azure-monitor-ingestion-pylisted
Install: claude install-skill aiskillstore/marketplace
# 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