Optimize Spark performance & cost

Optimizing Spark pipeline performance & resource utilization, to ensure SLAs and cut platform costs.

• Monitor job-level performance out-of-the-box -- Spark on-prem, cloud or K8S, Databricks, EMR, Dataproc, and others
• Tracking consumption and cost at all levels
• Pinpoint job-level waste, under-utilization and inefficiencies, such as data skew or memory spill
• Identify concrete optimization opportunities & actionable recommendations