Elastic, today announced the general availability of its Elastic Cloud Serverless, powered by a re-architectured Elasticsearch on an industry-first Search AI Lake optimized for real-time applications. This architecture combines vast storage with low-latency querying, along with all the strengths of Elasticsearch's AI and search capabilities.

“The need for scalability within search has never been more prevalent,” said Maribel Lopez, Founder & Principal Analyst of Lopez Research. “Serverless architecture supports the development of AI-powered search applications because it offers significant benefits in terms of scalability, cost-efficiency, and flexibility for modern software development. Companies need this type of architectural flexibility to navigate a rapidly changing AI landscape without having to make scale or performance trade-offs.”

Elastic Cloud Serverless is designed to handle high-volume, complex, and high-performance workloads—from retrieval augmented generation (RAG) to threat detection. By decoupling compute from storage and indexing from search, while utilizing cost-effective cloud-native object storage, the architecture scales seamlessly while preserving the rapid, low-latency querying and AI relevance capabilities of Elasticsearch.

“Ingesting data and querying the cluster showed nearly zero latency using Elastic Cloud Serverless,” said Madison Bahmer, Senior Principal Enterprise Architect at Two Six Technologies. “It is really fast and extremely easy to set up; we provisioned a new project without needing technical expertise.”

The fully managed Elastic Cloud Serverless provides both streamlined solutions and pricing. The new solution-specific pricing aligns costs with actual usage tailored to the different needs of security, observability, and search — offering greater flexibility and predictability.

By focusing on resource-based metrics like data ingestion, storage, and compute units, Elastic simplifies budget management and scalable solutions across applications. Additionally, new volume pricing for security and observability data, utilizing a tiered model, reduces costs per unit as data usage increases, facilitating the setup of new projects.

• Elasticsearch Serverless allows developers to rapidly build AI-powered search applications with the latest features, saving time managing infrastructure and scaling as needed.
• Elastic Observability Serverless provides a hassle-free experience without the need to manage the Elastic Stack or manually scale capacity.
• Elastic Security Serverless introduces a new cloud deployment option for security analytics and security information and event management (SIEM) use cases.

“What has stood out to our team with Elasticsearch Serverless is its ease of use,” said Marcel Makus, Development Manager at SAP Concur. “Elasticsearch Serverless is simple to use as a fully managed service, and it takes virtually no time to set up a new project. We’ve also been impressed with how well Elastic delivers on its autoscaling capabilities.”

“With our fully managed Elastic Cloud Serverless, we’re helping customers save more, scale fast, and search faster,” said Ken Exner, chief product officer at Elastic. “By removing operational overhead, developers can rapidly build AI-powered search applications without concern for latency or scalability. Our Search AI Lake inherently supports dense vectors and features crucial for applications like GenAI and RAG.”

Elastic Cloud Serverless is currently generally available on AWS. Support for Azure instances will be available in early 2025, providing seamless integration with Azure services. Support for Google Cloud instances will also be accessible in early 2025.

Information on solution-specific pricing is available here. For further details on starting with search, observability, and security, visit the blog or start your free trial now.

Elastic enables users to find real-time answers using their data, with solutions built on the Elastic Search AI Platform—used by many companies, including over 50% of the Fortune 500.