What challenges did Elastic face before AI implementation?

Reimagine the Elasticsearch experience as data volumes grew and workloads became more demanding. Reduce operational complexity and improve software delivery performance (DORA).

What was the impact of the AI solution?

~40% YoY growth in Elastic Cloud on Google Cloud business. ~20% reduced operational expenses through automation. Estimated 25% reduction in compute-related carbon footprint. Improved software delivery performance using Google Cloud's DORA framework.

Source

GCP

Elastic re-architects Elasticsearch offering on Google Cloud with Gemini Enterprise Agent Platform integration

Use case typeSearch modernizationUpdated Jun 17, 2026

Elastic fundamentally re-architected its Elastic Cloud offering to Elastic Cloud Serverless on Google Cloud, transforming its ability to provide lightning-fast search and AI capabilities at scale while eliminating operational complexity for customers and significantly improving its own software delivery performance through DORA practices. The solution uses Google Compute Engine, Google Kubernetes Engine, and Cloud Storage, and integrates Elastic vector search with Gemini Enterprise Agent Platform UI and SDK for prompt grounding.

Organization: Elastic
Industry: Tech & Comms
Location: United States
Published: June 2026

Reported outcomes

−25%

compute-related carbon footprintSustainability & resources

40 % YoYElastic Cloud on Google Cloud business growth−20%operational expenses

Strategic outcomes

Cost efficiencyEliminated operational complexity for customersScale & capacityImproved software delivery performanceScale & capacityEnabled automatic scaling and high performance at any scaleEcosystem & partnershipsBecame the first ISV directly integrated into Gemini Enterprise Agent Platform UI and SDK

Catalog median for sustainability & resources deployments: −30% across 32 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 3 of 3

1Search modernization
2Cloud migration
3Infrastructure modernization

Reimagine the Elasticsearch experience as data volumes grew and workloads became more demanding.
Reduce operational complexity and improve software delivery performance (DORA).

Re-architected Elastic Cloud into Elastic Cloud Serverless on Google Cloud.
Built on Google Compute Engine, Google Kubernetes Engine, and Cloud Storage.
Integrated Elastic vector search with Gemini Enterprise Agent Platform via UI and SDK.

Technologies

Google Compute Engine Google Kubernetes Engine Cloud Storage Gemini Enterprise Agent Platform Elastic vector search

~40% YoY growth in Elastic Cloud on Google Cloud business.
~20% reduced operational expenses through automation.
Estimated 25% reduction in compute-related carbon footprint.
Improved software delivery performance using Google Cloud's DORA framework.

Architecture

Elastic Cloud Serverless is built on Google Compute Engine, Google Kubernetes Engine, and Cloud Storage. It uses Elastic vector search and is integrated with Gemini Enterprise Agent Platform through UI and SDK for grounding Gemini prompts.

Sources & evidence1

Groundedness: 5/5Type: Customer StoryPublished: Jun 17, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High

Primary source

AI-generated summary. Verify important details with the linked sources before relying on this case.

Explore related AI use cases

Customer evidence