Talk Outline

1. The Developer Experience Gap with Kubernetes
   a. The traditional Kubernetes workflow i.e. Docker → YAML → kubectl → pray , is powerful but developer-unfriendly. It involves repetitive steps, friction at every stage, and a high risk of drift between local and production environments.
   b. Developers are often blocked by tight coupling with operations teams, relying on them for deployments, configs, and debugging.
   c. Devs need autonomy, speed, confidence - not just “infra knowledge”

2. Developer-Centric Kubernetes: What It Looks Like
   a. One command to spin up services
   b. Code-change triggers fast feedback (no full builds)
   c. Local clusters that mirror prod
   d. Live logs, port forwarding and visibility

3. The Toolkit (Solution Introduction) : “There’s a better way”
   Introduce a modern, DX-first toolchain that simplifies the cloud-native journey:
   a. FastAPI: Developer-friendly web framework
   b. Docker: Familiar base layer, everyone's comfortable here
   c. Skaffold or Tilt: Dev loop automation (auto-rebuild, redeploy, logs, config)
   d. K3s or kind: local K8s, zero cloud billing
   Discuss the goal: abstract away YAML & ops overhead so devs can focus on building.

4. Diving deep : Tilt for Local Dev
   a. This section will discuss about how Tilt lets developers iterate locally with live reloads, automatic container rebuilds, and a clean web UI. Then elaborate on how - Using a Python-like Tiltfile, can define builds and deploy in a few lines, enabling a faster inner dev loop and service observability.
   b. Demo: Live-edit a Python service deployed to kind with Tilt

5. Introducing Skaffold
   a. What is Skaffold? Lifecycle automation for K8s
   b. How Skaffold works: YAML config - build, tag, deploy
   c. Supports Helm, Kustomize, CI/CD
   d. Demo: Use Skaffold to push a Python service to a cloud environment
   e. Discuss Benefits: Developer + CI support , Works across environments

6. Tilt vs Skaffold: Which Tool, When?
   Tilt excels at rapid local development. Skaffold shines in structured, repeatable pipelines (Dev → CI → Staging → Prod) . We’ll explore when to use each tool - and how they can work together to support the entire dev-to-prod lifecycle.

7. Best Practices for Python Devs Using Kubernetes
   a. Use kind or k3d for local clusters
   b. Avoid handwritten YAML - generate via Helm or templates
   c. Automate repetitive tasks (certs, port forwards, secrets)
   d. Use minimal images and slim base containers
   e. Stay close to prod with shared configs/profiles and Get dev/prod parity without cloud costs

8. Q&A and Audience Polling
   Open floor for questions + a fun poll on what framework attendees plan to try next.