Nova monitors every Spark job, Delta Lake table, and cluster in your Databricks workspace. Track job durations, detect data quality anomalies, and optimize cluster costs, all from Nova's unified observability platform.
Nova monitors Spark job execution across your Databricks workspace, tracking job duration, stage progress, task failures, and resource consumption. When a job takes longer than expected or fails, you get immediate context on what went wrong and where.
Nova tracks cluster utilization, CPU, memory, and executor allocation, across all your Databricks clusters. Identify over-provisioned clusters, spot idle compute, and get actionable recommendations to reduce your Databricks bill.
Nova monitors Delta Lake table health, tracking row counts, schema changes, partition sizes, and data freshness. When a pipeline produces unexpected results or a table stops updating, you catch it before downstream consumers are affected.
Monitor Spark jobs, optimize cluster costs, and detect data quality issues, all from Nova's unified platform.