Cloud Provider
Databricks Workflows
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Inefficient Use of Job Clusters in Databricks Workflows
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Cloud Provider
Databricks
Service Name
Databricks Workflows
Inefficiency Type
Suboptimal Cluster Configuration

When multiple tasks within a workflow are executed on separate job clusters — despite having similar compute requirements — organizations incur unnecessary overhead. Each cluster must initialize independently, adding latency and cost. This results in inefficient resource usage, especially for workflows that could reuse the same cluster across tasks. Consolidating tasks onto a single job cluster where feasible reduces start-up time and avoids duplicative compute charges.

There are no inefficiency matches the current filters.