29 min
How Kubernetes Faces a New Reality with the AI Engineer The New Stack Podcast
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- Technology
The Kubernetes community primarily focuses on improving the development and operations experience for applications and infrastructure, emphasizing DevOps and developer-centric approaches. In contrast, the data science community historically moved at a slower pace. However, with the emergence of the AI engineer persona, the pace of advancement in data science has accelerated significantly.
Alex Williams, founder and publisher of The New Stack co-hosted a discussion with Sanjeev Mohan, an independent analyst, which highlighted the challenges faced by data-related tasks on Kubernetes due to the stateful nature of data. Unlike applications, restarting a database node after a failure may lead to inconsistent states and data loss. This discrepancy in pace and needs between developers and data scientists led to Kubernetes and the Cloud Native Computing Foundation initially overlooking data science.
The Kubernetes community primarily focuses on improving the development and operations experience for applications and infrastructure, emphasizing DevOps and developer-centric approaches. In contrast, the data science community historically moved at a slower pace. However, with the emergence of the AI engineer persona, the pace of advancement in data science has accelerated significantly.
Alex Williams, founder and publisher of The New Stack co-hosted a discussion with Sanjeev Mohan, an independent analyst, which highlighted the challenges faced by data-related tasks on Kubernetes due to the stateful nature of data. Unlike applications, restarting a database node after a failure may lead to inconsistent states and data loss. This discrepancy in pace and needs between developers and data scientists led to Kubernetes and the Cloud Native Computing Foundation initially overlooking data science.
29 min