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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Domain 2: Using Coding Agents for Application Development | 17% | - Integrate coding agents with development workflows - Manage MCP servers and custom skills - Use coding agents in secure sandboxed environments - Select and configure coding agents |
| Topic 2: Domain 3: Developing Custom Agents | 33% | - Design agent architectures and model selection - Implement RAG pipelines and vector retrieval - Integrate enterprise data sources and APIs - Configure sessions, memory, and state management - Build agents with the Agent Development Kit (ADK) - Orchestrate multi-agent workflows using MCP and A2A - Implement Agent Identity and permissions |
| Topic 3: Domain 4: Evaluating and Deploying Agentic Workflows | 22% | - Implement continuous evaluation pipelines - Monitor, troubleshoot, and optimize agents in production - Design evaluation datasets and methodologies - Select deployment targets: Agent Runtime, Cloud Run, GKE - Deploy and scale agentic workflows |
| Topic 4: Domain 5: Securing and Governing Agentic Workflows | 15% | - Apply governance policies and human-in-the-loop controls - Protect against prompt injection and data leakage - Monitor audit logs and compliance - Use Model Armor, Agent Gateway, and Agent Registry - Implement authentication and authorization for agents |
| Topic 5: Domain 1: Building Agents Using Low-Code Tools | 13% | - Integrate data sources and knowledge bases - Design and configure agents using low-code platforms - Test and iterate low-code agents - Configure agent triggers, workflows, and responses |
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NEW QUESTION # 62
You are troubleshooting a hierarchical multiagent architecture built with Agent Development Kit (ADK), in which a primary orchestrator delegates complex search tasks to specialized subagents. Execution traces show that subagents append their full tool execution histories to the orchestrator's context window across multiturn exchanges, causing rapid context window bloat, agent drift, and severe tool invocation latency. You need to isolate subagent execution history and prevent context pollution in the orchestrator.
What should you do?
Answer: C
Explanation:
Hierarchical multiagent systems frequently suffer from context pollution when subagents append raw, voluminous tool execution histories and intermediate scratchpad traces directly into the parent orchestrator's context window. Over multiple turns, this leads to rapid token bloat, increased inference latency, and cognitive drift in the orchestrator. To solve this in Agent Development Kit (ADK), specialized subagents should be wrapped using agent tool encapsulation (AgentTool), which executes the subagent within an isolated, nested sub-session. By configuring the subagent's language model settings with include_contents='none', the runtime prevents prior conversational history and internal tool execution events from being reflected into subsequent reasoning loops. Essential intermediate findings, extracted parameters, or final task outputs are selectively written to the shared session state rather than accumulating unpruned messages in the active prompt context. Compacting logs via Cloud Storage or adjusting tracing sampling rates only affects telemetry, failing to reduce the orchestrator's in-memory prompt size.
Reference: Developing custom agents - Context boundary management, AgentTool encapsulation, and session state persistence.
NEW QUESTION # 63
You are designing authentication controls for an Agent Development Kit (ADK) agent on Gemini Enterprise Agent Platform. The agent queries internal BigQuery datasets and will soon expand to call external third-party APIs. You want to enable secure, granular outbound tool authentication without managing custom credential vaults or hardcoding secrets in backend code.
What should you do?
Answer: A
Explanation:
Secure outbound tool integration in modern agent platforms requires identity-first authentication and managed credential brokering. The Gemini Enterprise Agent Platform utilizes SPIFFE-based (Secure Production Identity Framework for Everyone) agent identities, providing cryptographic workload identities directly to ADK agents. For native Google Cloud resources like BigQuery, architects grant required IAM permissions directly to the agent's SPIFFE-based identity principal, establishing access without managing long-lived service account keys. For external third-party APIs, Agent Identity auth manager acts as a managed credential vault and token broker. External API keys and OAuth tokens are registered within the auth manager; during tool execution, ADK coordinates with the auth manager to automatically fetch valid tokens and inject authentication headers into outbound requests. This eliminates custom vault management code, prevents hardcoded secrets, and maintains a secure identity boundary across both first-party and third-party tools.
Reference: Securing and governing agentic workflows - SPIFFE agent identities, Agent Identity auth manager, and automated token injection.
NEW QUESTION # 64
You are configuring enterprise agents that must dynamically discover and invoke capabilities across managed databases, third-party SaaS tools, and Google Cloud services. Your architecture hosts custom MCP servers on Cloud Run alongside pre-built Google Cloud MCP servers. Your operations team requires a centralized catalog to govern access controls, register JSON tool specifications, and manage IAM identities across all remote HTTP transport endpoints.
You need to maximize operational efficiency and maintain strict governance by establishing a single point of discovery and access control for both native and custom agent capabilities.
What should you do?
Answer: D
Explanation:
Heterogeneous agent environments combining first-party Google Cloud capabilities with custom business services require a centralized control plane for tool governance and catalog discovery. Agent Registry is designed as the single source of truth for agent capabilities, supporting the Model Context Protocol (MCP).
By registering custom Cloud Run-hosted MCP servers as Service resources in Agent Registry, administrators publish standardized JSON tool schemas and declare remote HTTP/SSE transport endpoints. Simultaneously, enabling Google Cloud MCP servers automatically indexes native connectors (e.g., BigQuery, Cloud Logging) within the registry. This unified catalog allows agents to dynamically discover available tools while centralizing IAM access governance, ensuring that callers are authenticated and authorized to invoke specific capabilities. Storing endpoint configuration maps in Secret Manager or using Cloud Endpoints requires bespoke service discovery plumbing and lacks native MCP schema integration, increasing maintenance overhead.
Reference: Securing and governing agentic workflows - Agent Registry Service resources, MCP server centralization, and unified capability governance.
NEW QUESTION # 65
You are deploying a data analysis agent with a dedicated agent identity. The agent needs access to a specific Cloud Storage bucket containing financial data in the same project as the agent. You must ensure that the agent identity cannot access any other storage buckets, even if overly permissive project-wide IAM roles are accidentally granted.
What should you do?
Answer: C
Explanation:
In Google Cloud identity architecture, Principal Access Boundaries (PAB) establish guardrail policies that restrict the resource set a principal can access, regardless of broad IAM allow permissions granted at the project, folder, or organization levels. When deploying autonomous data analysis agents handling sensitive financial records, accidental grants of overly permissive project-level roles (e.g., roles/storage.admin or roles
/editor) risk granting the agent access to unauthorized buckets across the project. Attaching a Principal Access Boundary policy to the agent's identity principal defines an explicit, non-bypassable perimeter that limits the principal's effective access exclusively to the specified Cloud Storage bucket resource. Even if a project administrator accidentally assigns broad storage permissions to the identity later, the PAB policy evaluates first and denies access to any resource outside the boundary. IAM Conditions on allow bindings do not prevent other unconditional grants from taking effect, and VPC Service Controls enforce network perimeter boundaries rather than per-identity resource limits.
Reference: Securing and governing agentic workflows - Principal Access Boundaries (PAB), IAM guardrails, and least-privilege agent identity governance.
NEW QUESTION # 66
You are deploying an agent on Gemini Enterprise Agent Platform in Project-A, a dedicated runtime Google Cloud project. The agent needs to retrieve database API credentials from Secret Manager in Project-B, a centralized governance project, and query an Agent Search data store also hosted in Project-B. You are using Agent Identity to govern the agent's permissions across projects. You need to grant the minimum required cross-project IAM access while following the principle of least privilege.
What should you do?
Choose two
Answer: D,E
Explanation:
Establishing cross-project access for autonomous agents under enterprise security standards requires adherence to the principle of least privilege through resource-level IAM bindings. Rather than granting project-wide administrative roles, Agent Identity principals must be granted only the specific roles necessary on the designated target resources. To allow the agent in Project-A to retrieve database API credentials from Secret Manager in Project-B without exposing other project secrets, the agent's identity principal is granted roles/secretmanager.secretAccessor scoped directly to the specific secret resource. This permits reading the secret payload (secretmanager.versions.access) while preventing secret modification or administrative deletion. Similarly, to enable grounded search against an enterprise knowledge corpus hosted in Project-B, the identity principal is granted roles/discoveryengine.viewer scoped strictly to the specific Agent Search data store resource. This grants search query permissions (discoveryengine.servingConfigs.search) without providing write access or broader project-level catalog management rights (discoveryengine.editor). Cross- project impersonation via serviceAccountTokenCreator introduces unnecessary privilege escalation paths.
Reference: Securing and governing agentic workflows - Cross-project Agent Identity, Secret Manager resource scoping, and Discovery Engine Viewer least-privilege IAM.
NEW QUESTION # 67
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