/azure-monitor-ingestion-py

azure-monitor-ingestion-py non-hero scenarios

These scenarios are intentionally separate from hero flows in SKILL.md. They cover secondary/advanced patterns typically used after the primary end-to-end path is working.

Async Client

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

async def upload_logs():
    async with DefaultAzureCredential() as credential:
        async with LogsIngestionClient(
            endpoint=endpoint,
            credential=credential
        ) as client:
            await client.upload(
                rule_id=rule_id,
                stream_name=stream_name,
                logs=logs
            )

asyncio.run(upload_logs())

Sovereign Clouds

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

# Azure Government
credential = DefaultAzureCredential(authority=AzureAuthorityHosts.AZURE_GOVERNMENT)
with LogsIngestionClient(
    endpoint="https://example.ingest.monitor.azure.us",
    credential=credential,
    credential_scopes=["https://monitor.azure.us/.default"]
) as client:
    # client.upload(...)
    ...

Batching Behavior

The SDK automatically:

• Splits logs into chunks of 1MB or less
• Compresses each chunk with gzip
• Uploads chunks in parallel

No manual batching needed for large log sets.

Client Types

Key Concepts

DCR Stream Name Format

Stream names follow patterns:

• Custom-<TableName>_CL — For custom tables
• Microsoft-<TableName> — For built-in tables