Kubernetes lacks a global consensus mechanism to coordinate workloads across multiple clusters, leading to inconsistencies and inefficiencies when managing stateful data across regions. This limitation hinders the effective deployment of complex applications like ML training pipelines that require synchronized operations across distributed systems, necessitating new approaches that understand data locality and processing requirements.
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Ali NematiWritten by Ali
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