What is Thanos?
Why developers like Thanos?
Here are some stack decisions, common use cases and reviews by companies and developers who chose Thanos in their tech stack.
We recently implemented Thanos alongside Prometheus into our Kubernetes clusters, we had previously used a variety of different metrics systems and we wanted to make life simpler for everyone by just picking one.
Prometheus seemed like an obvious choice due to its powerful querying language, native Kubernetes support and great community. However we found it somewhat lacking when it came to being highly available, something that would be very important if we wanted this to be the single source of all our metrics.
Thanos came along and solved a lot of these problems. It allowed us to run multiple Prometheis without duplicating metrics, query multiple Prometheus clusters at once, and easily back up data and then query it. Now we have a single place to go if you want to view metrics across all our clusters, with many layers of redundancy to make sure this monitoring solution is as reliable and resilient as we could reasonably make it.
If you're interested in a bit more detail feel free to check out the blog I wrote on the subject that's linked.
- Global querying view across all connected Prometheus servers
- Deduplication and merging of metrics collected from Prometheus HA pairs
- Seamless integration with existing Prometheus setups
- Any object storage as its only, optional dependency
- Downsampling historical data for massive query speedup
- Cross-cluster federation
- Fault-tolerant query routing
- Simple gRPC "Store API" for unified data access across all metric data
- Easy integration points for custom metric providers