Mountain View, CA, USA
Sep 17, 2020   |  By Karel Minařík
In our previous two blogs, we provided an overview of the architecture and design of the Elasticsearch Go client and explored how to configure and customize the client. In doing so, we pointed to a number of examples available in the GitHub repository. The goal of these examples is to provide executable "scripts" for common operations, so it's a good idea to look there whenever you're trying to solve a specific problem with the client.
Sep 16, 2020   |  By Enrique Kortright
In this two-part blog post, we’ll use Elastic Observability to monitor a sample Java application. In the first blog post, we started by looking at how Elastic Observability monitors Java applications. We built and instrumented a sample Java Spring application composed of a data-access microservice supported by a MySQL backend. In this part, we’ll use Java ECS logging and APM log correlation to link transactions with their logs.
Sep 15, 2020   |  By Sachin Frayne
For public IPs, it is possible to create tables that will specify which city specific ranges of IPs belong to. However, a big portion of the internet is different. There are company private networks with IP addresses of the form, or scattered in every country in the world. These IP addresses tend to have no real information for the geographic locations.
Sep 10, 2020   |  By François-Clément Brossard
OpenID Connect (OIDC) is an authentication layer based on OAuth 2.0 protocol that provides a way to identify and authenticate users via an authorization server. OAuth 2.0 authorization servers are managed by identity providers. In the domain associated with OIDC, they are also called OpenID Connect Providers (OPs). OIDC allows users to connect to web applications in a simplistic single sign-on (SSO) manner thanks to the identity provider.
Sep 10, 2020   |  By Darren Meiss
As work from home has ballooned in 2020, virtual methods for communicating with colleagues have become more critical than ever. Same goes for all the useful productivity and collaboration tools at our disposal. The emerging downside is the difficulty of finding needed information among so many tools. Compounding the problem is the tendency for info to get siloed off by department.
Sep 8, 2020   |  By Karel Minařík
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.
Sep 8, 2020   |  By Aravind Putrevu
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.
Sep 3, 2020   |  By Nick Peihl
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.
Sep 3, 2020   |  By Alex Marquardt
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.
Sep 2, 2020   |  By Enrique Kortright
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.
Sep 9, 2020   |  By Elastic
Snapshot Lifecycle Management (SLM) allows you to set up snapshot lifecycle policies to automate the timing, frequency, and retention of snapshots. In this talk we will cover the basics of registering a repository, setting up a snapshot policy and taking the test snapshots. If you are aware of the necessity of taking frequent snapshots for high availability/disaster recovery and you’ve been looking for a way to automate the whole process - then SLM is the right tool for you!
Aug 20, 2020   |  By Elastic
Kibana is quite powerful and versatile for visualizing data in Elasticsearch. And when you have a flexible tool like that, it's hard to know (and keep up with) everything that it can do. Just look at all of the things that MacGyver can do with a Swiss Army knife. In this talk, Felix will demo many of his favorite Kibana features — some new and some hidden gems — that let him make the most of his data.
Aug 19, 2020   |  By Elastic
Learn how the latest security capabilities in the Elastic Stack enable interactive exploration, incident management and automated analysis, as well as unsupervised machine learning to reduce false positives and spot anomalies — all at the speed and scale your security practitioners need to defend your organisation.
Aug 11, 2020   |  By Elastic
In this Black Hat 2020 presentation, learn from Elastic Security researchers how to hunt for adversary tradecraft in your organization’s network before damage and loss can occur.
Aug 3, 2020   |  By Elastic
Elastic Security equips analysts to solve their most pressing infosec problems by preventing, detecting, and responding to threats quickly and at scale.
Jul 31, 2020   |  By Elastic
This talk will dive into the technical details behind the recently announced Elastic Agent + Ingest Manager. After a quick overview of all the components involved and a demo, we explore how all the parts work together behind the scene. Some noteworthy parts to trigger your interest are "new indexing strategy", "constant_keywords", "datastreams" and a few more.
Jul 28, 2020   |  By Elastic
At Khoros, we provide a platform for brands to build a community around their customers. Behind the scenes, this community platform is powered by Elasticsearch for operations such as free text search, fetching data for our custom query language, and building customizations. Some of the biggest communities have millions of users and greater than 100 million documents. Come and take a look into how we index these millions of documents in a reliable and efficient way to power our community platform!
Jul 15, 2020   |  By Elastic
A quick look into how search can transform you organization. Kellen Person - Team Lead, Workplace Search
Jul 10, 2020   |  By Elastic
Introduction into Eland, a Python package to analyse, explore and manipulate Elasticsearch data. In this talk, Seth Larson introduces us to Eland. Eland is a Python Elasticsearch client for exploring and analyzing data residing in Elasticsearch with a familiar Pandas-compatible API.
Jul 2, 2020   |  By Elastic
Learn how to detect malicious events using both supervised and unsupervised machine learning techniques. See how to streamline the end-to-end experience of building and running machine learning jobs with the Elastic Stack.
Mar 1, 2018   |  By Elastic
Learn how you can use Elastic Stack and X-Pack features, from role-based access control to data encryption, to get your Elasticsearch data ready for GDPR.

Elastic is the world's leading software provider for making structured and unstructured data usable in real time for search, logging, security, and analytics use cases. Built on an open source foundation, the Elastic Stack lets you reliably and securely take data from any source, in any format, and search, analyze, and visualize it in real time.

The Elastic Stack:

  • Kibana gives shape to your data and is the extensible user interface for configuring and managing all aspects of the Elastic Stack.
  • Elasticsearch is a distributed, JSON-based search and analytics engine designed for horizontal scalability, maximum reliability, and easy management.
  • Beats is a platform for lightweight shippers that send data from edge machines to Logstash and Elasticsearch.
  • Logstash is a dynamic data collection pipeline with an extensible plugin ecosystem and strong Elasticsearch synergy.

Founded in 2012 by the people behind the Elasticsearch, Kibana, Beats, and Logstash open source projects, Elastic's global community has more than 80,000 members across 45 countries. Since its initial release, Elastic's products have achieved more than 100 million cumulative downloads.