Elastic, the company behind Elasticsearch and the Elastic Stack, announced the launch of Elasticsearch Service on Azure will be welcome news for many of their managed service users who want more cloud provider options and value Azure’s powerful global reach.
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.
Deepening a successful Elastic and Microsoft collaboration
Bringing the Elasticsearch Service to Azure is one of the ways to create an even better experience for users of both the Elastic Stack and Microsoft products. Many of the users already deploy Elasticsearch on Azure, often utilizing the ARM template for the Elastic Stack that was launched in collaboration several years ago.
Elastic supports Microsoft technologies in other areas, such as their .NET clients, Winlogbeat for WindowsOS event collection, Azure Active Directory integration to secure Elasticsearch clusters and .NET support in their Elastic APM product. The collaboration with Microsoft is important because it helps them serve their community of joint users.
Elasticsearch with Azure, and all the features you love
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.
And now, all these benefits are available to Azure customers.
“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.
Scott Guthrie, EVP of Cloud + AI, Microsoft Corp. said, “As customers adopt cloud services, having a solution for their most important needs such as search, logging, observability, and security of their critical applications, will be a key advantage. The focus on developer choice and managed services that both Microsoft and Elastic share benefit our mutual customers.”
The public beta is accessible to all Elasticsearch Service customers and trial users delivered from two Azure regions — East US 2 in Virginia and West Europe in the Netherlands — and includes the full set of Elasticsearch Service features.
During the beta period, Elastic technical support is available. Later in 2019, Elastic intends to move the service to generally available and add mission-critical support service levels.
As part of the beta launch, Elastic offers a promotional period where data transfer (in/out/between nodes) and snapshot storage (total storage size and requests) are free.
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:
- 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.