Beginner to Hero: Agentic AI on Google Cloud: full course guide
Take an agent to production on Google Cloud: identity and least privilege, grounding and the vector index, orchestration choices, contract testing against cloud services, evaluation in the pipeline, and infrastructure as code with cost controls and a runbook.
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What is inside this guide
01Getting Set Up on Google Cloud
- The Managed Pieces and What They Replace
- Projects, Identity and Least Privilege for an Agent
- Model Access, Regions and Quotas
- Local Development Against Cloud Services
- Your First Agent Running on Google Cloud, End to End
02The Development Framework
- Tools as Functions: Contracts, Timeouts and Retries
- Grounding, Search and the Vector Index
- Orchestration Choices: Serverless, Workflows or a Long-Lived Worker
- Session State, Memory and Storage
- Networking, Private Access and Data Boundaries
03The Testing Framework
- Testing Cloud Code Without Deploying Every Time
- Contract Tests Against Managed Services
- Recorded Trajectories and Deterministic Replay
- Load, Concurrency and Quota Behaviour
- Testing Permissions and the Deny Path
04The Evaluation Framework
- Wiring Evaluation Into the Build Pipeline
- Grounding and Retrieval Quality, Measured Separately
- Task Success and Cost per Task on Cloud Pricing
- Human Review Queues and Label Storage
- Comparing Two Configurations Without Fooling Yourself
05The Deployment Framework
- Infrastructure as Code for the Whole Agent
- Environments, Promotion and Configuration Drift
- Observability: Traces, Metrics, Logs and Redaction
- Cost Controls, Alerts and Runaway Protection
- Release, Rollback and the On-Call Runbook
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