Resolve Python issues faster with distributed tracing, centralized logging, and high-granularity metrics all within 1 platform.
Product Benefits
Simplify Complexity with End-to-End Visibility
Monitor all aspects of your application architecture from the user interaction to back-end storage - in a single platform
Easily identify bottlenecks, errors, heavy traffic issues, slow-running queries, and more with end-to-end application tracing, latency breakdowns, stack traces, and flame graphs highlighting errored requests
Automatically collect, monitor, and visualize high-granularity data and custom metrics in real time, including availability, response times, reliability, error rates, and throughput
Troubleshoot Python App Performance Issues Faster
Identify critical issues quickly with real-time service maps, AI-powered synthetic monitors, and alerts on latency, exceptions, code-level errors, log issues, and more
Resolve detected Python problems faster with distributed request traces, logs, and infrastructure metrics all within one platform
Test hypotheses in seconds by overlaying application events onto time-synchronized metric graphs
Efficiently Investigate and Manage Your Python Logs
Easily manage your logs with an intuitive, centralized logging platform
Discover log patterns and errors rapidly without the need to investigate and read every individual log file
Analyze all your logs without the need to learn or use a query language
Correlate request logs with traces automatically and easily isolate all your logs from a single request
Receive Alerts Only for the Issues That Matter & Eliminate False-Positives
Set up alerts for anomalies and outliers that account for daily, weekly, and seasonal fluctuations
Proactively prevent outages and errors by alerting on metric forecasts
Create composite alerts, based on Boolean logic, to reduce your time spent responding to spurious alerts
Automatically detect unanticipated outliers, anomalies, and errors with Watchdog
Spend Less Time Scaling and Maintaining Your Tools
Save time scaling and maintaining your open source tools as complexity grows within your stack
Automatically instrument your applications for popular Python frameworks such as Django, Pyramid, Flask, and Tornado
Efficiently analyze issues from any perspective with automated tagging integrated throughout the entire platform
