Domain Driven Design in Cloud Native Environments
summary
Argues that many tactical DDD patterns break on cloud native platforms and shows concrete adaptations: bounded contexts map to accounts/VPCs or clusters, serverless tradeoffs like cold starts and Lambda layers-as-binary-deps, and choices around one-account-per-team, one-cluster-per-team or one-namespace-per-team. Recounts a failed Flash-based language editor that was rebuilt with DDD, recommends infrastructure as code (CDK, Terraform, Helm), advocates data mesh and MLops for operationalizing analytical models, warns low‑code/step‑function limits, and stresses alignment of data, infra and team boundaries.
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chapters (16)
- 0:00Introduction and speaker background
- 8:30From burnout to DDD focus
- 10:15Transition to AWS and cloud challenges
- 12:42Bounded contexts in cloud native
- 16:20Serverless runtime behavior
- 17:24Infrastructure boundaries per context
- 20:55Context mapping and integration
- 23:22Serverless function layers
- 27:57Enforcing team boundaries
- 31:53Self-service infrastructure
- 34:24Data boundaries and persistence
- 38:15Operational data latency
- 41:02Analytical data governance
- 43:06Machine learning data flow
- 45:56Low-code environments limitations
- 49:51Complexity in visual tools
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