Cloud Adoption Patterns
summary
Key patterns emphasize using elastic ephemeral compute, writing logs to durable buckets, and choosing services that fit the data scale (EC2, Lambda, Cloud Run, Kubernetes, BigQuery, Spark, Dataplex, SageMaker). Concrete wins include cutting a genomic workflow from 500 hours to 5 hours (later to ~10 minutes) and saving $100k/month by switching bucket storage from multi‑regional to single‑region. Success hinges on MVP pipelines, end‑user validation, embedded learning time, and pragmatic security with alerting.
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chapters (6)
- 0:00Start
- 1:39CLOUD ADOPTION PATTERNS
- 6:43FIRST CLOUD PATTERN
- 7:50CLOUD SMELL
- 12:31CLOUD COSTS
- 36:39SANDBOX
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