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TEST - September 29, 2026 at 11 AM ET

TEST - The Hidden Cost and Risk of Kubernetes Multitenancy

Get one tenant's memory limit wrong, and someone else's pod gets killed for it, on a bill that can't tell the two of them apart anyway.

Save Your Seat

Almost nobody runs one cluster per team anymore, and once you share a node pool, requests and actual usage start drifting apart fast. That drift shows up as throttling, out of memory kills, and noisy neighbor incidents that platform teams end up debugging even though nothing in the platform is actually broken. Quotas don't fix this. They just cap how bad it gets. It also shows up in the cloud bill: one line for the node group, nothing for the tenant, built on whatever allocation model got cobbled together from those same bad requests. And the problem doesn't stop at the cluster edge. The shared database, the cross-zone traffic, the inference endpoint every team's model hits, none of that has a tenant attached to it either.

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This session skips the slide deck and goes straight to a live, multi-namespace cluster. You'll watch it happen: workloads right-sized autonomously, risk prioritized across clusters and namespaces, and multi-tenant costs attributed down to actual runtime consumption, no tags required. That's the demo, running on PerfectScale and Attribute by DoiT, but the problem belongs to anyone running a shared cluster. We're skipping the how-to-implement-multitenancy conversation entirely, no namespace-per-tenant debates, no RBAC design. This is about running it and paying for it once you already have it.

What you'll walk away with:

  • See exactly how a single inflated memory request turns into someone else's 2 AM page, and why resource quotas don't stop it
  • Learn why an allocation model built on requests is a model built on guesses, and where the biggest unallocated spend actually hides
  • Watch a live look at risk prioritization across namespaces, plus how runtime-level attribution puts a real number on shared infrastructure costs

Who is this session for:
Platform engineers, site reliability engineers, and FinOps practitioners responsible for shared Kubernetes environments.

Meet the team

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