Start with a realistic AWS deployment, event-driven service, data engineering pipeline or AI system. Read the architecture, inspect its components, then open an editable diagram. Visual and code editing are free to try without login; AI generation and cloud account storage require an account.
Separate internet-facing entry points, application compute and persistent data in an AWS three-tier architecture. Customize a working diagram of request routing, caching and database access before discussing your deployment with the team.
Map how an order service publishes events and independent consumers handle fulfillment and notifications. Use the Kafka diagram to discuss delivery guarantees, consumer ownership and recovery when processing fails.
Visualize a data engineering pipeline that moves source data through Bronze, Silver and Gold layers. Make ingestion, quality checks, analytical models and downstream consumption visible in one editable lakehouse architecture.
Outline the traffic path into a Kubernetes cluster running on Amazon EKS. Separate ingress, service discovery, application workloads and external data dependencies, then customize the diagram to match your namespaces and deployment topology.
Separate knowledge ingestion from online question answering in a retrieval-augmented generation system. Trace how documents become retrievable chunks and how a query uses selected context to produce a response with sources.
Design an AWS serverless API with a clear request path and a separate asynchronous processing path. Use API Gateway, Lambda and DynamoDB components to discuss authentication, data access, retry behavior and workload boundaries.
