Explore essential strategies to optimize Elasticsearch performance and cost efficiency. Learn best practices for cluster scaling, data tiering, and monitoring for both Elastic Cloud and on-premises deployments.

BigData Boutique recently hosted a webinar in partnership with Elastic and the Elastic community. Itamar Syn-Hershko, Founder of Pulse, shared valuable insights on maximizing performance and cost efficiency when using Elasticsearch on Elastic Cloud and on-premises setups. Here's a glimpse into the key takeaways:





Key Insights on Performance and Cost Efficiency

Itamar drew on his extensive experience with Elasticsearch to discuss the evolution of BigData Boutique and its focus on providing consulting and training services for Elasticsearch and the full Elastic Stack. He highlighted the need for rightsizing Elasticsearch clusters to achieve optimal performance while managing costs. Key points discussed included:

1. Scaling Up vs. Scaling Out

Itamar emphasized the importance of prioritizing scaling up (increasing node resources) rather than scaling out (adding more nodes) to improve performance and cost-effectiveness.

2. Cluster Topology

Separating data nodes from master nodes is crucial for enhancing stability and performance. This separation helps to distribute workloads more effectively and reduces the risk of performance degradation.

3. Data Tiering

Utilizing different storage tiers (hot, warm, cold) is essential for optimizing storage costs based on data access patterns. This strategy allows organizations to balance performance and cost efficiency.

4. Monitoring Key Metrics

Tracking critical metrics such as load average, heap memory usage, and thread pool metrics can help identify performance bottlenecks and resource constraints. Itamar stressed the importance of continuous monitoring to maintain optimal cluster performance.

Advanced Optimization Techniques

In the latter part of the webinar, Itamar delved deeper into advanced techniques for optimizing Elasticsearch performance and cost efficiency. Key strategies included:

  • Load Average: Regularly monitor the 5-minute load average to ensure optimal CPU utilization.
  • Heap Memory Management: Set the heap size to no more than 50% of total memory and avoid exceeding 30GB to prevent performance issues.
  • Thread Pools: Keep an eye on thread pool queues to identify potential bottlenecks and adjust resource allocation accordingly.
  • Data Tiering Implementation: Efficiently implement hot, warm, and cold storage tiers to balance performance and cost.
  • Shard Strategy: Maintain a balanced shard distribution to ensure even load across nodes.
  • Indexing and Query Optimization: Utilize data streams and rollovers to manage shard sizes and enhance query performance. Itamar cautioned against expensive queries, such as those using leading wildcards or scripts.
  • Caching Mechanisms: Leverage query and request caches to boost query performance.
  • Vector Search Techniques: Consider using KNN for small datasets and HNSW for larger ones. Optimize vector search performance through techniques like quantization and segment merging.

Troubleshooting Slow Queries

To troubleshoot slow queries, Itamar suggested the following:

  1. Review Infrastructure: Ensure that the cluster is properly sized and configured for your workloads.
  2. Analyze Query Patterns: Identify and optimize slow query patterns for better performance.
  3. Utilize Query Analytics: Use tools like Pools query analytics to gain insights into query performance and discover optimization opportunities.

By implementing these best practices and utilizing advanced techniques, you can significantly enhance the performance and cost-effectiveness of your Elasticsearch deployments.

Conclusion

With the insights shared, participants gained valuable knowledge on optimizing their Elasticsearch setups for both performance and cost efficiency. If you missed the live session, don't forget to watch the recording here to access all the valuable insights!

Get the best out of your Elasticsearch setup without the hassle. Pulse automates monitoring and cost optimization, helping you maintain top performance effortlessly. Learn more about Pulse and start optimizing today!