5 — Platform Engineering at Scale
Purpose
[stub: platform-engineering-at-scale]
Metadata
| Author | Amit Singh |
| Scope | kubernetes |
Local graph
Related notes
4 — AI/ML Platforms on Kubernetes
Why GPU scheduling — bin-packing, MIG partitioning, gang scheduling for distributed training — is the hard problem in running ML workloads on Kubernetes, not container orchestration itself.
8 — Architecture Interview Case Studies
Why the strongest system-design interview answers name the failure mode they're trading against, not just the components drawn on the whiteboard.
7 — Designing Control Planes
Why every control plane is a distributed consensus problem in disguise — the API server and etcd exist to answer 'what is true right now' under concurrent writers.
3 — Event-Driven Platforms
Why event-driven platforms on Kubernetes trade request-response simplicity for the ability to absorb bursty load and isolate producer and consumer failure domains.