Unifying storage for your data analytics workloads doesn‘t have to be hard. See how Google Cloud Storage brings your data closer to compute and meets your applications where they are, all while achieving exabyte scale, strong consistency, and lower costs. You'll get new product announcements and see enterprise customers present real-world solutions using Cloud Storage with BigQuery, Hadoop, Spark, Kafka, and more.

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As generative AI applications mature, retrieval-augmented generation (RAG) has become popular for improving large language model-based apps. We expect teams to move beyond basic RAG to autonomous agents and generative loops. We'll set up a Weaviate vector database on Google Kubernetes Engine (GKE) and Gemini to showcase generative feedback loops.

After this session, a Google Cloud GKE user should be able to: - Deploy Weaviate open source on GKE - Set up a pipeline to ingest data from the Cloud Storage bucket - Query, RAG, and enhance the responses

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This session is for AI/ML and data practitioners who want to build AI/ML data pipelines at scale and select the right combination of block, file, and object storage solution for your use case. Learn how to optimize all your AI/ML workloads like data preparation, training, tuning, inference, and serving with the best storage solution and easily integrate them into your Compute Engine, Google Kubernetes Engine, or Vertex workflows. We’ll also dive into how to optimize analytics workloads with Cloud Storage and Anywhere Cache.

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Attend this session for an overview of our storage solutions and how they are optimized for a variety of workloads. We’ll share storage best practices for AI, Google Kubernetes Engine, and VMs, and customer storage and infrastructure cost optimization. You’ll gain insight into new features that deliver more performant and available apps to your business. We’ll also share our storage vision providing you the ability to plan for future application workloads.

-Industry’s first unified cloud storage optimized for AI and analytics workloads; -Intelligent storage powered by AI; -Built for mission-critical, high-availability data protection; -Migrating to cloud storage and Google Cloud at scale at low cost

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Learn how Google Cloud’s backup and storage services secure and protect your data from a variety of threats, such as ransomware, outages, and user errors. Our backup services protect VMs, databases (such as SAP HANA), and Google Kubernetes Engine environments. Expand threat detection capabilities by alerting on suspicious activities around backup through Security Command Center. We’ll also dive into Cloud Storage and our industry-leading turbo replication for dual-region deployments, soft delete, versioning, and more to protect your data.

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Introduces new GCS management features and shares best practices to solve customers' goals of cost optimization, security and governance at billions of objects scale. Demos and details of Storage Insights Datasets, generating insights with Gemini and new data movement feature. Plus, learn directly from Recursion Pharma about their real-world success managing Cloud Storage at scale.

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Migrating high performance computing (HPC) workloads to the cloud presents unique challenges, as traditional on-premises infrastructure often clashes with cloud architectures, leading to operational and cost inefficiencies. Embracing core technologies like Google Kubernetes Engine and Google Cloud Storage offers a compelling solution to these hurdles. In this session, we explore PGS the transition of our entire HPC system to Google Cloud. This move allows us to run workloads five times larger than previously possible while reducing turnaround time by a factor of two.

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