Elastic announced the general availability of its Elastic Cloud Serverless powered by a re-architectured Elastic search that is built on an industry-first Search AI Lake optimised for real-time applications. It combines vast storage with low-latency querying and all of 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 engineered to tackle high-volume, complex, and high-performance workloads—from retrieval augmented generation (RAG) to threat detection. By decoupling compute from storage, indexing from search and using cost-effective cloud-native object storage, the architecture scales seamlessly while retaining the rapid, low-latency querying performance 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, Two Six Technologies. “It is really fast and extremely easy to set up; we provisioned a new project without needing technical expertise.”
Streamlined solutions that start fast and search faster
The fully managed Elastic Cloud Serverless offers 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 makes it easier for customers to manage budgets and scale as needed — enabling more control to manage workloads across different applications.
In addition, new volume pricing for security and observability data—using a tiered pricing model—simplifies scaling by reducing costs per unit as data usage increases, making it easy for customers to set up new projects for search, observability and security.
- Elasticsearch Serverless lets developers rapidly build AI-powered search applications with the latest features, save time managing infrastructure, and scale up or down to meet their needs.
- Elastic Observability Serverless enables a hassle-free experience without the overhead of managing the Elastic Stack or manually scaling capacity.
- Elastic Security Serverless provides security analysts with a new cloud deployment option for their security analytics and 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. “Elastic search 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 such as hybrid search, faceted search, and relevance ranking, which are especially vital for applications like GenAI and RAG.”
