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  • Install or run with Copy skill directory

When to use azure-monitor-ingestion-py Skill

  • Use it for data analysis.

Built with

TypeScriptCopy skill directory

Editorial notes

Source

  • Creator: microsoft
  • Repository: microsoft/skills
  • Skill file: .github/plugins/azure-sdk-python/skills/azure-monitor-ingestion-py/SKILL.md

What it does

Azure Monitor Ingestion SDK for Python. Use for sending custom logs to Log Analytics workspace via Logs Ingestion API. Triggers: "azure-monitor-ingestion", "LogsIngestionClient", "custom logs", "DCR", "data collection rule", "Log Analytics".

Skill instructions

Azure Monitor Ingestion SDK for Python Send custom logs to Azure Monitor Log Analytics workspace using the Logs Ingestion API. Installation bash pip install azure-monitor-ingestion pip install azure-identity Environment Variables bash Data Collection Endpoint (DCE) AZUREDCEENDPOINT=https://<dce-name.<region.ingest.monitor.azure.com Required for all auth methods Data Collection Rule (DCR) immutable ID AZUREDCRRULEID=dcr-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Required for all auth methods Stream name from DCR AZUREDCRSTREAMNAME=Custom-MyTableCL Required for all auth methods AZURETOKENCREDENTIALS=prod Required only if DefaultAzureCredential is used in production Prerequisites Before using this SDK, you need: 1. Log Analytics Workspace — Target for your logs 2. Data Collection Endpoint (DCE) — Ingestion endpoint 3. Data Collection Rule (DCR) — Defines schema and destination 4. Custom Table — In Log Analytics (created via DCR or manually) Authentication & Lifecycle 🔑 Two rules apply to every cod

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Frequently asked questions

What is azure-monitor-ingestion-py?

azure-monitor-ingestion-py is a open-source AI agent skill with Copy skill directory. Azure Monitor Ingestion SDK for Python. Use for sending custom logs to Log Analytics workspace via Logs Ingestion API.

Who is azure-monitor-ingestion-py best for?

azure-monitor-ingestion-py is best for reusing agent instructions, scripts, and references, data analysis workflows.

How do I install azure-monitor-ingestion-py?

Install or run azure-monitor-ingestion-py using Copy skill directory. Check azure-monitor-ingestion-py for the latest setup command.

Is azure-monitor-ingestion-py actively maintained?

azure-monitor-ingestion-py may need a closer maintenance check before production use.

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309
Last commit
2 months ago
Last verified
Aug 26, 2026
Metadata fetched
Aug 26, 2026
Repository age
8 months
License
MIT

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