Most technical exams stop at unit tests or multiple-choice questions. They check whether code runs or a definition is recalled — but rarely whether a learner can design, deploy, and validate a complete cloud solution. The result is a disconnect: students may score well, yet struggle to deliver when faced with real environments.
Meghkosh changes the equation. As an orchestration layer, it adapts to any cloud provider and allows instructors to design end-to-end cloud exams: from provisioning VPCs and databases to deploying applications, APIs, or even AI workflows.
In a fair exam, every student receives:
- A dedicated sandbox account, secure and quota-bound
- Stepwise instructions authored in CloudX Canvas
- Real-time monitoring of progress through CloudX Lab
- CloudX Observe dashboards for instructors to track scores, attempt patterns, and learning gaps
The final outputs aren't just tested for existence. With TruthSeeker, auto-grading goes beyond unit tests:
- API endpoints are called and validated for correctness and latency
- Applications are checked for functionality and resilience
- Semantic validation ensures solutions meet business logic, not just technical syntax
- Media or AI outputs (images, audio, models) are examined intelligently
This means grading is not only faster, but also consistent, transparent, and fair across large cohorts. Students prove they can deploy; institutions prove they can evaluate reliably.
With Meghkosh, cloud exams evolve from ticking boxes to demonstrating capability — bridging the gap between passing a test and being job-ready.