Kubernetes platform engineering is complex, especially with large, shared clusters supporting multiple workloads and teams. Defeating complexity requires multi-cluster thinking: Compose clusters declaratively with services and policies to support one or a small range of workload types (versus many); administer and lifecycle manage declaratively to continually assure cluster state; and repeat for all the workload types your organization needs to support. Simplifying platforms and customizing them to workload requirements pays off bigtime in agility, smoother operations, higher workload availability, security, and compliance. Plus: You don't need to implement a global multi-cluster architecture to do this at smaller scales. In this webinar, we’ll explore: - How to think of Kubernetes platforms as containers for workloads, services (LMA, FinOps), and policies. - Building up use-case-optimized platforms from 'bare clusters.' - Approaches to automate platform operations and LCM. - Strategies to keep platforms healthy and integrated over time. And we'll share how we're doing all of this with open-source-based tools. Join us!
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