Elastic Extends Elasticsearch to Microsoft Azure

Elasticsearch Service on Elastic Cloud now supports deployments on Microsoft Azure, now providing managed service users with more cloud provider options.

Organizations that have standardized on Azure will now be able to enjoy the convenience of a fully managed Elasticsearch service, from the creators of Elasticsearch, on their preferred cloud platform — something that was not previously possible.

Elasticsearch Service users on Azure can now deploy fully hosted Elasticsearch and Kibana from the creators of the software all with the click of a button.

Existing Elasticsearch Service customers can launch deployments on Azure in their existing accounts, and new users can get started with a free 14-day trial of the Elasticsearch Service.

Bringing Elasticsearch Service to Azure is one of the ways Elastics is creating an even better experience for users of both the Elastic Stack and Microsoft products. The collaboration with Microsoft is important because it helps serve a community of joint users.

The Elasticsearch Service on Elastic Cloud is the official hosted Elasticsearch and Kibana service, created and supported by Elastic.

It offers features — like Elastic APM, SIEM, Maps, Canvas, machine learning and more — and tech support expertise you simply won’t find anywhere else.

Users can wield Elasticsearch and Kibana with confidence, knowing they always have the latest release and security patches and can upgrade their deployments with a single click and zero downtime.

“The developer and open source focus that both companies share have made this integration a very natural fit. Microsoft’s commitment to choice is evident in their developer experience on Microsoft Azure, and mirrors our own,” said Shay Banon, founder and CEO of Elastic.

The engineering teams at Elastic and Microsoft have collaborated on carefully benchmarking and selecting the optimal VMs to support a variety of Elastic use cases with different performance profiles when running Elasticsearch Service on Azure.

This effort has resulted in four deployment templates that optimize Elasticsearch Service on Azure such as:

  • High I/O: Perfect for search or general use cases, this template runs on top of L-series VMs that have local NVMe SSD optimized for high read/writes.
  • Hot/Warm: A powerful architecture perfect for logging and time series use cases, combining NVMe SSD for fast access and a 1:100 RAM:Disk ratio with HDD storage for longer cost-effective retention.
  • High CPU: Often used for scripting, calculations, ingest processing or other compute-intensive use cases, this template offers double the CPU.
  • High Memory: Offers search use cases a cost-effective option for lower data volumes.

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