Autoscaling & Kubernetes:
Why It’s Harder Than It Looks

1. Scrape intervals & delays

Prometheus, DataDog, HPA checks could take eternity at scale

2. Multi‑cluster coordination

Clusters scale independently unless you unify metrics

3. GPU & AI workloads

GPU nodes are expensive; scaling them wrong burns cash fast

4. Security & compliance

Hardened images and FIPS matter in regulated environments

This is exactly why we built Kedify