azure-monitor-ingestion

What it is and what it does

Azure Monitor Ingestion is a Python client library for sending custom logs to Azure Monitor's Log Analytics workspace via the Logs Ingestion API. It provides both synchronous and asynchronous interfaces for uploading structured data from any source to custom tables or supported built-in tables (CommonSecurityLog, SecurityEvents, Syslog, WindowsEvents). The library handles authentication via Azure credentials and supports schema extension for built-in tables.

The package is built on azure-core and integrates with the broader Azure SDK ecosystem. It requires pre-configured Azure infrastructure—a Data Collection Endpoint, Data Collection Rule, and target Log Analytics workspace—before logs can be uploaded. The library includes error handling for HTTP failures and supports transformation rules defined in your Data Collection Rule to reshape incoming data.

Use it for:

• Ingest security logs (CommonSecurityLog, SecurityEvents) from third-party sources into Azure Monitor for centralized analysis.
• Stream application or system logs from Python services directly to a custom Log Analytics table for monitoring and alerting.
• Upload syslog or Windows event data from remote systems to Azure Monitor using a Python collector agent.
• Send structured telemetry or audit logs from a Python application to Azure Monitor for compliance and diagnostics.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Sends custom logs and structured data to Azure Monitor's Log Analytics workspace using the Logs Ingestion API, supporting both synchronous and asynchronous clients.

Yes. The package is production-stable (Development Status 5), actively maintained, has no known vulnerabilities, and low install friction. Install it if you need to send logs from Python to Azure Monitor and have the required Azure infrastructure (Log Analytics workspace, Data Collection Endpoint, Data Collection Rule) already in place. Not suitable if you lack an Azure subscription or prefer a non-cloud logging solution.

Install

azure-monitor-ingestion on PyPI

pip install azure-monitor-ingestion

uv add azure-monitor-ingestion

poetry add azure-monitor-ingestion

Installing azure-monitor-ingestion

Before you install

Low install friction with a pure-Python wheel. Actively maintained as of 2026-08-14 with recent releases. Depends on azure-core, isodate, and typing-extensions—all standard Azure SDK dependencies.

License in practice

MIT License permits commercial and private use with minimal restrictions; you must include a copy of the license and copyright notice.

Quickstart

pip install azure-monitor-ingestion

from azure.identity import DefaultAzureCredential
from azure.monitor.ingestion import LogsIngestionClient

endpoint = "<DATA_COLLECTION_ENDPOINT>"
credential = DefaultAzureCredential()
client = LogsIngestionClient(endpoint, credential)
client.upload(rule_id="<RULE_ID>", stream_name="<STREAM_NAME>", logs=[{"Time": "2021-12-08T23:51:14.1104269Z", "Computer": "Computer1"}])

Requires Python 3.9 or later; requires Azure subscription, Log Analytics workspace, Data Collection Endpoint, and Data Collection Rule already configured in Azure.

Verify before relying

• Whether the package supports batch uploads or has limits on log payload size.
• Performance characteristics when uploading large volumes of logs.
• Retry and backoff behavior for transient failures.

Package facts

Evidence: azure_monitor_ingestion-1.1.0-py3-none-any.whl

Keywords: azure, azure sdk

Tags

More Monitoring packages