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Prometheus

Open-source monitoring and alerting toolkit for cloud-native systems and services.

Quick Info

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Overview

Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud. Since its inception in 2012, it has evolved into a standalone open-source project and joined the Cloud Native Computing Foundation (CNCF) as the second graduated project after Kubernetes. It collects and stores its metrics as time series data, i.e., metrics information is stored with the timestamp at which it was recorded, alongside optional key-value pairs called labels.

The core value proposition of Prometheus lies in its powerful multi-dimensional data model, flexible query language (PromQL), and efficient alerting capabilities. It's particularly well-suited for dynamic cloud environments, offering service discovery mechanisms to automatically find and monitor new targets. While it excels at collecting and querying metrics, it's often complemented by other tools like Grafana for dashboarding and long-term storage solutions for historical data.

Best For

Monitoring microservices architectures
Observability for Kubernetes clusters
Real-time performance monitoring of applications
Infrastructure monitoring (servers, networks, databases)
Setting up custom alerts for system anomalies
Collecting and analyzing custom application metrics

Key Features

Dimensional data model for time series
PromQL: a powerful query language for time series data
Precise alerting based on PromQL
Alertmanager for handling notifications and silencing
Simple operation with independent servers and local storage
Extensive instrumentation libraries for various languages
Ubiquitous integrations and exporters for existing systems
Service discovery for dynamic cloud environments
Statically linked binaries for easy deployment

Pros & Cons

Pros

  • Highly flexible and powerful data model for metrics
  • PromQL offers advanced querying and aggregation capabilities
  • Excellent for cloud-native and Kubernetes environments
  • Large and active open-source community support
  • Easy to deploy and operate due to standalone architecture
  • Rich ecosystem of exporters and client libraries for diverse integrations
  • Graduated CNCF project, indicating maturity and reliability

Cons

  • Not designed for long-term data storage; requires integration with other solutions for historical data
  • Can be complex to set up and configure for beginners
  • Scalability can be challenging for very large, distributed environments without careful planning
  • Requires a separate Alertmanager component for notification management
  • Limited built-in dashboarding capabilities, often paired with Grafana
  • Not ideal for event logging or tracing, primarily focused on metrics

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