Operations | Monitoring | ITSM | DevOps | Cloud

Debugging Microservices in Production with Distributed Tracing

Your production checkout flow just started returning 500 errors. Six microservices handle checkout. Logs show errors in three of them. Which service broke? Which error happened first? What caused the cascade? Traditional debugging doesn't work. You can't attach a debugger to production. Searching logs across six services gives thousands of lines with no obvious connection. By the time you correlate timestamps and trace IDs manually, customers have abandoned their carts.

Cloud Microservices Monitoring on AWS and Azure with OpenTelemetry

Your checkout flow starts in an AWS Lambda function, calls a payment service running on EKS, then triggers notifications through Azure Functions. Three different compute platforms, two cloud providers, one distributed trace that you can't see. Cloud providers want you to use their native monitoring tools. AWS pushes X-Ray and CloudWatch. Azure promotes Application Insights and Azure Monitor. These tools work well within their ecosystems but lock you into vendor-specific implementations.