Data and AI releases

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Provisioned Throughput: Multiple pending new orders GA

Generally availableVerified

The ability to submit multiple pending orders is generally available. you can submit up to seven Google model orders for the same model and region. See Multiple pending orders .

RegionsPerformance

Read on docs.cloud.google.com

Also shipped Jul 1, 2026Google Cloud in July 2026 →

Veeva Vault connector (Beta)

The Veeva Vault connector is now available in Lakeflow Connect in Beta . Workspace admins can control access to this feature from the Previews page. The connector uses Veeva's Direct Data API to ingest all standard objects, custom objects, system tables, and audit trail tables from your Vault instance into Databricks.

Beta
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MySQL integrated CDC pipeline is now in Beta

The integrated CDC pipeline for MySQL is now in Beta . An integrated CDC pipeline ingests change data from MySQL into Databricks using a single pipeline, combining extraction and application into one pipeline update. Unlike the standard gateway-based architecture, an integrated CDC pipeline requires no separate ingestion gateway.

Beta
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More from Gemini Enterprise Agent PlatformEvery Gemini Enterprise Agent Platform release →

AlphaGenome released for Gemini Enterprise Agent Platform

AlphaGenome, Google DeepMind's state-of-the-art genomics foundation model, is now available for deployment and use with Gemini Enterprise Agent Platform. Designed to decipher the functional regulatory code of the human genome, AlphaGenome analyzes large-scale DNA sequences at single-base resolution to predict how genetic variations affect molecular and...

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Grok 4.1 models deprecation

The Grok 4.1 model family (including xai/grok-4.1-fast-reasoning and xai/grok-4.1-fast-non-reasoning ) on the Gemini Enterprise Agent Platform is deprecated and will be shut down on August 20, 2026. After this date, Google Agent Platform Model as a Service (MaaS) will no longer serve these models.

Deprecation
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Memory Bank support for Gemini Embedding 2

Memory Bank supports the gemini-embedding-2 model for similarity search configurations. When you configure gemini-embedding-2 as the embedding model, you must use one of the global , us , or eu endpoints in the model's resource name (for example, projects/{project}/locations/us/publishers/google/models/gemini-embedding-2 ).

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