What Is Thanos?

Thanos is an open-source project that extends Prometheus to provide long-term metrics storage, global query capabilities across multiple Prometheus instances, and high availability. It integrates seamlessly with existing Prometheus deployments by uploading metric data to object storage like S3 or GCS and providing a unified query layer that aggregates data from all Prometheus instances and historical storage.

Why Thanos Matters

Prometheus is designed for short-term metric storage on local disk, which limits retention to weeks rather than months or years. It also runs as a single instance per cluster, making it difficult to query metrics across multiple clusters. Thanos solves both problems by offloading historical data to cheap object storage and providing a global query interface that federates data from all instances.

Teams that understand and adopt thanos gain a significant operational advantage, reducing manual effort and improving the reliability and scalability of their infrastructure. As cloud-native adoption accelerates, familiarity with thanos has become a core competency for DevOps engineers, platform teams, and site reliability engineers working in production Kubernetes and cloud environments.

How Thanos Works

Thanos runs a sidecar container alongside each Prometheus instance that uploads metric blocks to object storage. The Thanos Store component serves historical data from object storage. Thanos Query acts as a unified query frontend that aggregates real-time data from Prometheus sidecars and historical data from the Store. Thanos Compact handles downsampling and compaction of historical data to keep storage costs low.

Understanding how thanos fits into the broader cloud-native ecosystem is important for making informed architecture decisions. It works alongside other tools and practices in the DevOps and platform engineering space, and choosing the right combination depends on your team's specific requirements, scale, and operational maturity.

Key Features

Long-Term Storage

Store months or years of Prometheus metrics in object storage like S3 or GCS at a fraction of local disk cost.

Global Query

Query metrics across all Prometheus instances and clusters through a single, unified endpoint.

High Availability

Deduplicate metrics from Prometheus HA pairs, ensuring consistent query results even with redundant setups.

Downsampling

Automatically downsample historical data to reduce storage costs while maintaining useful resolution for long-range queries.

Common Use Cases

Retaining Prometheus metrics for one year or more in S3 for capacity planning and historical trend analysis.

Querying metrics across multiple Kubernetes clusters from a single Grafana dashboard using Thanos Query.

Running Prometheus in a high availability pair with Thanos deduplication ensuring clean query results.

Compacting and downsampling old metrics to reduce object storage costs for long-term retention.

How Obsium Helps

Obsium's managed observability team helps organizations implement and optimize thanos as part of production-grade infrastructure. Whether you are adopting thanos for the first time or looking to improve an existing implementation, our engineers bring hands-on experience across cloud platforms and Kubernetes environments. Learn more about our managed observability services →