🚨 Elasticsearch High CPU Issue Due to Memory Pressure – Real Production Incident & Fix

🔍 Introduction Running Elasticsearch in production requires deep visibility into CPU, memory, shards, and cluster health. One of the most confusing scenarios DevOps engineers face is: ⚠️ High CPU alerts, but CPU usage looks normal In this blog, I’ll walk you through a real production incident where: Elasticsearch triggered CPU alerts But the actual root cause was memory pressure + shard imbalance + node failure We’ll cover: Core Elasticsearch concepts Real logs and debugging steps Root cause analysis Production fix 📘 Important Elasticsearch Concepts Before diving into the issue, let’s understand some key building blocks. 📦 How Elasticsearch Stores Data Elasticsearch stores data as documents, grouped into an index. However, when data grows large (billions/trillions of records), a single index cannot be stored efficiently on one node. 🔹 What is an Index? An Index is: A collection of documents Logical partition of data Similar to a database 👉 Example: metricbeat-* .monitoring-* user-data