Defeat Platform Complexity with Use Case-Optimized Multi-Cluster Kubernetes

In this month's installment, Sergey Goncharov, Sr. Product Manager for Mirantis Kubernetes Engine 4k (MKE 4k) is back to help you tackle the ever-emerging problem of Platform Engineering for complex multi-cluster, multi-cloud Kubernetes workloads. With the rise of AI/Ml, these are becoming more and more prevalent in enterprises around the world.

Overcoming this complexity requires a multi-cluster approach: designing clusters tailored to specific workloads with declarative services and policies, ensuring consistent lifecycle management (LCM), and scaling this strategy across your environments. By optimizing platforms for specific use cases (Kubernetes-based platforms that is), you can improve agility, streamline operations, boost workload availability, enhance security, and maintain compliance - without implementing a global multi-cluster architecture at smaller scales.

A full list of this episode's topics include:

• Challenges with Kubernetes complexity
• Multi-cluster thinking is key
• Building use case-optimzied platforms at scale
• Example open source tools for multi-cluster K8s

If you want to listen to more episodes of Radio Cloud Native, please visit https://www.mirantis.com/radiocloudnative/ to download, or find them wherever you prefer to consume your podcasts.

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Chapters

• 0:00 Intro
• 0:43 Challenges with K8s complexity
• 4:45 Multi-cluster thinking is key
• 8:50 Building use case-optimized platforms at scale
• 19:12 Example open source tools for multi-cluster K8s
• 21:33 Key takeaways from what we've covered
• 23:43 Outro