During mock tests and result announcements, thousands of students log in within minutes. With a single application server, a single database, no auto scaling and only basic monitoring, the site slowed or crashed at the moment students needed it most.
A DevSecOps pipeline governs every feature from planning to production, using AWS-native, third-party and open-source tools, so releases never put a live exam at risk.
| # | Stage | Description |
|---|---|---|
| 1 | Plan | Release scope, with changes held back from major exam windows |
| 2 | Code | Application and infrastructure code under version control |
| 3 | Security scan | Mandatory vulnerability gate before build and release |
| 4 | Build | Automated build and unit tests |
| 5 | Release | Feature flags and canary testing for gradual rollout |
| 6 | Deploy | Infrastructure and application deployed as code |
| 7 | Operate and monitor | Live dashboards, real-time alerts and configuration drift checks |
The solution design does not yet report measured, post-implementation cost savings — per-document processing cost will be tracked going forward via AWS Cost Explorer once the solution is live. What the design does establish is where the return is expected to come from, based on the operational targets above:
To translate these into a dollar ROI figure, Gro Digital Platforms would need to supply a few inputs once available — current manual processing cost per document, average operations headcount cost, and monthly document volume — which can then be modeled against the post-go-live Cost Explorer data. We’d recommend adding a measured ROI figure to this case study once 60–90 days of production data is available.
