with OpenTelemetry (OTel)
OTel auto-instrumentation in Python
we at Helios are leveraging OTel to deliver more value for developers working in distributed systems and microservices. Our approach for OTel auto-instrumentation in Python is easy to implement and maintain and doesn’t require any code changes.
The value of Helios for Python developers
Troubleshooting in Python
Root Cause Analysis Quickly pinpoint the root cause of your issues using Stack trace, error logs, and trace correlation
Replay Flows Find failed requests, generate snippets, and re-run them with the same or different parameters
Identify bottlenecks in app flows Instantly identify and analyze bottlenecks
Pinpoint Failed Tests Efficiently pinpoint the root cause of failed tests and gain insight into tests running in CI/CD
Trace-based Testing Eliminate the need to build testing infrastructure by creating trace-based tests from real traffic
Autogenerate Tests From traces to improve validation
Detailed instructions can be found in our docs.
Completely. The Helios OpenTelemetry SDK is built on top of OpenTelemetry’s Python SDK, and uses industry-standard instrumentation techniques.
No. Helios is free to use.
Our instrumentation is configured to collect all the data you may need to troubleshoot your application and to make sure that context is propagated properly across different services and provides the best way to locate issues and identify their root cause faster than ever.
We support the same versions that are supported by OpenTelemetry, Python 3.7 or later.
Helios is compliant with: