> just keep k8s in mind but I think is better to dedicate a session for k8s. anything I should know now? I understand the concepts well and have some practical 
  experience (on the job and running a cluster locally) but its been a while

● Good to plan ahead! Here are the key things to keep in mind for the K8s session:

  K8s-Specific Considerations for Your App

  Stateful Components:
  - PostgreSQL (needs StatefulSet + PVC)
  - Redis (can be deployment but consider persistence)
  - Media files storage (shared PVC across workers)

  Service Architecture:
  - Django ASGI (HTTP + WebSocket)
  - Celery workers (separate deployment)
  - Nginx (HLS file serving)
  - External services (PostgreSQL, Redis)

  Scaling Patterns:
  - HPA for Celery workers based on queue depth
  - Video processing is CPU/memory intensive
  - WebSocket connections need session affinity

  Storage:
  - Shared volume for HLS segments (/media)
  - Database persistence
  - Consider GCP Cloud Storage integration

  Networking:
  - Ingress for external access
  - Internal services communication
  - WebSocket support in ingress

  GCP Integration Points:
  - GKE cluster
  - Cloud Storage for media
  - Cloud SQL (optional PostgreSQL upgrade)
  - Container Registry for images

  The current Docker Compose setup translates well to K8s, but you'll need persistent volumes and proper service discovery. Your video processing workload is perfect
  for demonstrating K8s scaling capabilities.

  We can tackle the architecture cleanup first, then dedicate a full session to the K8s deployment!