Slide 11 of 13

Prometheus

Prometheus: The cloud-native metrics standard

What it’s for: Time-series metrics including CPU, memory, request rates, error counts, and latency.

Trade-offs

ProsCons
Industry standard for K8sPromQL learning curve
Huge ecosystem of exportersLocal storage limitations
Pull-based (secure)Single-node scalability
Native Grafana integrationRequires Prometheus-compatible backend

Best for

  • Kubernetes environments
  • Microservices architectures
  • Cloud-native applications

Learning path

Connect your Prometheus data source step by step.

Prometheus data source

Script

Let’s start with Prometheus, the industry standard for cloud-native metrics. If you’re running Kubernetes, microservices, or anything modern, chances are Prometheus is involved somewhere.

Prometheus is an open-source monitoring and alerting toolkit. It includes a time-series database for storing metrics, a pull-based collection model that scrapes targets at regular intervals, PromQL for querying data, and built-in alerting. The ecosystem is massive. Thousands of exporters exist for everything from Linux systems to databases to message queues.

And Grafana treats Prometheus as a first-class citizen with native integration, optimized performance, and deep feature support. If you’re doing cloud-native observability, Prometheus is probably where you start.

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