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001-Prometheus.md

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Prometheus

What is Prometheus

Prometheus is a server-based monitoring system where typically, you run one instance per environment.

  • Cross-platform, works with Linux and Windows
  • Gather metrics exposed in your systems
  • Provides metrics on CPU, memory, disk use, etc.
  • Stores this data in a time-series database on the same server.

Time-series data

  • This means that all metrics recorded have a timestamp.
  • This makes it easier to see trends and spikes over a period of time.
  • Timestamps are added when the data is fetched.
  • This makes them easy to query using time ranges.

PromQL

  • Prometheus also has its own query language called PromQL.
  • This is because time-series data doesn't work well with standard SQL.
  • Queries can be ran using the HTTP API running in the server.

Server Configurations

  • Server configurations can be viewed through the web UI on the server.
  • The Web UI can be used for administrative tasks, like verifying reachability of the monitored systems.
  • The web UI is limited and not a comprehensive dashboard.
  • For a complete system health view, connect Grafana to Prometheus to visualize data.
  • In-built alerting system to set rules for sending emails or creating tickets when triggered.

Exporters

To monitor systems with Prometheus, you need to run an exporter on each system.

  • The exporter creates an HTTP endpoint that provides metrics.
  • Metrics are then collected and stored by the Prometheus server a regular schedule.
  • Prometheus doesn't interpret what the system or metrics represent.
  • It simply collects them in a standardized format.
  • It can monitor various systems, including:
    • Websites running on Windows
    • Batch processes on Linux
    • Servers on both Windows and Linux

For example, to monitor a Linux server, you would run a node exporter on it. This exporter provides an HTTP endpoint that returns all current metric values in the Prometheus format.

<metric name>{<label name>=<label value>, ...}

An example of a time series could be an entry with the metric name api_http_requests_total and the labels method="POST" and handler="/messages".

api_http_requests_total{method="POST", handler="/messages"}

The entire monitoring stack runs on a single, lightweight server. Additionally, many exporters, developed by the community or the Prometheus project, are available for various use cases, including:

  • Databases
  • Message queues
  • Cloud services
  • Hardware, etc.

For application-level metrics, Prometheus also supports several client libraries, including:

  • Python
  • Node.js
  • Go
  • Java
  • Microsoft .NET

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