Hi to,

Let's be honest. Most Kubernetes environments weren't built with the level of determinism that modern workloads actually demand. Five nodes, you can handle. At one hundred, the drift your team has been working around becomes your biggest bottleneck. Then adding AI workloads on top means you're not just firefighting harder, you're building on a foundation that will fail you at the worst possible moment. Why keep stacking more tooling on a broken foundation when you can eliminate the conditions that create drift in the first place?

Join us live on April 9 to learn how to make that shift.

What you'll take away:

• How to identify the hidden drift patterns that are quietly stalling your roadmap
• How to quantify the cost of operational toil and make the case for a better foundation
• How an API-driven, immutable OS eliminates drift instead of just managing it
• How to scale your cluster count and your AI ambitions without scaling your headcount

Move beyond the firefighting phase even if you can't make it live. Register anyway and we'll send you the recording.

On-Demand Sessions

Looking for more insights? Catch up on previous discussions available to watch anytime:

• Building a self-service developer platform the thoughtful way

  Developers want a public cloud-like experience — even on-prem. In this insightful session, we uncovered how to automate full-stack Kubernetes deployments with a single Git commit.
  
  

• Scaling real-time AI & ML workloads for performance and efficiency

  Platform teams are being squeezed between the need for massive contextual data and the reality of brittle, high-maintenance infra. Explore why real-time context has become the core data primitive for modern AI.
  
  

• AI-powered Kubernetes observability best practices in 2026

  As AI workloads move into production, the ephemeral nature of Kubernetes is becoming even more difficult to manage. Learn how to leverage AI-powered insights to ensure the health, performance, and security of your increasingly complex K8s environments.

   

• Building production-ready agentic AI — why a Control Plane matters
  Generative models alone aren’t enough for production-grade AI. Without a unifying control plane, scaling autonomous agents often leads to hallucinations, cascading errors, and unpredictable system behavior. Catch the replay for a deep dive into the missing piece in the AI stack: the Control Plane.

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