FinOps

Cost intelligence

Understand where Databricks spend is moving, which workloads are creating cost pressure, and where optimization has the strongest ROI.

Spend anomaly detected

recommendation_generation moved 154.9% above baseline.

LakeOps correlated the change against the recent cost baseline and promoted this workload as the first cost investigation target.

Baseline 7D

$385.84

Current 7D

$983.42

Workspace savings

$1,790/mo

Observed spend

$5,965

Last 30 days

Est. monthly savings

$1,790

30% optimization opportunity

Top workload

37.6%

recommendation_generation

Cost findings

Prioritized cost signals

Spend trajectory

Daily spend against the 7-day rolling baseline

Actual7D avg

Cost drivers

Ranked by 30-day list cost and spend share

1recommendation_generation

$2,246

37.6% share

2customer_etl

$1,421

23.8% share

3finance_daily

$1,077

18.1% share

4marketing_etl

$728

12.2% share

5events_compaction

$494

8.3% share

Optimization opportunities

Evidence-backed cost signals, ordered by severity and impact

$1,790/mo potential

criticalcost · JOB COST INCREASE

Cost increased for recommendation_generation

Review recent runtime, schedule, compute, or workload changes for this job.

baseline 7d cost: 385.84current 7d cost: 983.42

Confidence

95%

Est. impact

$2,561/mo

highcost · TOP COST DRIVER

recommendation_generation is a major cost driver

Prioritize this workload for rightsizing and schedule/runtime optimization.

period cost: 2245.7

Confidence

80%

Est. impact

$337/mo

mediumcost · JOB COST INCREASE

Cost increased for customer_etl

Review recent runtime, schedule, compute, or workload changes for this job.

baseline 7d cost: 298.47current 7d cost: 433.7

Confidence

95%

Est. impact

$580/mo

mediumcost · TOP COST DRIVER

customer_etl is a major cost driver

Prioritize this workload for rightsizing and schedule/runtime optimization.

period cost: 1420.95

Confidence

80%

Est. impact

$213/mo