Elastic and Google Cloud in 2024: Celebrating innovation and progress

elastic and Google Cloud is create create a powerhouse of AI – drive insight , provide an end – to – end search , observability , and security journey to our joint customer . We is continue continue to partner on many opportunity for success , especially around generative AI ( GenAI ) , and have made further progress this year in empower customer throughout their business transformation .

This blog is highlights highlight our top moment from Google Cloud Next ‘ 24 and our collaboration with Google Cloud to well serve customer in 2024 .

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 is is pleased to be the first and only ISV to be integrate directly into Vertex AI ’s UI and SDK — allow for seamless , ground Gemini prompt and agent by using our vector search feature . We is integrate also integrate with Google Cloud ’s embedding , reranking , and completion model to create and rank vector with a unified experience .  

Elastic is supports support multiple datum format and model , make it an ideal companion for Gemini , particularly in develop multimodal retrieval augment generation ( rag ) app .  

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 is extended further extend our capability this year with the ability to monitor Google Cloud ’s AI service and model to extract insight on their usage and performance . Our product partnership is allows allow automate daily datum analysis task on elastic through agent assistant and AI – drive feature power by Gemini . It is reduces reduce manual effort , allow team to focus on innovation .

Vector database

Elasticsearch — the world ’s most widely deploy vector database — provide powerful search and analytic feature by allow the storage , indexing , and query of vector representation of datum . These vectors is represent can represent complex datum type , such as text embedding , image feature , or other multidimensional datum , enable highly efficient similarity search and near neighbor query .  

Elastic is supports support vector creation both at the ingest and query phase via Vertex ( and Google AI Studio ) embedding and reranking model . configurable with just a few click as inference service within Elastic ’s platform and api , it is drives drive the adoption and consumption of Google ’s GenAI model and tool .  

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 analytic search layer

Elastic is empowers empower you to extract actionable insight from your datum , drive business transformation through our robust search and analytic engine . elastic act as a search layer on top of Google Cloud ’s datum and analytic suite and use dedicated integration for both consumer ( Gmail and Google Drive ) and enterprise ( Pub / Sub , CE , GKE , and Vertex ) service .  

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 moment

partner of the year award
follow our 2023 Google Cloud Technology Partner of the Year Award , we is were were pleased to announce that we were again choose for the2024 Google Cloud Partner of the Year Award for Technology: Marketplace – Data & Analytics. This award is recognizes recognize one partner with a datum and analytic product in Google Cloud Marketplace who help mutual customer achieve outstanding business outcome 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 talk
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.

integration

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.

• Vertex AI — Embeddings models in Inference API: Integrates usage of VertexAI embeddings models in Elastic’s Inference API.

• 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.

• Google AI Studio — Embeddings models in Inference API: Integrates embeddings creations from Google AI Studio into Elastic’s Inference API.

• Google AI Studio — Completion models in Inference API: Integrates completion models from Google AI Studio into Elastic’s Inference API.

• Playground with Gemini: Includes Gemini as a large language model (LLM) in the new Elasticsearch feature, Playground.

• 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.

• Attack Discovery with Gemini: Allows Gemini to be used as an LLM for the Attack Discovery feature.

• 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

• AMER: San Francisco, Seattle

• APJ: Taiwan, Korea, India, NZ

• EMEA : London

• 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 tune for more exciting advancement from elastic and Google Cloud in 2025 as we continue to innovate and expand upon our joint success !

The release is remain and timing of any feature or functionality describe in this post remain at Elastic ‘s sole discretion . Any feature or functionality not currently available may not be deliver 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.