New Release: Traffic Viewer for API Visibility in Kubernetes Clusters
We are excited to announce a new global release of our software with unique API visibility features to help organizations discover problems with their cloud services well before they impact customers in production.
According to Peter Kreslins, CTO of Digibee:
“We are leveraging the capabilities of the new Traffic Viewer when building new APIs, as well as in debugging system issues quickly. We examine the actual values in API calls, exposing potential schema and configuration issues. Not only that, we use the new filter capabilities to build tests and mocks of just the APIs we need. Now Digibee generates Speedscale quality automation even faster.”
The Traffic Viewer feature adds real-time observability into the elastically scaling Speedscale Traffic Replay application, providing an API-oriented view where developers can easily understand how apps call each other, what data is being sent and what technologies are used. Once an API is instrumented with Speedscale’s listener, the Traffic Viewer handles the rest.
For those interested in learning more, join Speedscale during a webinar on August 24 at 4:00pm EST. Sign up here.
From Ken Ahrens, CEO and Founder of Speedscale:
“We are proud to share our Traffic Viewer with engineering teams to help increase Kubernetes API visibility for our clients. With big advancements in open telemetry and distributed architectures, our goal was to expose all the information developers need to better test the next version of code. The upgrade was driven by customer feedback and our focus on continuous improvement.”
Traffic Viewer Features include:
- Dashboard with ability to drill down to individual transactions including message payload, headers, cookies, authentication tokens, etc.
- Powerful filters to analyze specific subsets of traffic.
- Decrypt TLS traffic on the fly to see details of calls to https endpoints.
- Auto detection of downstream API dependencies, both internal and third-party.
- Replay selected traffic as performance and regression tests.