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Google AI Classroom Part 7: Serverless Map-Reduce-Map Video Intelligence & Rubric-Driven Practical Task Auto-Grading with Gemini 4 Argon

DEV Community: firebase·Cyrus Wong·about 22 hours ago
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Author: Cyrus Wong (黃俊彥) — Google Developer Expert - Cloud (AI), Senior Lecturer at HKIIT

1. The 80-Hour Lab Grading Bottleneck & The HTTP 429 Quota Wall

In hands-on cloud computing, DevSecOps, and full-stack software engineering courses, students spend 2 to 3 hours building infrastructure in the AWS/GCP Console, writing Terraform modules in VS Code, and debugging container deployments in the terminal. Reviewing a single 40-student cohort's 2-hour screen recordings manually requires 80 hours of instructor time per lab .

However, when our engineering team first attempted to automate post-class video grading by firing 40 concurrent multimodal video analysis calls against the Gemini API at the end of a lab session, two hard distributed systems walls appeared immediately:

The Serverless Execution Timeout Wall ( 540s ) : Even a 2nd-Gen Cloud Run-backed Cloud Function caps synchronous execution at 540 seconds (9 minutes).…

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