How to automate version aware distributed trace analysis
Distributed Traces serve as a “source of truth” for developers and architects. They record the entire chain of events for each unique request processed by your apps and services. Distributed Traces is the “source of truth for programmers and architects.”
Engineers can use IDE (Integrated Development Environment) and test tool connections. It remains a big platform to do distributed trace analysis on the distributed traces they just generated while running unit or API tests in a local dev environment. The outgoing call, including request and response data, will be visible in the distributed trace. It makes it easier to answer queries like “Does my code appropriately call the latest backend service version for my specific use case?”
From a handful to millions of distributed traces requires automation
When you capture distributed traces in shared testing or production environments with hundreds of services/microservices deployed in one or more versions, you could quickly wind up with millions of collected fractions. If you can automate the study of those traces, you can enable DevOps and SRE teams. They will be able to answer queries like:
- “Which versions of our services are handling our essential transactions right now?”
- “How does an overburdened backend service affect the frontend service’s SLOs?”
- “Which frontend services are to blame for the backend services’ changing traffic behavior?”
- “Do two different versions of a service behave differently?” If that’s the case, should we halt the production rollout?”
These are questions I’m hearing more and more these days, which is a little concerning. You need to record version information on every distributed trace to address version-specific questions like the one above. Still, it would help if you also automated the analysis because no one can manually sift through millions of trails and come up with answers that lead to better delivery and release decisions.
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