Agent Operations on Google Cloud (AOPGC) – Outline

Detailed Course Outline

Module 1 - Introduction to AgentOps on Google Cloud

Topics:

  • Challenges of managing production agents
  • Core principles of AgentOps
  • AgentOps on Google Cloud

Objectives:

  • Navigate the challenges of managing production agents
  • Define the core principles of AgentOps
  • Architect agent operations on Google Cloud

Module 2 - CI/CD for Agent Deployments

Topics:

  • CI/CD review
  • Agentic deployment targets
  • CI/CD tooling and patterns on Google Cloud
  • Cloud Build automation

Objectives:

  • Leverage CI/CD tooling and patterns for agentic solutions on Google Cloud
  • Select the deployment target for agents on Google Cloud
  • Build a complete CI/CD pipeline for an agent

Activities:

  • Lab: CI/CD for Agents on Google Cloud

Module 3 - Observability for Debugging and Improvement

Topics:

  • Observability review
  • Logging with agent callback logging
  • Logging and tracing with OpenTelemetry

Objectives:

  • Identify challenges addressed by observability
  • Instrument an ADK agent with structured logs
  • Enable OpenTelemetry tracing on Agent Engine and Cloud Run
  • Leverage BigQuery and Looker Studio for visualization

Activities:

  • Lab: Instrument and Debug Agents with Cloud Logging, and Cloud Trace

Module 4 - Agent Evaluation and Quality Assurance

Topics:

  • Testing generative AI model responses
  • Evaluating model responses

Objectives:

  • Perform validation on model responses
  • Evaluate agent behavior, tool usage, and trajectory correctness
  • Create and manage evalsets using ADK Web UI
  • Evaluate evalsets with ADK UI, CLI, or code
  • Use the Vertex AI Generative AI Evaluation Service

Activities:

  • Lab: Evaluating Agents with ADK

Module 5 - Security and Governance

Topics:

  • Model and context security
  • Agent access

Objectives:

  • Secure model inputs and outputs with Model Armor
  • Protect sensitive data using Sensitive Data Protection with Model Armor
  • Secure the connection between a user and an agent

Activities:

  • Lab: Enhancing AI Security with Model Armor and Sensitive Data Protection

Module 6 - Applying FinOps to Agent Costs

Topics:

  • Primary cost drivers for AI Agents
  • Cost-efficienct agentic systems
  • FinOps on Google Cloud

Objectives:

  • Identify the primary cost drivers of AI agents
  • Reduce token and model costs
  • Architect cost-efficient agent systems
  • Implement a measurable AI FinOps loop on Google Cloud