Elasticsearch powers search experiences for so many tools and apps used today, from operational analytics dashboards to maps showing the closest restaurants with patios so you can get out of the house. And in all of those implementations, the connection between application and cluster is made via an Elasticsearch client. Optimizing the connection between the client and the Elasticsearch cluster is extremely important for the end user’s experience.

We’re pleased to introduce you to the latest Elastic Cloud features and functionality. Grab a cup of your favorite beverage and five minutes, and let’s dive in.

You’ve created the perfect design for your indices and they are happily churning along. However, in the future, you may need to reconsider your initial design. Maybe you want to improve performance, change sharding settings, adjust for growth. Whatever the reason, Elasticsearch is flexible and allows you to change index settings to improve your Elasticsearch Performance Tuning. Let’s see how to do that!

We're excited to announce that Elastic Enterprise Search is now available on Elastic Cloud. Simply sign up for a free Elastic Cloud account and you can be up and running in a matter of minutes. The Elastic Enterprise Search solution encompasses both our Workplace Search and App Search products — a comprehensive package of search tools that dramatically simplifies the process of creating enterprise-grade search experiences for consumers, users, and teammates alike.

Amazon Web Services Elasticsearch Service enables an organization to deploy, secure, and run their Elasticsearch clusters. AWS Elasticsearch is a cost-effective way to operate at scale. In this article, we will cover.

Jira has long been a popular issue tracking tool for development teams, but its scope has broadened quite a bit over the years, and it has bloomed into a more well-rounded project management tool as well. It’s used widely by agile teams to plan, track, and release software, along with numerous other cloud (and traditional self-managed) productivity tools.

Elastic is prepping for Elasticsearch 8.0, but in the meantime is rolling out upgrades and features with Elasticsearch 7.7. The new version introduces asynchronous search as well as changes with Elasticsearch clusters, mapping, SQL enhancements, snapshots and machine learning. This post will cover just a few of the highlights of the new release. Besides asynchronous search, ES 7.7 also introduces multi-class classification, reduced heap usage, inference time features, and better password security.

At Elastic, we love data. It’s the backbone of what we do: search. And that data takes many forms. A knowledge base article showing how to reset your cable box — data. Logs from your network — data. IP addresses accessing your secure network — data. A video tutorial on how adults can use TikTok — data. The list goes on. But behind each piece of data is a story. And a person. Or a customer.

Elasticsearch has a lot of strengths (speed, scale, relevance), but one of its most important strengths is its flexibility to be added to existing environments without the need for any sort of architectural overhaul. If you are a sysadmin (dev, sec, ops, etc.), you know just how appealing this is. So many legacy systems remain in place not because they are perfect, but because replacing them would cost time and money that you don't have.