The search experience on your website is often the key driver of visitor satisfaction. Even on well-designed, well-organized websites, visitors frequently resort to search to find the exact products, services, content, and information they need. In fact, many visitors go immediately to the search box. The quality of search results they get back, and the ease with which they can customize and filter those results, can play an outsized role in engagement, conversion, and customer loyalty.
Engineering teams hoping to gain full-stack observability into their environment need access to the relevant logs, metrics, and traces generated by their cloud infrastructure and applications. Accessing the relevant data quickly is essential – not just because it is more convenient, but because faster engineers are also business-critical for many organizations.
There are many ways to add search functionality to a Rails application. While many Rails developers choose to use the native search functionality built into popular databases like MySQL and Postgres, others need more flexible or feature rich search functionality. ElasticSearch is probably the most well known option available but it has its own issues. Firstly, it is a resource hungry beast. To run ElasticSearch properly in production, you need a few beefy servers.
At ElasticON Global 2021, we shared a future view of Elastic Enterprise Search and how we’re continuing to build next-generation, machine learning-powered search experiences backed by the speed, scale, and relevance of Elasticsearch. We also highlighted the many ways we plan to keep building even more flexibility into our solutions.
We are pleased to announce the general availability of Elastic 7.15, a release that brings a broad set of new capabilities to the Elastic Search Platform (including Elasticsearch and Kibana) and its three built-in solutions — Elastic Enterprise Search, Elastic Observability, and Elastic Security.
Our first tutorial gave a general introduction to OpenSearch installation and configuration. We recently also published a comparative introduction for OpenSearch queries (and how they parallel or contrast with Elasticsearch). Now, we’ll continue that series with an intro to OpenSearch clusters. This is a very simple tutorial with straight-forward examples, but we will try to cover some detail and common advanced settings.