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Home - Lessons - AWS Application Development - M3 — Data Layer: DynamoDB and S3 - Choosing between DynamoDB, Aurora and RDS honestly

AWS Application Development Choosing between DynamoDB, Aurora and RDS honestly

AWS Application Development

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M1 — Development Environment and AWS SDKs

AWS account setup and the shared responsibility line for developers

IAM users, roles and the credential model developers actually need

Installing and configuring the AWS CLI and SDKs

Infrastructure basics every developer should read in the console

Local development with SAM CLI and emulators

Project structure, environment separation and configuration

M2 — Serverless with Lambda and API Gateway

Lambda execution model, cold starts and concurrency

Writing a handler that fails safely

API Gateway: REST and HTTP APIs, stages and deployment

Request validation, mapping and response shaping

Authorizers: Lambda, Cognito and IAM

Versioning, aliases and safe traffic shifting

M3 — Data Layer: DynamoDB and S3

Modelling access patterns before modelling tables

Partition keys, sort keys and the single-table decision

Indexes: LSI and GSI and their cost

DynamoDB transactions, conditional writes and idempotency keys

S3 for objects: presigned URLs, multipart and event triggers

Choosing between DynamoDB, Aurora and RDS honestly

M4 — Integration: SQS, SNS, EventBridge and Step Functions

Why the synchronous call is usually the wrong architecture

SQS queues, visibility timeout and dead-letter queues

SNS topics and fan-out to multiple consumers

EventBridge rules, schedules and cross-account events

Step Functions state machines for multi-step work

Delivery guarantees, ordering and poison messages

M5 — Authentication and Application Security

Cognito user pools, federated identity and token flow

Authorization: what the app checks versus what the service enforces

Secrets management and keeping credentials out of source

Input handling, injection and the usual application attacks

Encryption in transit and at rest in an application context

OWASP-aligned review of your own service before it ships

M6 — Testing, Observability and Debugging

Unit and integration testing against cloud services

Contract testing between distributed components

Structured logging that answers questions later

X-Ray tracing across service boundaries

CloudWatch metrics, alarms and dashboards for an app

Debugging a failure that spans three services

M7 — CI/CD for Applications

Source control strategy and environment branching

Building with CodeBuild and the pipeline artefact model

Deploying with CodePipeline, SAM and CloudFormation

Quality gates: tests, linting and security scanning

Configuration promotion between environments

Rollback strategy you have actually rehearsed

M8 — Capstone: A Production Application

Build the API and data layer from a written requirement

Add asynchronous processing with queues and dead-letter handling

Implement authentication and fine-grained authorization

Wire CI/CD with tests and a security gate

Instrument with logs, traces, metrics and alarms

Ship it, then operate it through a simulated incident

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