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Updated Feb 10, 2026
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Part 6: AI Cloud Native Development

Part 7 takes the agent you built in Part 6 and turns it into a production cloud service. You'll containerize the stack, orchestrate it on Kubernetes, automate delivery, and operate it with observability, security, and cost controls. The goal: a reliable Digital FTE that runs 24/7 for real users.

Prerequisites: Parts 4-6. You need a working agent service to deploy.

Goals​

By completing Part 7, you will:

  • Containerize agent services with production Dockerfiles and image optimization
  • Orchestrate at scale using Kubernetes deployments, services, and Helm charts
  • Adopt event-driven patterns through Kafka-based messaging
  • Leverage Dapr for service invocation, state, pub/sub, and workflows
  • Automate delivery with CI/CD pipelines and GitOps via ArgoCD
  • Operate with excellence through observability, security, governance, and cost management

Chapter Progression​

Seven stages build deployment capability step-by-step:

  • Containerization & Orchestration (49-51): Docker fundamentals → Kubernetes deployments → Helm packaging.
  • Event-Driven Architecture (52): Kafka for asynchronous agent communication.
  • Dapr Core (53): Sidecar patterns for state, pub/sub, and secrets.
  • Automation (54): GitHub Actions plus ArgoCD for repeatable releases.
  • Operations Excellence (55-58): Observability, API gateways, security, and infrastructure-as-code for cloud clusters.
  • Advanced Dapr (59): Actors and workflows for long-running, stateful agents.
  • Real Cloud Deployment (60): Apply everything on a managed cloud environment.

Why this order? Containerization precedes orchestration; orchestration precedes automation; automation precedes operations; advanced patterns come after the foundations are stable.

Outcome & Method​

You finish with a sellable Digital FTE: containerized, deployed to Kubernetes, scalable, observable, secure, and cost-aware. The same spec-driven approach continues—write infrastructure specs, let AI draft manifests/pipelines, and validate against requirements.