01 / Inside the engagement
Situation
Engineers ran critical analysis code through remote desktop sessions on shared engineering workstations, hunting for scripts and fixing file paths by hand. Only trained engineers could use it, versions drifted, and a technician on the floor with a question had to wait for someone off-shift.
Context
- Analysis scripts
- Shared workstations
- Remote desktop
UTIS contribution
- Browser job request
- Databricks App and Azure AKS
- Job status and outputs
Simplified workflow. The case text describes the contribution, delivery stage and evidence.
Explore the full conceptual diagram
02 / Inside the engagement
What UTIS did
- Stood up the Kubernetes analytics platform on Azure: AKS, container registry, CI/CD and orchestration, built with Terraform and Azure DevOps.
- Built and deployed a Databricks App that lets users submit MATLAB and Python analysis jobs to the cluster, monitor status, review outputs and explore data, inside strict network restrictions and with Entra-based access control.
- Documented the platform and named a successor so the handover did not depend on one person.
03 / Inside the engagement
Results
- Production analysis code runs on the new platform with outputs matching the existing system.
- Job submission, monitoring and output review from a browser, with no scripts or remote desktop setup.
- Daily-workflow cutover in progress at time of writing.
Why it matters to you
A controlled browser route can make analysis easier to run while preserving the established calculation. The documented check compared outputs with the existing system; daily-workflow cutover remained in progress in the available record.
Stack
How we measured it: output reconciliation against the existing production system.