Planning for cluster capacity and resources
Planning for sufficient cluster capacity and resources is crucial for any production environment, especially when implementing a vector search use case of considerable size. To ensure optimal performance and efficiency, careful consideration, planning, and testing must be carried out.
In the following chapter, we will delve into load testing, which is an essential part of fine-tuning and optimizing your Elasticsearch deployment. But before that, we will explore what it takes to run embedding models on ML nodes in Elasticsearch, outlining the essential factors to consider in order to strike the right balance between performance and resource utilization. In this section, we will discuss the critical aspects of CPU, RAM, and disk requirements, setting the stage for a comprehensive understanding of resource management in Elasticsearch.
CPU and memory requirements
The CPU requirements for vector search in Elasticsearch are not drastically...
