Distributed tracing remains one of the most important features of any tracing system. Nearly a year ago, we announced Elastic APM distributed tracing, let’s take a look at how this useful feature works behind the scenes. Over the past few years, many applications have adopted microservice architecture. Each of the services in a microservice architecture can have their own instrumentation to provide observability into the service.
A lot of businesses are thinking about the future of virtual work and how to make it successful in light of recent world events. For managers and employees used to working in a traditional office space, moving to remote work can be a challenge on many fronts. How do I and my team stay motivated and productive? What’s the best setup for a home office? Most importantly, how do I separate office work from the duties I normally perform around the home?
Distributed tracing is great — it helps you identify (micro)services within complex architectures having issues interfering with user experience, such as high latency or errors. But once a problematic service is identified, it can be difficult to find out which methods are to blame for the slowdown. Well, we have some big news to share for our Elastic APM users within the Java ecosystem.
More than 40 million people use GitHub as a collaboration tool for building software around the world. For most companies — including distributed teams like Elastic — GitHub has become a critical content source for building software, holding much of the information and knowledge upon which the organizations are built, across items like issues, pull requests, and more.
Last month, we hosted a webinar, Hunting for persistence using Elastic Security, where we examined some techniques that attackers use in the wild to maintain presence in their victim’s environment. In this two-part blog series, we’ll share the details of what was covered during our webinar with the goal of helping security practitioners improve their visibility of these offensive persistence techniques and help to undermine the efficacy of these attacks against their organization.
BlackSky monitors the globe from space, the air, the ground, the internet, environmental sensors, asset tracking sensors, satellites in space, social media feeds, industrial IoT, and other sources too numerous to name. Once gathered in their Elastic-powered analytics engine, all of the data from these disparate sources is correlated, compared, and cleaned.
Elastic Workplace Search is rooted in a simple, but powerful mission: bringing information, content, and files from every corner of your organization into a singular, centralized source of truth. Thanks to its portfolio of first-party integrations, Workplace Search easily connects to a variety of popular content platforms.
We’re happy to announce the beta availability of our new government region, AWS GovCloud (US East), for the Elasticsearch Service on Elastic Cloud. This new region is our first step in simplifying operations for Elastic users who handle government data as we work toward gaining a Moderate authorization for the Federal Risk and Authorization Management Program (FedRAMP).
Until now, standard search solution pricing has been based on models that are difficult to understand, expensive to scale, and/or beneficial to only the search vendor. At Elastic, we’re taking a different approach based on the principles of transparency, fairness, and scalability, and have introduced resource-based pricing for our products running on Elastic Cloud. And we believe that this pricing approach will revolutionize Enterprise Search buying and ownership.
With the release of Elastic Security 7.6, we've announced our creation of a modern detection engine that provides SOC teams with a unified SIEM rule experience through Elastic SIEM detections. The detection engine draws from a purpose-built set of Elasticsearch analytics engines and runs on a new distributed execution platform in Kibana.
