A vehicle that remains in sport mode consumes more fuel than necessary. The same principle applies to cloud platforms: the operating model and compute capacity must match actual demand. ITM Consulting therefore redesigned the Databricks environment supporting the SAP LeanIX integration for a leading German automotive manufacturer. Within five months, monthly costs fell from around US$24,000 to US$123.
01 The Challenge
Operationally reliable, but not cost-optimized
Databricks processed integrations, automations, scripts, and webhooks for an SAP LeanIX environment encompassing 22 fact sheet types and more than 240,000 fact sheets. The environment functioned as intended, but there was no end-to-end approach to determine which workloads required Databricks, how they could be consolidated, or how much compute capacity they actually needed. Monthly costs had reached approximately US$24,000.
The customer had set an annual savings target of US$150,000. Achieving this goal required more than simply scaling down individual clusters. The team first needed to identify which processing tasks SAP LeanIX could handle natively. The remaining Databricks capacity could then be sized precisely.
02 The Approach
Move the workloads first, then optimize compute
Phase 1: Move workloads back to SAP LeanIX
ITM Consulting reviewed every integration, automation, script, and webhook. Tasks that could be handled using SAP LeanIX's native capabilities—including automations, calculations, and scheduled connectors—were moved from Databricks back to SAP LeanIX.
The remaining workloads were consolidated. Where appropriate, scheduled processing replaced event-driven execution. More streamlined trigger events and payloads also reduced the number and size of runs. This first phase cut the original cost by 77%.
Phase 2: Reduce the remaining Databricks costs by an additional 98%
For the workloads that still required Databricks, ITM Consulting aligned DBU consumption and cluster configuration with actual demand. Compute capacity was reduced to the lowest level that still ensured stable operations.
Right-sizing reduced the costs remaining after Phase 1 by an additional 98%. Combined, the two phases resulted in an overall reduction of 99.5%.
Continuously monitor cost trends
Databricks dashboards provide an ongoing view of usage and costs. Deviations become apparent early on, and the environment can be adjusted as new requirements arise. This helps maintain savings over time.
The greatest savings did not come from smaller clusters alone. They came from avoiding unnecessary Databricks workloads and precisely sizing the remaining compute capacity.
03 The Outcome
From about US$24,000 to US$123 per month
After five months, monthly Databricks costs stood at US$123. Compared with the original level of around US$24,000, this represents a reduction of 99.5%. If the new cost level remains stable, the annualized savings potential is about US$287,000.
The architecture is also clearer. SAP LeanIX now handles every task that can be delivered natively. Databricks is reserved for workloads that genuinely require external computing capacity. This reduces complexity and makes it easier to control costs over time.
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