We set up these examples to help you try out Pyroscope. You'll need docker + docker-compose to run them:
cd python
docker-compose up --buildThese are very simple projects where the application is basically one while true loop and inside that loop it calls a slow function and a fast function. Slow function takes about 75% of the time and the fast one takes about 25%. See debug_python_with_pyroscope.md for a full example of how improving one function can decrease overall CPU utilization and ultimately save cut server costs by 66%!
Pyroscope identifies performance issues in your application by continuously profiling the code.
If you've never used a profiler before, then welcome!
If you are familiar with profiling and flame graphs, then you'll be happy to know that Pyroscope:
- Requires very minimal overhead
- Can store years of perf data down to 10 second granularity
- Uses a unique, inverted flame graph for increased readability
There are two main components that allow Pyroscope to run smoothly and quickly:
Every .01 seconds, the Pyroscope agent wraps around your Python, Ruby, or Go application to poll the stacktrace and calculate which function is consuming your CPU resources.
Pyroscope records and aggregates what your application has been doing, then sends that data to the Pyroscope server over port :4040(BadgerDB) to be processed, aggregated, and stored for speedy queries of any time range, including:
- all of 2020
- that one day last month when that weird thing happened
- that time you deployed on a Friday and messed up everything without knowing why
- A random 10 seconds you are only querying to see if Pyroscope is legit
Check out our Demo Page and select any time range to see how quickly Pyroscope works!
