Python Log Management Made Easy
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Aggregate logs from any Python application
Consolidate your Python logs into one location – including logs from Django and Flask servers -
Search and tail logs instantly
Quickly search through hours of Python logging data and see a real-time live feed of log events -
Accelerate troubleshooting with log analytics
Troubleshoot a spike in event messages or identify trends over time with a comprehensive Python log analysis tool
Here's How Papertrail Helps
Aggregate logs from Python applications
Consolidate logs from all your Python applications, including logs from Django servers. Debug application errors, diagnose operational issues, detect anomalies, and trace problems. Visualize the event message flow with the Papertrail Event Viewer to quickly spot trends and patterns. Easily integrate Python log management with third party services including Slack, PagerDuty, and Redshift for instant alerts.
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Search and tail logs instantly
Quickly search through hours of Python logs and see a real-time live feed of log events. Intuitive, and powerful log tailing, allows you to pause, search, scroll, and click on log elements such as IP address, UUIDs, user IDs and more to accelerate troubleshooting. Quickly search across existing Python logs as new logs appear in real time, which is great for trying to reproduce and perform root cause analysis on Python related issues. Save searches and create alerts without leaving the event viewer to streamline future debugging.
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Log velocity analytics
Catch issues before they go critical by visually monitoring log volume to quickly spot an uptick in error message count or change in trends. Use log velocity analytics for Python logs to visualize the error flow at a particular point in time. Click on a point in the graph and instantly jump to those events to streamline troubleshooting.
Sign up for a free plan- Python Logging
- Simplify Python log management and troubleshooting by aggregating Python logs from any source, and the ability to tail and search in real time.