As part of the Agentic Data Cloud launch at Google Cloud Next ‘26, we announced two AI-powered database agents to simplify database management. These include the Database Onboarding Agent for Day 0 operations — setup, configuration, and initial deployment — as well as the Database Observability Agent for Day 1 and 2 operations, including monitoring, troubleshooting, and ongoing maintenance.
These agents are always on, informed by Google’s years of experience, and integrated across Google surfaces such as Chat, CLI, the Google Cloud console, Managed Context Protocol (MCP) servers, and third-party tools — including your preferred integrated development environment (IDE), so you get help where and when you need it.
Traditionally, managing and creating databases has involved a combination of manual architecture planning, custom scripts, and distinct tools. Teams handle database provisioning, schema design, index configuration, and query tuning, alongside performance monitoring—often cycling through repeated testing and optimization cycles as application demands change. Although this method is functional, it demands substantial technical skill and continuous attention throughout the entire database lifecycle. For example, developers often fear making an update that may limit their ability to scale the system later. Similarly, when an application slows down, finding the exact query or resource constraint causing the issue can take hours of manual investigation and troubleshooting.
Intelligent AI-powered agents can simplify database lifecycle management by automating many of these tasks such as recommending the right database type for the workload, detecting anomalies, recommending the right configurations, optimizing queries, and providing actionable insights to improve operational efficiency. By embedding these capabilities directly into workflows where you need them, agents help organizations build, operate, and optimize databases more efficiently while reducing operational overhead.
Let’s take a closer look at these new database agents.
Database Observability Agent: From diagnosis to remediation
The Observability Agent empowers Site Reliability Engineers (SREs), DevOps pros, DBAs and developers to diagnose complex issues and remediate them using simple natural language prompts.
As your operations scale, identifying subtle issues like query hotspots or lock contention becomes an expensive burden. The database observability agent uses Google’s operational expertise and the reasoning capabilities of Gemini to solve these challenges. By automatically connecting telemetry across multiple sources including Database Insights, Cloud Monitoring, Cloud Logging, and Cloud Trace the agent provides a clear root cause analysis in minutes.
Beyond just identifying the “why,” the agent suggests recommended actions to fix the issues found, and can execute validated actions with your approval. For example, if it detects a bottleneck, it might suggest you “Enable connection pooling for Cloud SQL instance,” providing the rationale and expected impact before you commit to the change. Some capabilities include:
-
Fleet-level troubleshooting: The Observability Agent is integrated with Database Center so you can use Gemini Chat to ask complex fleet-wide questions like, “Which databases in my fleet consumed the most CPU in the last 7 days?” to receive a summarized analysis across your entire fleet.
-
In-product investigations: The agent correlates complex telemetry across Database telemetry, Cloud Monitoring, Cloud Logging, Cloud Trace, and multiple other data sources to pinpoint issues like latency spikes or lock contention. (In preview with select customers)
-
Validated remediations: Instead of just identifying problems, the agent provides crisp recommendations and can execute validated actions with your approval, such as adding indexes for a Cloud SQL instance. (In preview with select customers)
-
MCP tools: The Observability Agent derives insights with the help of tools such as system metrics, query metrics, fleet inventory, and issues, which are also available as MCP tools via the Database Insights MCP Server and Database Center MCP Server.
Integration that fits your workflow
You can access these Database Observability Agent capabilities directly within your existing database management processes. The agent powers several experiences, including:
-
Cloud Assist chat: Ask questions in natural language, for example, “What is the CPU utilization trend for my top Cloud SQL instances?” to get a summarized analysis complete with charts. Then, within the Chat window, you can start an investigation for any issues found,and get a root-cause analysis and remediations.
