We recently announced the general availability of our Elasticsearch Service API. APIs help to automate tasks such as creating and scaling deployments, integrating with existing workflows, and testing. The Elasticsearch Service API supports the Open API Specification, which allows you to use tools like Swagger to generate software development kits (SDKs) in any programming language. You can import the API spec onto Postman and create a Postman Collection to create a test suite.

In a previous blog, we saw that the seemingly simple job of an Elasticsearch client — moving data between the calling code and the cluster — is actually quite complicated under the hood. Naturally, as much as we try to make the default behaviour of the client optimal for the majority of scenarios, there are situations where you want to configure, customize, or enable/disable certain features.

We love maps at Elastic. In the Elastic Stack, there is one core component of all data we visualize using maps: Location. Location can mean reporting real-time positions of fleet vehicles, using a geofence for limiting search results, gauging application performance metrics from a geographic area, or identifying security threats by attaching geographic coordinates to IP addresses.

In two previous posts, we covered structuring data with grok and building custom grok patterns. But what happens if you just can’t get your grok patterns to work? In this article, we’re going to use Kibana’s Grok Debugger to help us debug a broken grok pattern. The divide-and-conquer method described below should help you to quickly find the reason that a given grok pattern is not matching your data.

The goal of Java application monitoring is to minimize the time it takes to discover a problem with a Java application (mean time to detect, or MTTD) and the time it takes to recover from it (mean time to resolve, or MTTR). Understanding what's going on in our code is the biggest step in finding and eliminating the root cause of a problem, and let's face it — that code that seemed clear and concise when we wrote it a year ago might not be as "self documenting" as we thought.

Open source contributions are foundational to Elastic — from Elasticsearch’s Apache Lucene core to the addition of open source Logstash and Kibana to form the Elastic Stack you’ve come to know and love. Over the years, the Elastic community has created over 90 Beats, shared use case tutorials like those from Volvo, T-Mobile, and Microsoft, and presented at hundreds upon hundreds of meetups.

Since we launched Canvas in 2018, we have seen tons of our users create beautiful dashboards that tell stories with Elasticsearch data. In the spirit of making it even easier to get started, we are creating templates that you can import and get instantly beautiful dashboards for all the data the Elastic Stack captures.

The official Go client for Elasticsearch is one of the latest additions to the family of clients developed, maintained, and supported by Elastic. The initial version was published early in 2019 and has matured over the past year, gaining features such as retrying requests, discovering cluster nodes, and various helper components. We also provide comprehensive examples to facilitate using the client.

We recently released our new training Quick Start guides for the products in the Elastic Enterprise Search solution: Elastic Workplace Search and Elastic App Search. Each product is built on the Elastic Stack, so you can enjoy its speed, scale, and relevance without the heavy development and maintenance requirements of building your own search solution. Each 15-minute video tutorial provides everything you need to start creating powerful search experiences for your workplace, websites, and apps.

Elastic Cloud Enterprise (ECE) makes it easy to manage your Elastic Stack deployments, just like role-based access control (RBAC) makes it easy to manage your users. Combining the two can really make an administrator's life much simpler. The intent of this blog post is to provide instructions for configuring a SAML realm for RBAC in ECE environments where Auth0 is used as an identity provider (IdP).