Back in our 7.10 release of the Elastic Stack, we announced the beta of our Ruby and Python clients for Elastic Enterprise Search. Now, with 7.11, both the Ruby and Python clients are generally available. We’ve also begun work on a PHP client. All client source code for both enterprise-search-ruby and enterprise-search-python is available on GitHub. Documentation on how to get started with each client is available on elastic.co.

When it comes to your SIEM, your data is only as useful as your ability to ingest and analyze it. To solve complex security problems, your team ideally needs the ability to comprehensively monitor events within your environment with contextual insights from high-volume data sources.

Graphical processing units, or GPUs, aren’t just for PC gaming. Today, GPUs are used to train neural networks, simulate computational fluid dynamics, mine Bitcoin, and process workloads in data centers. And they are at the heart of most high-performance computing systems, making the monitoring of GPU performance in today's data centers just as important as monitoring CPU performance.

The cold tier of searchable snapshots, previously beta in Elasticsearch 7.10, is now generally available in Elasticsearch 7.11. This new data tier reduces your cluster storage by up to 50% over the warm tier while maintaining the same level of reliability and redundancy as your hot and warm tiers.

Security information and event management (SIEM) systems are centralized logging platforms that enable security teams to analyze event data in real time for early detection of targeted cyber attacks and data breaches. A SIEM is used as a tool to collect, store, investigate, and report on log data for threat detection, incident response, forensics, and regulatory compliance.

With an increasing number of organizations migrating their applications and workloads to containers, the ability to monitor and track container health and usage is more critical than ever. Many teams are already using the Metricbeat docker module to collect Docker container monitoring data so it can be stored and analyzed in Elasticsearch for further analysis. But what happens when users are using Amazon Elastic Container Service (Amazon ECS)? Can Metricbeat still be used to monitor Amazon ECS? Yes!

We are excited to announce the new Elastic Cloud usage analysis page. You can now explore and analyze your Elastic Cloud usage to better understand how the resources you consume contribute to your monthly bill. Your Elastic Cloud monthly bill consists of usage fees for the resources you used, including: Understanding your resource utilization allows you to make smarter decisions about your Elastic deployments as well as identify areas where you may be able to save costs.

Istio is an open source service mesh that can be used by developers and operators to successfully control, secure, and connect services together in the world of distributed microservices. While Istio is a powerful tool for teams, it's also important for administrators to have full visibility into its health. In this blog post, we'll take a look at monitoring Istio and its microservices with Elastic Observability. As the Istio docs mention.

We are pleased to announce the general availability (GA) of Elastic 7.11. This release brings a broad set of new capabilities to our Elastic Enterprise Search, Observability, and Security solutions, which are built into the Elastic Stack — Elasticsearch and Kibana. This release enables customers to optimize for cost, performance, insight, and flexibility with the general availability of searchable snapshots and the beta of schema on read.

We are thrilled to announce the general availability of alerting in the Elastic Stack with the release of 7.11. With deep integrations throughout our products and solutions, a laser focus on distinguishing signal from noise, and tie-ins to the third-party platforms you depend on like email, PagerDuty, ServiceNow, and Microsoft Teams, building, using, and acting on alerts in Elastic has never been more powerful.

In Elastic Enterprise Search 7.11, we’re thrilled to announce the beta launch of Elastic App Search web crawler, a simple yet powerful way to ingest publicly available web content so it becomes instantly searchable on your website. Making content on these websites searchable can take several forms. Elastic App Search already lets users ingest content via JSON uploading, JSON pasting, and through API endpoints.

Historically, Elasticsearch has relied on a schema on write approach to make searching data fast. We are now adding schema on read capabilities to Elasticsearch so that users have the flexibility to alter a document's schema after ingest and also generate fields that exist only as part of the search query. Together, schema on read and schema on write provides users with the choice to balance performance and flexibility based on their needs.

In 7.11, we’re excited to announce support for schema on read in the Elastic Stack. We now offer the best of both worlds on a single platform — the performance and scale of the existing schema on write mechanism that our users love and depend on, coupled with a new level of flexibility for defining and executing queries with schema on read. We call our implementation of schema on read runtime fields.

WaKED-CO (Watch of Knowledge on Emergent Diseases COVID-19) is an initiative launched in record time — deployed just a month after developing a prototype — under the leadership of the health service within the Ministry of Armed Forces in France. The project had one core mission: to make it easier to research the literature around the COVID-19 crisis.

This post is a recap of a presentation given at ElasticON 2020. Interested in seeing more talks like this? Check out the conference archive. Network infrastructure is the engine that drives a company’s business. As companies scale, assets that compose this infrastructure become more complex to manage. That means there’s more hardware, more software, and more subscriptions and services that require tracking.

As a security analyst on Elastic’s InfoSec team, a common scenario we see is users coming to our team and asking: “Is this file safe to open?” Or one user reports a phishing email with an attachment that they didn’t open, but we see from the logs that 10 other users also received that email but didn’t report it and no alerts went off on their systems.

When we announced our license change for Elasticsearch and Kibana, moving the Apache 2.0-licensed source code to be dual licensed under both the Elastic License and SSPL, we also mentioned we would work closely with the community on a simplified and more permissive version of the Elastic License. I am happy to share the results with you. The Elastic License is already widely used.

Elasticsearch 7.10 made configuring the lifecycle of your data less complicated. In this blog post I’ll walk through some of the changes, how to use them, and some best practices along the way. Data lifecycle can encompass a lot of stages, so we’ll touch on.