Overview
In a microservices architecture, "the API is slow" can mean five different things depending on which of eight downstream services is the actual bottleneck. Metrics and logs tell you that something's wrong; distributed tracing tells you where, request by request.
I instrument your services with OpenTelemetry and stand up Jaeger or Grafana Tempo so you can follow a single request across every service it touches.
What's Included
- Jaeger or Grafana Tempo — deployed and sized for your trace volume
- OpenTelemetry instrumentation — auto-instrumentation where available, manual spans added around your critical paths
- Service dependency mapping — a visual map of how your services actually call each other (often a surprise)
- Latency analysis dashboards — find the slowest hop in any request path without guessing
Our Process
- Architecture review — service map, existing instrumentation (if any), and where the pain points are.
- Tracing design — where OpenTelemetry auto-instrumentation is sufficient vs. where manual spans are needed.
- Implementation — tracing wired in across services, validated by tracing a handful of real requests end-to-end.
- Handover — a walkthrough of reading traces and adding instrumentation to new services.
Who This Is For
Teams running microservices where "which service is actually slow" is a recurring, time-consuming question. Most valuable once you have more than three or four services calling each other.
FAQ
Do you need to modify our application code? Some manual instrumentation is usually needed around business-critical code paths, but OpenTelemetry's auto-instrumentation covers most common frameworks and libraries without code changes.
Jaeger or Tempo — how do you decide? Tempo integrates more tightly with Grafana if you're already using it for metrics/logs. Jaeger is a solid standalone choice. I'll recommend based on your existing stack.
Does this replace metrics and logging? No — tracing complements monitoring and logging, it doesn't replace either.