Stories · Data Platform
EMR on EKS, migrated agent-native : the data team got its cycles back.
Operational overhead on a legacy EMR footprint had grown to the point where it consumed the data team's cycles. EKS-native EMR was the engineering answer; the migration risk was the blocker. Agent-native delivery landed the migration. Aedeon ran the discovery and validation. FDEs owned the architecture and cutover. The data team reallocated its cycles from infrastructure maintenance to analytical work.
Baseline
Legacy EMR cluster footprint. Operational overhead consuming data-team cycles.
Outcome
Amazon EMR on EKS. Consolidated Kubernetes-native infrastructure. Cycles reallocated to analytics.
Time to Value
Weeks
The Challenge
The data team was patching infrastructure instead of doing analysis.
Operational overhead on the legacy EMR footprint had grown to the point where it consumed most of the data team's cycles. EKS-native EMR was the obvious engineering answer : but the migration risk meant the team that owned the legacy was the team that would have to run the migration, on top of the operational work that was already consuming its cycles. A traditional engagement would have demanded those same scarce cycles from the data team.
How We Delivered
Aedeon ran discovery and validation. The data team kept its operational cycles.
Aedeon ran the discovery and validation across the legacy EMR footprint : work that under traditional delivery would have demanded the data team co-staff the analysis. Forward-deployed engineers owned the target architecture and the cutover. The data team contributed where its judgment was needed : on the analytical workload priorities, on the cutover sequencing for live jobs : but did not have to absorb the analyst-tier work that Aedeon handled. The cycles freed by the migration multiplied after cutover, when the infrastructure stopped consuming maintenance time.
Why This Matters
The data team's cycles stay on the analytical work the business actually needs.
Infrastructure consolidations live or die by whether the team that runs the legacy can also run the migration. Agent-native delivery makes that math work : Aedeon does the analyst-tier work the team would have been pulled in for, so the data team's cycles stay on the analytical work the business actually needs.