
Open-source monitoring and alerting toolkit for cloud-native environments
Prometheus is a powerful open-source monitoring system and time series database originally built at SoundCloud. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays results, and triggers alerts when specified conditions are met. Widely adopted as a Cloud Native Computing Foundation (CNCF) graduated project, it has become the de facto standard for monitoring Kubernetes and cloud-native infrastructure.
Powerful query language for querying, correlating, and transforming time series data for visualizations, alerts, and analytics
Stores time series data identified by metric name and key/value pairs for flexible, dimensional data analysis
Define alerting rules based on PromQL with a dedicated Alertmanager component for routing, silencing, and grouping notifications
Automatically discovers and monitors services through Kubernetes, Consul, DNS, and other service discovery mechanisms
Scrapes metrics from instrumented targets over HTTP, providing better control over collection intervals and reliability
Hundreds of official and community-contributed exporters to collect metrics from databases, hardware, messaging systems, and more
Seamless integration with Grafana for building rich, customizable dashboards and data visualizations
Monitor container orchestration, pod health, resource usage, and service availability across Kubernetes clusters
Set up real-time alerts for server health, CPU, memory, disk usage, and network metrics with customizable thresholds
Track request rates, error rates, and latencies across distributed microservice architectures
Monitor cloud-native applications with automatic service discovery and dynamic target management
The industry-standard metrics engine for cloud-native environments, best paired with Grafana for visualization and VictoriaMetrics or Thanos for long-term storage
Best for Kubernetes and cloud-native infrastructure monitoring. Pair with VictoriaMetrics or Thanos for long-term storage to build a complete, production-grade monitoring stack.
Includes a basic web UI for ad-hoc querying, graphing, and exploring collected metrics data
Analyze historical metrics trends to forecast resource needs and plan infrastructure scaling

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