Your Telemetry Pipeline May Be Leaking More Than Errors
Observability data can become a security problem when it records more than engineers intended. Logs, traces, and metric attributes often cross application, network, storage, […]
Category: Observability
Tail Sampling Can Save the Right Traces—or Quietly Lose Them
Keeping fewer traces can improve observability—if the traces you keep are the ones that explain failure. Many teams begin with simple probabilistic sampling: retain […]
Your Trace Broke at the Queue: Use Span Links for Asynchronous Work
A trace that looks complete at the API boundary can still lose the most important part of the work. The request returns, a message […]
Cardinality Is a Reliability Risk: Build a Metric Budget Before It Builds Your Bill
High-cardinality metrics can raise costs and quietly weaken dashboards and SLOs. Build a practical metric budget that protects both infrastructure and operational meaning.
Your Payment API Is Up. Did the User Complete the Journey?
A healthy payment API does not prove that users completed their journey. Learn how to define user-centered SLIs, instrument meaningful transitions, and connect payment reliability to operating decisions.
Will Your Telemetry Survive an Outage? Test Your OpenTelemetry Collector
A larger queue is not a delivery guarantee. Learn how to size an OpenTelemetry Collector outage window, validate persistent storage, and test recovery without risking production telemetry.
OpenTelemetry Profiles Are Alpha: A Practical Adoption Guide for African Engineering Teams
OpenTelemetry Profiles entered public alpha in 2026. Here is a disciplined five-step plan for African engineering teams to evaluate continuous profiling without turning an emerging signal into a new production risk.
Building Observability When Bandwidth Is Unreliable
How engineering teams can keep operational visibility when bandwidth is expensive, unstable, or simply unavailable when it matters most.
Lean Monitoring Stacks for Small Engineering Teams in Africa
A practical approach to monitoring for lean teams that need strong operational outcomes without enterprise-scale tooling overhead.
Choosing the Right Signals When Storage and Compute Are Expensive
Observability becomes more sustainable when teams focus on the signals that explain user impact instead of storing everything by default.