Serverless tools for machine learning, big data and app backends
summary
Overview of practical serverless tooling on Google Cloud and Firebase: demos show headless Chrome screenshots and a Docker-based serverless containers flow that runs Blender for on‑demand 3D renders, and Cloud Functions wired to Firestore, Pub/Sub, BigQuery and ML APIs. BigQuery query scans 2.3 billion GitHub files (2.36 TB) in ~48 seconds; AutoML trains on ~1,000 cheese images and returns correct labels; Cloud Functions cold starts and environment variables, scaling to zero and per‑invoke billing, are demonstrated end to end.
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chapters (11)
- 0:00Start
- 2:40Two types of serverless
- 4:24Cloud Function event triggers
- 5:35New Cloud Functions languages!
- 6:30(-) What's new in Cloud Functions
- 7:24Serverless containers on Cloud Functions
- 17:53Supercharge Firebase with GCP
- 19:29What type of ML problem are you solving?
- 21:09Cloud ML Engine
- 26:42Serverless for data big and small
- 32:16Qualities of a good RDBMS
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