Elastic and Google Cloud create a powerhouse of AI-driven insights, providing an end-to-end search, observability, and security journey to our joint customers. We continue to partner on many opportunities for success, especially around generative AI (GenAI), and have made further progress this year in empowering customers throughout their business transformation.
This blog highlights our top moments from Google Cloud Next ‘24 and our collaboration with Google Cloud to better serve customers in 2024.
Table of Contents
Delivering synergistic results
Elastic and Google Cloud have partnered to create production-ready GenAI solutions for you. Read further to see what we’ve been working on this year to help you expand your capabilities as an organization.
Elasticsearch and Gemini
Elastic is pleased to be the first and only ISV to be integrated directly into Vertex AI’s UI and SDK — allowing for seamless, grounded Gemini prompts and agents by using our vector search features. We also integrate with Google Cloud’s embedding, reranking, and completion models to create and rank vectors with a unified experience.
Elastic supports multiple data formats and models, making it an ideal companion for Gemini, particularly in developing multimodal retrieval augmented generation (RAG) apps.
We use Gemini not only for building AI apps but also to empower IT operations, such as in the Elastic AI Assistants, Attack Discovery, and Automatic Import, reducing daily effort for security analysts and SREs.
We further extended our capabilities this year with the ability to monitor Google Cloud’s AI services and models to extract insights on their usage and performance. Our product partnership allows automating daily data analysis tasks on Elastic through agent assistants and AI-driven features powered by Gemini. It reduces manual efforts, allowing teams to focus on innovation.
Vector database
Elasticsearch — the world’s most widely deployed vector database — provides powerful search and analytics features by allowing the storage, indexing, and querying of vector representations of data. These vectors can represent complex data types, such as text embeddings, image features, or other multidimensional data, enabling highly efficient similarity searches and nearest neighbor queries.
Elastic supports vector creation both at the ingest and query phases via Vertex (and Google AI Studio) embeddings and reranking models. Configurable with just a few clicks as inference services within Elastic’s platform and APIs, it drives the adoption and consumption of Google’s GenAI models and tools.
Elastic is the perfect vector database for multiple data formats and multimodal interaction, making it the best companion of Gemini’s various interactive experiences. Gemini is also integrated in Elasticsearch’s Playground feature, allowing the prototyping, testing, and deploying of RAG-based GenAI applications on top of Elastic’s vector database.
Real-time analytics search layer
Elastic empowers you to extract actionable insights from your data, driving business transformation through our robust search and analytics engine. Elastic acts as a search layer on top of Google Cloud’s data and analytics suite and uses dedicated integrations for both consumer (Gmail and Google Drive) and enterprise (Pub/Sub, CE, GKE, and Vertex) services.
In 2024, customers used our native Dataflow templates. The ease-of-use benefits are a significant driver in the adoption of Elastic on Google Cloud. With BigQuery, we see our joint customers adopting Elastic as a real-time analytics speed layer on top of their data lake. With Pub/Sub integration, we enable the collection of events, logs, and metrics to provide full visibility of the Google Cloud landscape.
Google Cloud Next ‘24 highlights
Key moments
Partner of the year award
Following our 2023 Google Cloud Technology Partner of the Year Award, we were pleased to announce that we were again chosen for the 2024 Google Cloud Partner of the Year Award for Technology: Marketplace – Data & Analytics. This award recognizes one partner with a data and analytics product in Google Cloud Marketplace who helped mutual customers achieve outstanding business outcomes with Google Cloud.
The fact that Elastic has won a Google Cloud Partner of the Year Award four times is a testament to our strategic partnership and technological collaboration.
Cloud talk
Kathleen Walker, senior director of Search product marketing, took the stage for a Cloud Talk on better AI decision-making with Elastic on Google Cloud.
Lightning talks
Our booth was packed for more than 20 lightning talks with Elastic experts presenting on topics like the Elastic AI Assistant, Elasticsearch Relevance Engine (ESRE), RAG, Elastic and Vertex AI, and more.
Kathleen Walker also shared more insights on GenAI during an interview with theCUBE.
Be sure to visit the Elastic booth at Google Cloud NEXT ’25!
Building momentum together: 2024 recap
Our partnership momentum with Google Cloud has continued to grow substantially throughout 2024. Below is a recap of our joint efforts over the past year to help you address your evolving use cases and derive the most value possible from Elastic on Google Cloud.
Integrations
As we mentioned at the beginning of this blog, Elastic and Google Cloud have collaborated on a number of AI integrations that you can reference below. All of these are intended to help with your most prevalent GenAI challenges.
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Vertex AI — Embeddings models in Inference API: Integrates usage of VertexAI embeddings models in Elastic’s Inference API.
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Vertex AI Rerank in Inference API: Integrates with Vertex AI Agent Builder — rerank feature — and callable from Inference API endpoint to rerank documents for RAG.
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Google AI Studio — Embeddings models in Inference API: Integrates embeddings creations from Google AI Studio into Elastic’s Inference API.
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Google AI Studio — Completion models in Inference API: Integrates completion models from Google AI Studio into Elastic’s Inference API.
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Playground with Gemini: Includes Gemini as a large language model (LLM) in the new Elasticsearch feature, Playground.
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Elastic AI Assistant for Security and Observability with Gemini: Allows Gemini to be used as an LLM for the Elastic AI Assistant for Observability. Gemini offers a much bigger context tokens amount, which is perfect for investigating a high number of alerts combined.
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Attack Discovery with Gemini: Allows Gemini to be used as an LLM for the Attack Discovery feature.
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Vertex AI observability monitoring: Monitors Vertex AI built-in and custom-deployed models usage like token usage, response time, resource consumption, and audit logs.
- Vertex AI — Elasticsearch for built-in grounding: Gemini can natively be grounded via Google Cloud console, APIs, and Vertex SDK with Elasticsearch.
Blogs
The blogs below provide deeper information and tutorials on how to best use Elastic solutions.
Key joint GenAI in-person events and roadshows
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AMER: San Francisco, Seattle
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APJ: Taiwan, Korea, India, NZ
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EMEA: London
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LATAM: Chile, Brazil, Colombia
Customer case studies
Helping our customers address challenges and realize opportunities using Elastic solutions on Google Cloud fuels our strategic collaboration. Below are a handful of these examples over the past year.
Looking ahead
Our partnership with Google Cloud is founded on a shared vision of empowering organizations to maximize the potential of their data. As we look into the future, we are excited to innovate and deliver solutions that help customers take advantage of the cloud and GenAI capabilities.
Stay tuned for more exciting advancements from Elastic and Google Cloud in 2025 as we continue to innovate and expand upon our joint successes!
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.
Elastic, Elasticsearch, ESRE, Elasticsearch Relevance Engine and associated marks are trademarks, logos or registered trademarks of Elasticsearch N.V. in the United States and other countries. All other company and product names are trademarks, logos or registered trademarks of their respective owners.
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