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AI workloads reshaping Kubernetes autoscaling patterns
- Platform/SRE — Learn: Useful framing on how GPU-bound and bursty AI workloads strain the classic HPA/VPA/cluster-autoscaler division; no version change or deadline, but informs how you’d architect autoscaling for AI teams onboarding to the cluster.
- CI/CD — Skip
- Leader — Learn: Useful context for platform strategy as teams push AI/ML workloads onto shared Kubernetes; no near-term decision or cost/vendor change implied, but shapes how you’d evaluate autoscaling capabilities when reviewing cluster investments.
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