Build Flexible Agents with ADK and Low-Code Options

Use Agent Development Kit (ADK) to construct agents in Python, TypeScript, Java, or Go, supporting sequential, multi-agent, or deterministic graph-based designs. ADK integrates any model like Gemini, Anthropic's Claude, or Llama open-weight models for text or multimodal tasks. Connect external tools via Model Context Protocol (MCP) or other agents through Agent-to-Agent (A2A) protocol, enabling microservice-like multi-agent systems compatible with LangGraph, Curi, or AG2. Start via adk.dev by selecting language, patterns, and models for instant code generation. For agentic coding, Agent CLI automates ADK agent creation, evaluation, and deployment. Agent Studio offers visual low-code flow mapping with real-time testing and export to ADK code for Cloud Run or GKE. Leverage Agent Garden's pre-built templates for enterprise patterns like financial analysis to accelerate development.

Deploy and Scale Production-Ready Agents

Deploy to Agent Runtime, a PaaS with <1-second cold starts and support for agents reasoning up to 7 days, framework-agnostic for ADK, LangChain, or custom stacks. Manage user interactions via Agent Sessions, auto-handled in ADK with custom IDs linking to customer records. Enable long-term recall with Memory Bank to avoid repetitive user inputs. For code execution or UI interactions on legacy apps, use Agent Sandbox for isolated environments. This setup ensures agents handle high-scale, multi-user production loads without manual oversight.

Govern Agents for Enterprise Security

Assign each Agent Runtime-deployed agent an IAM principal via Agent Identity for action traceability. Auto-catalog all agents, MCP servers (including first-party, Apogee, and third-party), and A2A agents in Agent Registry. Control access with Agent Policies on agents, tools, and registry, plus Model Armor for prompt injection blocking and PII sanitization. Route all traffic through Agent Gateway for policy enforcement and auditing. Detect anomalies using LLM-as-judge on reasoning patterns, viewable in the Agent Security Dashboard. This governance stack provides trust for autonomous business tasks.

Observe, Evaluate, and Optimize Agent Performance

Gain visibility with Agent Observability's dashboards and traces into decisions, tool calls, and failures; use Agent Topology for graph views of multi-agent systems. Test non-deterministic behavior via Agent Evaluation for multi-step interactions and Agent Simulation to auto-generate thousands of edge cases pre-production. Automate improvements with Agent Optimizer, refining instructions from failure signals in a feedback loop. These tools address AI's complexity, ensuring consistent quality at scale without manual test case creation.