Testing
Custom OpenTelemetry instrumentation is code like any other code — it can be wrong, and wrong instrumentation is worse than no instrumentation. If your span names are wrong, your dashboards show garbage. If context propagation is broken, your distributed traces have gaps. If attributes are missing, your SLOs can't
Testing Strategy
When a test fails in a distributed system, the error message tells you what failed — not where, why, or which of the twelve services involved was responsible. Distributed tracing in your test suite gives you the full execution path for every test run, turning hours of log-digging into a
Testing
When a test fails in a distributed system, the error message tells you what happened but not where. A 500 response from your API gateway might be caused by a timeout in service C, waiting on a database query in service B, initiated by a bad request from service A.
Chaos Engineering
Chaos engineering is not about breaking systems randomly. It's about running controlled experiments to validate hypotheses about system behavior under failure conditions. Without observability, you can't form those hypotheses, can't detect the blast radius of an experiment, and can't determine whether your
Testing
Testing observability in microservices is the discipline that nobody implements until an incident exposes the gap. You're in the middle of a production outage, you open Grafana, and the dashboard is empty. Or the traces are there but missing the tenant_id attribute that would tell you which
Testing
Bad alerting is worse than no alerting. A monitoring setup that pages you at 3am for a 2-second blip that self-resolved trains your team to ignore alerts. And teams that ignore alerts miss the real outages. Getting synthetic monitoring alerting right is mostly about restraint: being precise about
Testing
Synthetic monitoring is one of those terms that sounds more complicated than it is. At its core, it means running scripted tests against your application on a schedule — simulating what a real user would do — and alerting you when something breaks. No real users required. If you've ever
Testing
Picking a synthetic monitoring tool is a decision most teams make once and live with for years. The difference between the right tool and the wrong one is often less about features and more about fit: what kind of engineers use it, what else it integrates with, and what it
Testing
Synthetic monitoring and real user monitoring (RUM) both answer the question "is my application working?" — but they answer it differently, from different angles, with different tradeoffs. Most teams need both. The question is understanding what each one tells you. What Each One Is Synthetic monitoring runs scripted tests
Testing
Playwright is one of the best tools for synthetic monitoring of web applications. It's fast, it supports all major browsers, it handles modern JavaScript applications well, and its API is intuitive enough that you can write a useful monitor in 20 minutes. This guide covers how to structure
Testing
API synthetic monitoring is the most cost-effective monitoring you can do. No browser, no JavaScript, no rendering — just send an HTTP request and validate the response. A well-configured API monitor can run every 30 seconds for minimal cost and catch outages within a minute. This guide covers the
Testing
Unit tests verify logic in isolation. End-to-end tests verify user-visible behavior. Neither tells you whether your distributed system's observability is correct — whether the traces you're emitting are complete, correctly named, and carrying the right attributes. Asserting on OpenTelemetry spans in integration tests fills