Logs in context for the Python agent connects your logs and APM data in New Relic. Bringing all of this data together in a single tool helps you quickly get to the root cause of an issue and find the log lines that you need to identify and resolve a problem.
Set up your Python app
To enable logs in context for APM apps monitored by Python, you can use our manual installation option.
- Make sure you have already set up logging in New Relic. This includes configuring a supported log forwarder that collects your application logs and extends the metadata that is forwarded to New Relic.
- Install or update to the latest Python agent version, and enable distributed tracing. Use Python agent version 5.4.0 or higher for logs in context.
- Configure logs in context for your log handler.
- To verify that you have configured the log appender correctly, run your application, then check your logs data in New Relic using the query operator
has:span.id has:trace.id
.
If everything is configured correctly and your data is being forwarded to New Relic with the enriched metadata, your logs should now be emitted as JSON and contain trace.id
and span.id
fields. If you don't see log data in the UI, follow the troubleshooting procedures.
What's next?
After you set up APM logs in context, make the most of your logging data:
- Explore the logging data across your platform with our Logs UI.
- See your logs in context of your app's performance in the APM UI. Troubleshoot errors with distributed tracing, stack traces, application logs, and more.
- Get deeper visibility into both your application and your platform performance data by forwarding your logs with our infrastructure monitoring agent. Review your infrastructure logs in the UI.
- Set up alerts.
- Query your data and create dashboards.