Collecting metrics is essential for monitoring the behavior and performance of your applications, closing the feedback loop with development, and for alerting you if things go wrong during operation. But for metrics to be effective, they have to be accurate. We show how to develop useful and balanced metrics, how to collect accurate metrics, and how to avoid pitfalls especially when storing metrics long-term in time-series databases by considering the effects of retention policies and sampling rates.
Marcus Crestani is an experienced software architect and works at Active Group GmbH. His interests lie in functional programming, software architecture, and programming languages. Currently, he is working on developing and running large, stream-based event systems with long-time storage and time-series databases.