How to write about it — Logs, metrics and traces: why is your application slow?
Structure, tips and best practices for writing about this topic
Explore this guide : Definition Benefits Complete guide Use cases For businesses Statistics & data Comparison Cost & budget Training & learning Trends Common mistakes Alternatives Read the full guide
Three complementary signals help move from noticing a problem to understanding where it happens.
Recommended structure
- IntroductionThree complementary signals help move from noticing a problem to understanding where it happens.
- Metrics show patternsMetrics summarize request volume, error rates and response duration over time. Averages can hide slow requests, so inspect latency percentiles. Alert on sustained user impact rather than every brief increase in CPU usage.
- Logs explain eventsStructured logs record request IDs, actions and error types. They help find events around failures. Avoid passwords, tokens and full customer documents. Set retention and access rules because operational data can still contain personal information.
- Traces connect the journeyA trace follows a request through the API, database and external calls. Its spans reveal which step took time. OpenTelemetry provides instrumentation and export mechanisms; you still need a backend to store and explore signals.
- ConclusionMetrics reveal patterns, logs explain events and traces connect request steps.
Angles to cover
Writing tips
- Start with a concrete problem your reader is facing
- Use real examples — abstract explanations lose readers quickly
- Break long paragraphs into scannable sections with clear headings
- End every section with an actionable insight, not just information
The essential point : Metrics reveal patterns, logs explain events and traces connect request steps.
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