In our last episode, I wrote about some speed improvements to date_histogram and I was beside myself with excitement to see if I could apply the same principles to other aggregations. I've spent most of the past few months playing a small part developing runtime fields but eventually I found time to take a look at the terms aggregation.

We are excited to share the latest development in our ongoing partnership with Microsoft. Available in public preview, you can now find, deploy, and manage Elasticsearch from within the Azure portal. Bring powerful enterprise search, observability, and security capabilities to your Azure environment with a user interface and tools that are already familiar to you.

We recently announced that users can find, deploy, and manage Elasticsearch from within the Azure portal. This new integration provides a simplified onboarding experience, all with the Azure portal and tooling you already know, so you can easily deploy Elastic without having to sign up for an external service or configure billing information.

It has been just over two years since we introduced the Elastic Common Schema (ECS), and what a journey it’s been. From categorization fields to request for comments to Threat Intelligence fields, ECS has evolved rapidly over the course of the last two years. In this blog post, I would like to reflect on the ECS journey so far, and look towards the future of ECS.

I’ll come clean and admit it – this part of the series will be a bit interesting given the fact that I know very little about Elasticsearch. So really, this is an honest test of the question – “can I still build something good with Dashboard Server even if I only have nominal knowledge of the tool where the data is sourced from?”

Elastic's new frozen data tier decouples compute from storage and leverages low-cost object stores such as Google Cloud Storage, Azure Blob Storage, or Amazon S3 to directly power searches. It provides unlimited scaling of storage while preserving the ability to efficiently query the data without any need to rehydrate it first, making it easier and cheaper to manage data at scale.

Hiya! With Elastic’s expansion of our Elasticsearch Service Cloud offering and automated onboarding, we’ve expanded the Elastic Stack audience from full ops teams to data engineers, security teams, and consultants. As an Elastic support rep, I’ve enjoyed interacting with more user backgrounds and with even wider use cases.

On the 14th of January 2021, Elasticsearch B.V. announced that future releases of Elasticsearch and Kibana would be released under a dual license SSPL (Server Side Public License). As a result of this change it is evident that the components that make up Elasticsearch and Kibana in version 7.11 (and onwards) of the ELK Stack will no longer be considered as open source based upon the Open Source Initiative's requirements for licensing.