What gets measured gets managed, and with the vast array of monitoring systems used today, collecting and alerting on traditional infrastructure metrics is a relatively straightforward task. However, measuring only system metrics or metrics emitted by third-party services won’t paint the whole picture of application health.
Custom metrics tend to be underutilized because of the need to modify application code to emit metrics, the higher volumes of data that custom metrics generate, and the challenge of keeping instrumentation consistent across teams as new services are added or old ones changed. But instrumentation friction isn’t as high as it seems; instrumenting custom metrics is critical to correctly monitoring services, as well as for debugging, experimentation, and business observability.
Maxime Petazzoni explains why monitoring custom application metrics is essential for visibility into the internal workings of a system and shares a framework for properly instrumenting them while writing application code, along with a number of relevant use cases.
Maxime Petazzoni is a technical lead and engineering manager at SignalFx. He is the architect behind SignalFx’s Microservices APM offering, and spent several years working on the core of SignalFx: its real-time, streaming SignalFlow™ Analytics. He is also the creator of MaestroNG, a container orchestrator for Docker environments.
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