Elasticsearch is widely used, but that doesn't mean it's perfect. Elasticsearch projects can fail for any number of reasons, including Logstash node failure, the presence of too many shards, aggregations that are too deep, and even failures due to poorly mapped indices. Let’s take a look at some of the most common causes of project failure, and how to avoid them. In this chapter, we will explain Elasticsearch best practices that we can apply to increase performance. Oftentimes, people install Elasticsearch and start using it with the default settings, which causes some performance issues, so it is advisable to tune Elasticsearch to get optimal output.
In this chapter, we are going to cover the following topics:
- Failure to obtain the required data
- The best cluster configuration approaches
- Using index templates to save time
- Using _msearch for e-commerce...