Vector Search for Practitioners with Elastic

4

Performance Tuning – Working with Data

In the previous chapter, we covered how to integrate Elasticsearch with machine learning (ML) models. In this chapter, we’ll focus on optimizing vector search performance in Elasticsearch.

The topics we will cover include the following:

• ML model deployment tuning techniques
• Estimating vector capacity for an Elasticsearch node
• Load testing with Elastic’s performance tool, Rally
• Troubleshooting slow k-nearest neighbor (kNN) search response times

By the end of this chapter, you will understand how to estimate the number of Elasticsearch nodes required for your use case, how to use performance benchmarking to ensure those estimates are in line with your requirements, and identify potential causes for slow ...