Kubernetes platforms generate massive volumes of logs from microservices, infrastructure, and platform services. At scale, OpenSearch observability pipelines often struggle with shard explosion, indexing bottlenecks, JVM pressure, and slow queries.

This session presents a practical architecture for operating an OpenSearch observability platform handling 100M+ logs per day from Kubernetes environments. We will walk through the end-to-end pipeline—from log collection to ingestion and indexing—and share performance engineering techniques used to maintain cluster stability under heavy workloads.

Topics include shard and index design, JVM and thread-pool tuning, optimizing indexing throughput, and using lifecycle policies and hot-warm architectures to scale efficiently. Attendees will gain actionable strategies for building resilient OpenSearch observability platforms for cloud-native systems.