Stop Making Your Data Team Learn Kubernetes

Successful organizations often find a balance where platform teams empower others without overwhelming them with infrastructure complexity, which is particularly challenging for data teams focused on tasks like analysis and data science rather than infrastructure concerns. These teams require specialized orchestration tools that cater to their unique needs, such as handling batch jobs, resource-intensive operations, and dynamic workflows, without forcing them to become infrastructure experts. Traditional infrastructure solutions often fail to meet these needs, leading data teams to either build complex custom systems, adapt ill-fitting tools, or embrace complexity in their code, which diverts focus from their core tasks. The article highlights the importance of creating a separation of concerns where data teams concentrate on data processing while platform teams manage orchestration and infrastructure, thereby allowing both to excel without unnecessary complexity. This approach enhances innovation and efficiency, as exemplified by tools like Prefect, which aim to simplify workflow orchestration for data teams.