A highly available Prometheus setup with long-term storage capabilities, enabling global query views and unlimited metric retention.
Thanos is an open-source, highly available metric system that extends Prometheus with long-term storage capabilities and a global query view. It solves the problem of limited retention and scalability in Prometheus by allowing historical metrics to be stored cost-efficiently in object storage while maintaining fast query performance. It seamlessly integrates with existing Prometheus setups to provide a unified, fault-tolerant monitoring solution.
DevOps engineers, SREs, and platform teams managing large-scale Prometheus deployments in production environments, particularly those in Kubernetes or multi-cluster setups requiring high availability and unlimited metric retention.
Developers choose Thanos for its seamless integration with Prometheus, enabling global querying across all instances without disrupting existing setups. Its unique selling point is the combination of unlimited, cost-effective storage in any object storage with high availability and deduplication features, making it a robust solution for enterprise-scale monitoring.
Highly available Prometheus setup with long term storage capabilities. A CNCF Incubating project.
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Provides a single endpoint to query metrics across all connected Prometheus servers, enabling unified monitoring across clusters and data centers as highlighted in the key features.
Leverages object storage for historical metric data, allowing unlimited retention at lower costs compared to local SSD storage, directly addressing Prometheus's scalability limits.
Ensures fault tolerance for Prometheus setups and automatically handles metrics from HA pairs, preventing data duplication and merging results on the fly.
Works on top of existing Prometheus deployments without disruption, using sidecar or receive modes for easy adoption, as emphasized in the architecture overview.
Requires composing multiple components (e.g., Sidecar, Query, Store), increasing deployment complexity and operational learning curve, contrary to simple, all-in-one solutions.
Mandates object storage for unlimited retention, adding infrastructure dependencies and potential latency for queries, which may not suit all environments.
Demands ongoing maintenance and tuning, especially in large-scale setups, due to its distributed nature and need for monitoring the Thanos components themselves.