📝 See a mistake or have insights to add? This podcast is community-driven - open a PR on GitHub! Summary: • Service mesh ambient mode eliminates sidecars (Istio 1.24, Red Hat OpenShift 3) • AI/ML integration: Kubeflow mainstream, 85% shadow AI problem requires governance • When to use K8s: 200+ nodes, complex orchestration, multi-cloud, 5-15 FTE platform team • When to skip: ＜200 nodes, monoliths, limited expertise, need production in ＜3 months • Skills rising: platform engineering (60% forming teams), AI/ML workloads, security/compliance • Skills declining: manual kubectl ops, vendor-specific expertise (multi-cloud abstractions winning) • Alternatives gaining ground: Docker Swarm revival, Nomad, ECS/Cloud Run, PaaS ($400/mo vs $150K/yr team) • 88% cite rising costs, 42% say it’s their #1 pain point - most underestimate by 3-5x • Salary: $144K-$202K for K8s skills alone, premium for platform engineering expertise