A Rust client for Elasticsearch (alpha)
We're happy to announce an initial alpha release of a new Rust client for Elasticsearch! You can find it on crates.io with the crate name elasticsearch and dive into the documentation to get started.
We're happy to announce an initial alpha release of a new Rust client for Elasticsearch! You can find it on crates.io with the crate name elasticsearch and dive into the documentation to get started.
As part of Elasticsearch 7.5.0, we introduced a couple of ways to control the index age math that’s used by index lifecycle management (ILM) for phase timings calculations using the origination_date index lifecycle settings. This means you can now tell Elasticsearch how old your data is, which is pretty handy if you’re indexing data that’s older than today-days-old.
Curious about how to write more idiomatic concurrent code in Go? It’s not always easy or intuitive, even if you’ve done lots of concurrent programming in other languages. I’ve been lucky to have worked in a well-written code base, and had the expert advice of Beats core area lead Steffen Siering along the way. In this post I’ll walk you through how we implemented a new scheduler for Heartbeat that is part of our upcoming 7.6.0 release.
KeyBank is one of the largest banks in the United States. And as the bank has grown, so has their end-to-end monitoring system. With more than 1,100 branches and 1,400 ATMs stretching across 15 states, KeyBank’s infrastructure had evolved into a “Noah’s Ark of design,” says Mick Miller, Senior Product Manager, Cloud Native at KeyBank. In other words, they had two of everything, resulting in 21 different data islands.
When it comes to having visibility and detecting threats on macOS, one of the best sources of information for file system events, process events, and network events is the kernel. MacOS kernel extensions provide the ability to receive data about these events in real time with great detail. This is good for providing quick visibility into detecting anomalies and identifying possible threats.
As another year is coming to an end, let's take time to look at what happened in Lucene land in 2019.
Wow, it's finally here! After 25 fantastic articles we've reached the end of the 2019 Elastic Advent series. We've covered Elasticsearch and Python, Auditbeat, ECS, data transform, jvm options, anomaly detector models, Maps, SSL configuration, Smart query cancellation, data transforms, SLM, the new enrich processor, App Search, and so much more. In the topics we've spoken in German, Greek, English, French, Finish, Spanish and Swedish.
Using percentages when performing data analytics is an essential approach to effective numeric comparison, especially when the data in question demonstrates drastically different sample sizes or totals. Percentages allow for a quick and accurate understanding of how much data sums have changed across a dimensional category like a range of time, geographic regions, product lines, etc.
As attackers continue to evolve and advance their techniques, tactics, and procedures (TTPs), it is crucial for enterprise organizations to deploy necessary countermeasures and defenses to secure their networks. Elastic Security provides an endpoint protection platform (EPP) with some of the most advanced and effective endpoint protections and preventions on the market today.
Tools. As engineers we all love great tools that help our teams work productively, resolve problems faster, be better. But tools can tend to grow in number, require additional maintenance, and most importantly, create silos. Each team has certain responsibilities and is constantly searching for tools that can address specific requirements in the best possible way.