Launch and grow your startup on GCP
summary
A 10‑year startup case study of SnapEngage shows how migrating from App Engine alpha to a GCP stack (App Engine Java, Datastore, Cloud Storage, Compute Engine, Cloud Functions, Firestore, Cloud Pub/Sub) lets a small team avoid ops work, handle billions of queries per month, and iterate fast. Concrete wins: App Engine auto-scaling removes capacity planning, Cloud Storage serves bundled JS assets from the edge, BigQuery streaming analytics replaces a failed third‑party vendor, and Stackdriver live debugging cuts MTTR. Limitations: dataset per‑client hits project‑level API limits.
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chapters (17)
- 0:00Start
- 10:33App Engine for Java
- 12:01App Engine
- 13:33Deploy Process
- 14:38Split Speed Version Deploy
- 17:49Automatic Scaling as Automatic Failover
- 19:45Connectivity
- 23:14Cloud Datastore
- 23:33App Engine Data Store
- 27:03Data Store
- 27:44Cloud Storage
- 28:46Cloud Data Store
- 30:51Cloud Endpoint
- 35:31Ui
- 39:18Bigquery
- 48:15Stackdriver
- 52:20Firebase
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