From Idle Compute to Zero Unnecessary Infrastructure Cost
Eliminating unused Dataiku compute, reducing infrastructure overhead, and creating a more disciplined approach to resource allocation.
THE TRANSFORMATION
$48K → $0
Annual infrastructure cost associated with the identified clusters
This represents a 100% reduction in the reported infrastructure cost for the decommissioned resources.
The important transformation wasn't simply shutting systems down.
It was identifying infrastructure that was no longer creating enough value to justify its ongoing cost, removing it, and introducing a Kubernetes resource allocation strategy for the remaining environment.
Idle infrastructure
↓
Utilization analysis
↓
Cluster identification
↓
3 clusters decommissioned
↓
Kubernetes Node Pool strategy
↓
Zero ongoing cost for the identified resources
OUTCOME SUMMARY
The Dataiku optimization focused on infrastructure that was consuming budget without sufficient workload demand to justify its continued operation. By identifying and decommissioning the unused GPU, SCOE and MASH clusters, the engagement eliminated the reported $48,000 annual infrastructure cost associated with those resources.
The optimization also introduced a Kubernetes Node Pool strategy to improve how resources are allocated and scaled. Rather than treating infrastructure capacity as a fixed requirement, the approach created a more deliberate model around actual workload needs, resource utilization and ongoing cost visibility.
