### Module 5: Performance Tuning #### Lesson 1: Monitoring Tools and Metrics for OpenSearch **Objective**: Equip participants with the knowledge to effectively monitor OpenSearch clusters, utilizing the right tools and understanding key performance metrics. **Topics**: - **Introduction to Monitoring Tools**: Overview of built-in OpenSearch monitoring features, third-party tools, and AWS monitoring services like Amazon CloudWatch for OpenSearch Service. - **Key Performance Metrics**: Detailed explanation of essential OpenSearch metrics, including CPU usage, memory usage, JVM heap usage, disk I/O, and network traffic. - **Interpreting Metrics**: How to interpret these metrics in the context of OpenSearch performance and identify potential bottlenecks or issues. - **Alerting and Anomaly Detection**: Setting up alerts for critical metrics and using anomaly detection to preemptively address performance issues. #### Lesson 2: Tuning Index Performance (Shard Sizes, Refresh Rates) **Objective**: Dive into strategies for optimizing index performance through effective shard management and understanding the impact of refresh rates. **Topics**: - **Optimal Shard Size**: Discussing the trade-offs associated with large vs. small shard sizes, and how to find the optimal size for different use cases. - See [[Shard#Strategies for Balancing Shard Size and Count]] - **Shard Allocation and Balancing**: Techniques for distributing shards across nodes to ensure balanced workloads and prevent hotspots. - **Adjusting Refresh Rates**: Understanding how the refresh rate affects indexing performance and search latency, and when to adjust it. - **Forced Merges**: Exploring the use of forced merges to reduce shard count and improve query performance for read-heavy indices. #### Lesson 3: Query Optimization Techniques **Objective**: Teach effective techniques for optimizing OpenSearch queries to reduce latency and resource consumption. **Topics**: - **Writing Efficient Queries**: Best practices for constructing queries to minimize their performance impact, including the use of filters, avoiding heavy aggregations, and using the right query types. - **Understanding Query Execution**: Insight into how OpenSearch executes queries and how this affects performance. - **Caching Strategies**: Leveraging OpenSearch’s query cache and field data cache to improve query performance. - **Profiling Queries**: Using the OpenSearch Profile API to analyze and optimize query execution.