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Cloud Architecture

GCP Agentic Workflow Understanding

A cloud architecture study showing how agentic AI workflows can be bounded, observable, and reviewable.

GCP ConceptsAgentic WorkflowsCloud RunPub/Sub

Overview

This case study documents conceptual understanding of GCP-oriented agentic workflow architecture with emphasis on control, observability, and review gates.

Role / Contribution

  • Mapped service responsibilities, execution boundaries, state transitions, and review points for agentic workflow planning.

System Architecture

Step 01

Event Trigger

Step 02

Task Router

Step 03

Agent Worker

Step 04

Tool/API Layer

Step 05

State Store

Step 06

Review Gate

Primary Flow

Event TriggerTask RouterAgent WorkerTool/API LayerState StoreReview Gate

Data Flow

  1. An event creates a bounded task request.
  2. A router classifies the task and assigns allowed tools.
  3. The agent worker executes within policy constraints.
  4. State and outputs are logged for review.
  5. Sensitive or low-confidence actions pause at a review gate.

Technical Components

Cloud Run concept
Pub/Sub event routing
Cloud Storage or database state
Service account boundaries
Logging and monitoring
Human approval gates

JSON Output Example

{
  "task_id": "TASK-2041",
  "trigger": "new_document_uploaded",
  "allowed_tools": [
    "extract_text",
    "validate_schema"
  ],
  "execution_status": "waiting_for_review",
  "audit": {
    "logs_written": true,
    "reviewer_required": true
  }
}

Engineering Notes

  • Agentic workflows should be scoped by permissions, task type, and review policy.
  • Cloud architecture decisions should support auditability before expanding autonomy.

Key Takeaways

  • Demonstrates GCP conceptual fluency.
  • Shows understanding of bounded agent execution.
  • Connects cloud workflow patterns with governance needs.