Elastic Cloud Serverless: Another Azure region

With Elastic Cloud Serverless, you just create a project and start building. Elastic runs all the underlying infrastructure on your behalf. The platform comes pre-tuned for Search AI workloads with infrastructure optimized for vector search, hybrid retrieval, and high-throughput ingest out of the box. There are no clusters to size, no shards to balance, no upgrades to schedule, and no capacity to plan. Search and ingest scale independently on a decoupled architecture, so a spike on one side doesn't impact the other. The result: Teams move faster from idea to production for context-aware search, observability, security, and retrieval augmented generation (RAG) applications.

Serverless is relevant for any cloud-based Elastic use case. Below are a few examples where the operating model is especially impactful.

Retailers frequently experience massive, unpredictable traffic spikes during events like flash sales, forcing them to over-provision infrastructure and pay for unused compute during idle periods just to avoid downtime or poor customer experience. With Serverless, the decoupled architecture automatically scales compute up during traffic surges and scales it down when traffic normalizes. Customers only pay for the exact compute used, ensuring high-performance catalog retrieval.

ISVs and SaaS platforms face significant challenges balancing secure data isolation with cloud costs, as managing dedicated clusters for thousands of individual tenants creates a massive operational burden. Serverless provides a robust foundation for multitenancy by allowing organizations to rapidly provision discrete projects for new customers natively through the API. This isolates data efficiently without the need to manually manage node allocation or shard routing.

During a system outage, applications can generate a massive spike in error logs. In a coupled architecture, this sudden ingest spike may consume all cluster resources, causing the actual search queries used to find the root cause to slow down. Serverless independently separates indexing compute from search compute, meaning a massive spike in log ingestion will dynamically scale the indexing tier without any scale up for the search tier. This allows SREs to query their observability data in real time during a critical incident.

Elastic provides four serverless project types on Elastic Cloud. Follow these guides to get started with your serverless project:

• Elasticsearch Serverless: Build powerful, scalable search and analytics applications across structured data, logs, metrics, documents, and vectors as part of a broader Elastic Stack.

• Elasticsearch Vector Database: Build embedding-driven workloads such as semantic search, RAG, and AI-powered retrieval. Built-in models and vector-optimized defaults mean less configuration and faster time to production.

• Elastic Observability Serverless: Monitor your own platforms and services using powerful machine learning and analytics tools with your logs, metrics, traces, and APM data.

• Elastic Security Serverless: Detect, investigate, and respond to threats with SIEM, endpoint protection, and AI-powered analytics capabilities.

To try Elastic Cloud Serverless on Azure, visit Microsoft Marketplace and follow the steps below. You can either start a seven-day free trial or employ any of your existing credits. Your Elastic subscription will appear in your Microsoft Azure consolidated billing, and your spend counts toward your Azure cloud commitment. Or, you can sign up or log in to the Elastic Cloud console and follow the steps below. Either way, you can easily monitor and analyze your Elastic usage and costs right from the Elastic Cloud console. 

1. Create a Serverless project.

2. For Elasticsearch, Elastic Observability, Elastic Security, or Elasticsearch Vector Database projects, select Azure as the cloud provider and then choose your preferred Azure region. 

3. Click Create project, and your Elastic Cloud Serverless project will be provisioned.

If you have any questions or want to learn more, visit our documentation.

Elastic Cloud Serverless is a fully managed operating model that provides the most efficient way to build and scale search, observability, and security applications. When Elastic manages all your behind-the-scenes operations like version upgrades, sharding, and scaling, it allows your developers to focus entirely on their applications.

For more information, check out our roadmap or read why Vectorize.io and Docusign chose Elastic Cloud Serverless.

The release and timing of any features or functionality described in this post remain at Elastic's sole discretion. Any features or functionality not currently available may not be delivered on time or at all.

In this blog post, we may have used or referred to third party generative AI tools, which are owned and operated by their respective owners. Elastic does not have any control over the third party tools and we have no responsibility or liability for their content, operation or use, nor for any loss or damage that may arise from your use of such tools. Please exercise caution when using AI tools with personal, sensitive or confidential information. Any data you submit may be used for AI training or other purposes. There is no guarantee that information you provide will be kept secure or confidential. You should familiarize yourself with the privacy practices and terms of use of any generative AI tools prior to use. 

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