Free Practice Questions for Google Cloud Professional Agentic Architect Certification

Configuring state-based workflows (pages, transition routes, and event handlers) using Gemini Enterprise tools (e.g., Gemini Enterprise Agent Designer and Customer Experience Agent Studio [CX Agent Studio])

Creating system instructions and in-console prompt templates (e.g., few-shot and chain-of-thought) to guide agent behavior (e.g., Agent Designer and CX Agent Studio)

Configuring agents to securely connect and query enterprise proprietary data sources (e.g., Gemini Enterprise and Agent Search)

Ingesting and processing unstructured multimodal data (e.g., videos, audio, and images) into the agentic workflow

Configuring coding agents with Model Context Protocol (MCP) servers, custom skills, and access to tools (e.g., Antigravity and Claude Code on Google Cloud)

Using coding agents in secure sandboxes (e.g., Google Kubernetes Engine [GKE], Cloud Workstations, and Antigravity)

Using coding agents to refactor source code, optimize execution runtimes, and patch application-layer vulnerabilities

Creating skills, plugins, extensions hooks, rules, and subagents using Antigravity

Augmenting Antigravity with Agents CLI to build, scale, govern, and optimize deployed agents

Selecting and configuring the appropriate language model (e.g., large language model [LLM] vs. small language model [SLM], self-hosted vs. software as a service [SaaS], and open-source software [OSS] vs. proprietary LLM) considering cost, security, and agent architecture

Building custom agents using open-source libraries (e.g., Agent Development Kit [ADK])

Configuring sessions and memory (e.g., Agent Platform Memory Bank and managed sessions)

Configuring skills using Agents CLI (e.g., plugins and agent vs. human mode)

Designing, configuring, and managing retrieval-augmented generation (RAG) pipelines and vector retrieval systems (e.g., embedding models, similarity scoring, and reranking) using appropriate services such as vector databases (e.g., Vector Search and Agent Retrieval)

Configuring agent permissions (e.g., Agent Identity)

Using Google Cloud tools (e.g., Agent Registry, Google Cloud MCP Servers) to configure prebuilt and custom capabilities (e.g., custom integration layers for managed databases, API integrations, and MCP server that connects agents to third-party SaaS tools and remote servers)

Orchestrating agents using agentic protocols (e.g., MCP and Agent2Agent [A2A])

Selecting and coordinating multiagent handoffs and workflows (e.g., parallel agents, sequential agents, and graph workflow) using Google Cloud tools (e.g., Agent Identity, Agent Registry, Agent Runtime, and agent policies)

Creating test sets for agent evaluation (e.g., golden data, prompts, and edge cases)

Creating continuous evaluation pipelines to assess an agent’s tool execution based on established success criteria

Determining the appropriate evaluation framework and tooling (e.g., ADK evaluation tooling (evalset), Agent Platform Gen AI evaluation service, and custom autoraters)

Evaluating an agentic system against a golden dataset to assess agent response and retrieval quality (e.g., using ADK)

Selecting optimal deployment runtime based on the use case, requirements, and cost (e.g., Agent Runtime, Cloud Run, and GKE)

Troubleshooting agent issues (e.g., drift, tool invocation latency, agent reasoning loops, and system failures)

Monitoring and optimizing agents for performance, reliability, and cost (e.g., identify logic errors, latency bottlenecks, and hallucinations)

Implementing authentication and secure tool execution (e.g., agent-to-tool API calls using OAuth 2.0)

Configuring principal access boundary (PAB) policies using Agent Identity

Configuring Agent Gateway to monitor traffic and track agents

Designing and configuring agentic governance and policy enforcement (e.g., Agent Registry and Model Armor)

Designing appropriate safety frameworks and guardrails (e.g., Agent Gateway, Model Armor, and human-in-the-loop [HITL])

Configuring secure access to data and identity propagation (e.g., Agent Gateway and Agent Registry)