The aggregations framework has been part of Elasticsearch since version 1.0, and through the years it has seen optimizations, fixes, and even a few overhauls. Since the Elasticsearch 7.0 release, quite a few new aggregations have been added to Elasticsearch like the rare_terms, top_metrics or auto_date_histogram aggregation. In this blog post we will explore a few of those and take a closer look at what they can do for you.
The ability to monitor your Elastic Cloud deployment is critical for helping ensure its health, performance, and security. Our Elastic Observability solution provides unified visibility across your entire ecosystem — including your Elastic Cloud deployments. Elastic Observability allows you to bring your logs, metrics, and APM traces together at scale in a single stack so you can monitor and react to events happening anywhere in your environment.
You may have noticed how on sites like Google you get suggestions as you type. With every letter you add, the suggestions are improved, predicting the query that you want to search for. Achieving Elasticsearch autocomplete functionality is facilitated by the search_as_you_type field datatype. This datatype makes what was previously a very challenging effort remarkably easy.
More organizations than ever before have shifted to a hybrid work culture to reduce the impact of COVID-19. This unprecedented change has not only given rise to new security challenges, but has also considerably increased the surface area available for an attack. A blend of personal and corporate endpoints in use, geographical spread of resources, and a sharp spike in the overall number of security threats have further complicated the already labor-intensive security landscape.
Last month we launched the Elastic Contributor Program to recognize and reward the hard work of our awesome contributors, encourage knowledge sharing within the Elastic community, and build friendly competition around contributions. But how do you start contributing? In this blog post, we’ll walk through how to log in to the Elastic Contributor Program portal and set up your profile so you can begin submitting your own contributions and validating others’ contributions!
Elastic 7.6 introduced the inference processor for performing inference on documents as they are ingested through an ingest pipeline. Ingest pipelines are incredibly powerful and flexible but they are designed to work at ingest. So what happens if your data is already ingested? Introducing the new Elasticsearch inference pipeline aggregation, which lets you apply new inference models on data that's already been indexed.
Chances are you already spent a big part of your day looking for a document, an email, or an answer that lies deep within a Google Slides presentation. Thankfully, you landed in the right place. With Workplace Search, finding the right information across all your cloud and on-premises data platforms is now easier than ever, and it’s a few clicks closer than you expect.
At Siren, we build a platform used for “investigative intelligence” in Law Enforcement, Intelligence, and Financial Fraud. Investigative intelligence is a specialisation of data analytics that serves the needs of those that are typically hunting for bad actors. Such investigations are the primary focus of law enforcement and intelligence, but are also critical to uncovering financial crime activities and for threat hunting in cybersecurity.
