A comprehensive guide to scaling Prometheus in high-volume environments, covering horizontal scaling, remote storage, resource optimization, and high availability configurations. The article provides
practical implementations and configurations for each scaling strategy, including federation, sharding, query optimization, and monitoring solutions.
Reasons to Read -- Learn:
specific configuration techniques for scaling Prometheus beyond its default capacity of 1-2 million active time series and 100,000 samples per second
how to implement multiple scaling strategies with practical code examples, including federation, sharding, remote storage integration, and query optimization configurations
concrete methods for reducing resource usage through relabeling, metric filtering, and storage optimization, with detailed configuration examples in YAML format
publisher: @platform.engineers
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