azure-monitor-ingestion-py

# 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) AZURE_DCE_ENDPOINT=https://<dce-name>.<region>.ingest.monitor.azure.com # Data Collection Rule (DCR) immutable ID AZURE_DCR_RULE_ID=dcr-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx # Stream name from DCR AZURE_DCR_STREAM_NAME=Custom-MyTable_CL ``` ## 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 ```python from azure.monitor.ingestion import LogsIngestionClient from azure.identity import DefaultAzureCredential import os client = LogsIngestionClient( endpoint=os.environ["AZURE_DCE_ENDPOINT"], credential=DefaultAzureCredential() ) ``` ## Upload Custom Logs ```python from azure.monitor.ingestion import LogsIngestionClient from azure.identity import DefaultAzureCredential import os client = LogsIngestionClient( endpoint=os.environ["AZURE_DCE_ENDPOINT"], credential=DefaultAzureCredential() ) rule_id = os.environ["AZURE_DCR_RULE_ID"] stream_name = os.environ["AZURE_DCR_STREAM_NAME"] logs = [ {"TimeGenerated": "202...