Thanos is an open-source project that enhances Prometheus' capabilities, providing high availability, global query capabilities, and long-term storage for Prometheus metrics. It acts as a layer on top of existing Prometheus deployments, allowing you to seamlessly scale your monitoring infrastructure and retain historical metrics data for extended periods.

• **Global Query:** Thanos enables you to query metrics across multiple Prometheus servers, providing a unified view of your entire environment, even if you have Prometheus instances running in different clusters or regions.
• **High Availability:** Thanos's components are designed to be highly available, ensuring uninterrupted access to metrics data and query capabilities even in the event of failures.
• **Long-Term Storage:** It supports integration with various object storage backends, such as Amazon S3, Google Cloud Storage, and Azure Blob Storage, allowing you to store and query historical metrics data for extended periods.
• **Downsampling and Compaction:** Thanos can automatically downsample and compact historical metrics data, reducing storage costs and improving query performance.
• **Rule Evaluation:** It can evaluate Prometheus recording and alerting rules across multiple Prometheus instances, ensuring consistent alerting and metric aggregation.

• **Scalability:** Thanos allows you to scale your Prometheus monitoring infrastructure horizontally, handling large volumes of metrics data and accommodating growing environments.
• **High Availability:** Its high-availability design ensures that your monitoring system remains operational even if individual components fail.
• **Long-Term Retention:** Thanos enables you to store and query historical metrics data for months or even years, providing valuable insights into long-term trends and patterns.
• **Cost Optimization:** Downsampling and compaction help reduce storage costs associated with long-term metric retention.
• **Unified View:** Thanos's global query feature provides a single, unified interface for querying metrics across multiple Prometheus servers, simplifying monitoring and analysis.

While Thanos configuration involves YAML files and command-line options, here's a simplified example of a Thanos Sidecar configuration:

```yaml apiVersion: v1 kind: Pod metadata:

 name: prometheus-sidecar

 containers:
 - name: prometheus-sidecar
   image: quay.io/thanos/thanos:latest
   args:
   - sidecar
   - --prometheus.url=http://localhost:9090/metrics
   - --tsdb.path=/prometheus/data
   - --objstore.config-file=/etc/thanos/objstore.yaml
   volumeMounts:
   - name: prometheus-data
     mountPath: /prometheus/data
   - name: objstore-config
     mountPath: /etc/thanos
 volumes:
 - name: prometheus-data
   emptyDir: {}
 - name: objstore-config
   secret:
     secretName: my-objstore-secret

This configuration deploys a Thanos Sidecar container alongside a Prometheus server, enabling it to upload metrics data to an object storage backend configured in the `my-objstore-secret` Secret.

• **Thanos Official Website:** s://thanos.io/(https://thanos.io/)
• **Thanos GitHub Repository:** s://github.com/thanos-io/thanos(https://github.com/thanos-io/thanos)
• **Thanos Documentation:** [invalid URL removed]