How storage works in Prometheus, and why is this important?

Learn the bases that make Prometheus, so a great solution to monitor your workloads and use it for your own benefit.

Prometheus is one of the key systems in nowadays cloud architectures. The second graduated project from the Cloud Native Computing Foundation (CNCF) after Kubernetes itself, and it is the monitoring solution for excellence in most of the workloads running on Kubernetes.

If you already have used Prometheus some time, you know that it relies on a Time series database, and it is one of the key elements. Based on their own words from the Prometheus official page:

Every time series is uniquely identified by its metric name and optional key-value pairs called labels, and that series is similar to the tables in a relational model. And inside each of those series, we have the samples that are similar to the tuples. And each of the samples contains a float value and a milliseconds-precision timestamp.

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How storage works in Prometheus, and why is this important?