This last month was very busy in implementing community ideas and feedback! Here are some of the features we rolled out 🚀
Reducing the Digma Footprint – Stage 1
While Digma can be deployed to a K8S cluster where it can handle production scale workloads, wanted to make sure that we don’t overload the local machine resources if you install Digma on your modest laptop. In the first stage of this endeavor, we’ve reduced the number of microservices from 15 to 9. Next month we’ll finish this task reducing Digma’s footprint to 4 microservices and greatly reducing the RAM and CPU consumption. Expect to hear more about this next month!
A New and Improved Dashboard
We decided to give the Digma dashboard the real estate it deserves and re-implement it as a document. The first two widgets are already there with more to be added in the coming weeks and months, providing a high-level view of your project status. The first widgets can be used to identify slow queries and specific clients with a high impact of your application performance
Don’t fail without a trace
Digma has previously captured errors and allowed navigating the call stack to understand what went wrong. Now we’ve combined this capability with tracing to allow exploring errors also in the context of the scenario in which the failing code is being used.
Understanding Digma Continuous Feedback
Digma continuous feedback is an IDE plugin for analyzing code runtime data. It enables rapid development in complex projects by linting and detecting issues as they appear, highlighting possible risks in code, and providing code change analysis and context.
Why do developers need Digma
If developers can’t see how their code performs in the real world, they can’t make informed design decisions and assess the impact of their changes.
Digma lints common code smells and issues as you code
- Error hotspots
- Bottlenecks and concurrency
- Query anti-patterns
- Performance trends
For more info check out the Digma main repo