AWS infrastructure
Map application mechanisms to AWS resources, permissions, and limits.
Connect code, credentials and resources deliberately
Running a local Python process does not create an AWS API, queue, or database. A deployment needs an application artifact, its configuration, resource definitions, and a runtime identity with the right permissions. Each has a separate owner and failure mode.
Begin with reproducible local execution and the service mapping. The conditional-write and upload labs provide commands. The queue lab supplies an AWS SAM template and worker. Each cloud exercise states setup, expected evidence, and cleanup.
Parts group related chapters. Each lesson has a chapter.lesson address, such as 4.07. Open a title below, or use Next to follow the reading sequence. Within a lesson, On this page lists its sections.
- 12.01
Build once and supply configuration safely at runtime
Concepts and examples
- 12.02
AWS · translate a mechanism into infrastructure
Concepts and examples
- 12.03
Use DynamoDB conditions to reject duplicate creates and stale edits
Concepts and examples
- 12.04
Upload private object bytes directly and finalize application metadata
Concepts and examples
- 12.05
Process duplicate SQS jobs with one conditional DynamoDB result
Concepts and examples
- 12.06
Implement bounded report execution and shutdown
Projects and practical assessment