AlloyDB for PostgreSQL
Feature
Context sets (previously known as data agents) enable you to interact with the data in your database using conversational language and are used by tools like QueryData to build conversation agents. For more information, see Context sets overview. This feature is available in (Preview).
The preview release increases the accuracy of SQL generation with value search queries which match values and their context within a database. Value search queries trigger automatically. Context sets also add support for Parameterized secure views (PSVs) to help secure applications that use natural language queries generated using QueryData.
Apigee API hub
Feature
Agent Registry integration support for MCP metadata (Preview)
API hub now includes a managed integration with Agent Registry to automatically synchronize Model Context Protocol (MCP) servers and tools metadata. This feature enables AI agents to discover and interact with the APIs registered in your hub without manual configuration.
This feature is in Public Preview. For more information, see Manage Agent Registry integration.
Apigee X
Change
On April 6th, 2026, we released an updated version of Apigee.
This change introduces the new apigee.coreServiceAgent IAM role for
Apigee. Effective immediately, use apigee.coreServiceAgent instead of the
apigee.serviceAgent role.
For information on the new role, see
apigee.coreServiceAgent.
Fixed
Correction to April 2, 2026 release note: Deployment disruption for Apigee Drupal Portal via Google Cloud Marketplace
For the deployment disruption announced on April 2, the announcement noted that deployment and management functionality using Google Cloud Deployment Manager would definitely be unavailable during the transition. This statement is incorrect. The functionality might be unavailable.
See the Known issue for more information.
BigQuery
Feature
You can now use a custom organization policy to allow or deny specific operations on these BigQuery resources: tables, data policies, and row access policies. This feature is in preview.
Feature
You can now use the
AI.AGG function
to semantically aggregate unstructured input data based on natural language
instructions. This feature is in
Preview.
Cloud Logging
Libraries
Go
{: track-name=’go’} #### v1.14.0 (2026-04-02)Cloud SQL for MySQL
Feature
Context sets (previously known as data agents) enable you to interact with the data in your database using conversational language and are used by tools like QueryData to build conversation agents. For more information, see Context sets overview. This feature is available in (Preview).
The preview release increases the accuracy of SQL generation with value search queries which match values and their context within a database. Value search queries trigger automatically.
Cloud SQL for PostgreSQL
Feature
Context sets (previously known as data agents) enable you to interact with the data in your database using conversational language and are used by tools like QueryData to build conversation agents. For more information, see Context sets overview. This feature is available in (Preview).
The preview release increases the accuracy of SQL generation with value search queries which match values and their context within a database. Value search queries trigger automatically.
Cloud SQL for SQL Server
Feature
Cloud SQL for SQL Server now supports SQL Server 2025 (GA):
- SQL Server 2025 Standard
- SQL Server 2025 Enterprise
- SQL Server 2025 Express
For more information, see Database versions and version policies and Choose a machine series.
Feature
Cloud SQL for SQL Server integration with Microsoft Entra ID (GA) provides centralized identity and access management (IAM) for your databases using your existing Microsoft Entra ID tenant.
Gemini Cloud Assist
Deprecated
Custom IAM roles permission update for Gemini Cloud Assist
On April 8, 2026, Gemini Cloud Assist is replacing the
cloudaicompanion.instances.completeTask IAM permission with
geminicloudassist.agents.invoke. Updates to standard IAM roles will be done
automatically, but if you have access to Gemini Cloud Assist through a custom
IAM role, you must update the role before April 8, 2026 to ensure continued
access. For more information, see the
deprecated IAM permissions
page.
Generative AI on Vertex AI
Feature
Metadata search for RAG Engine
Use schema-based metadata search in Vertex AI RAG Engine. You can define a metadata schema for a corpus, attach metadata to files within that corpus, and use this metadata to filter contexts during retrieval. For more information, see Filter with metadata search.
Google SecOps
Deprecated
v1 Cloud Storage Feed Types (GCS, S3, SQS, Azure)
The v1 feed types for GOOGLE_CLOUD_STORAGE, AMAZON_S3, AMAZON_SQS, and AZURE_BLOBSTORE are deprecated and will be discontinued on March 15, 2027. The new v2 feed types uses the Google Cloud Storage Transfer Service (STS) to provide improved performance, scalability, and reliability.
To ensure continued ingestion, transition your feeds before the March 15, 2027 shutdown date:
- Google SecOps will automatically migrate your feeds using v1 feed types to v2 in waves starting from April 6, 2026. To facilitate this, some feeds may require additional IP allowlist or service account permission updates. You can also self-migrate by replacing your existing data feeds with new feeds using v2 feed types.
You can also self-migrate by creating new feeds using v2 feed types to substitute your existing feeds using v1 feed types by following the steps documented in our feed configuration guides before March 15, 2027.
Key Dates:
- April 6, 2026: Transition begins; auto-migration available.
- September 15, 2026: Support for v1 feeds is discontinued.
- March 15, 2027: v1 feeds reach End of Life (EOL) and will stop returning data.
For more information, see Feature deprecations.
Google SecOps SIEM
Deprecated
v1 Cloud Storage Feed Types (GCS, S3, SQS, Azure)
The v1 feed types for GOOGLE_CLOUD_STORAGE, AMAZON_S3, AMAZON_SQS, and AZURE_BLOBSTORE are deprecated and will be discontinued on March 15, 2027. The new v2 feed types uses the Google Cloud Storage Transfer Service (STS) to provide improved performance, scalability, and reliability.
To ensure continued ingestion, transition your feeds before the March 15, 2027 shutdown date:
- Google SecOps will automatically migrate your feeds using v1 feed types to v2 in waves starting from April 6, 2026. To facilitate this, some feeds may require additional IP allowlist or service account permission updates. You can also self-migrate by replacing your existing data feeds with new feeds using v2 feed types.
You can also self-migrate by creating new feeds using v2 feed types to substitute your existing feeds using v1 feed types by following the steps documented in our feed configuration guides before March 15, 2027.
Key Dates:
- April 6, 2026: Transition begins; auto-migration available.
- September 15, 2026: Support for v1 feeds is discontinued.
- March 15, 2027: v1 feeds reach End of Life (EOL) and will stop returning data.
For more information, see Feature deprecations.
Memorystore for Redis
Feature
You can use the Memorystore for Redis remote MCP server. This server lets you connect to Memorystore for Redis instances from LLMs, AI applications, and AI-enabled development platforms. This feature is available in Preview.
Memorystore for Valkey
Feature
You can use the Memorystore for Valkey remote MCP server. This server lets you connect to Memorystore for Valkey instances from LLMs, AI applications, and AI-enabled development platforms. This feature is available in Preview.
Pub/Sub
Feature
Pub/Sub now offers the AI Inference Single Method Transform (SMT). This SMT lets you get inferences on Pub/Sub messages from Vertex AI models. The model’s inferences are added to each message, making them available for downstream processing along with the original message data.
The change is being rolled out in a phased manner over the rest of the week. For more information, see AI Inference SMT. This feature is generally available.
Spanner
Feature
Context sets (previously known as data agents) enable you to interact with the data in your database using conversational language and are used by tools like QueryData to build conversation agents. For more information, see Context sets overview. This feature is available in (Preview).
The preview release increases the accuracy of SQL generation with value search queries which match values and their context within a database. Value search queries trigger automatically.
Source: Google Cloud Platform
