
No drag-and-drop AWS icon libraries. Describe your VPCs, load balancers, compute, and databases in plain English and get a clean, structured architecture diagram back.
Drawing a cloud architecture usually means hunting through icon libraries and lining up boxes by hand. With CloudSketch AI you describe the setup the way you would explain it to a colleague (CDN, load balancer, containers, functions, databases and network boundaries) and get a structured diagram with VPCs and subnets grouped correctly.
“An AWS architecture with a public ALB routing to an ECS Fargate service, an internal API Gateway, Lambda functions for image processing, an RDS Postgres instance in a private subnet, and S3 for static assets, all behind CloudFront.”
Drawing the diagram…
An example of the diagram this prompt describes. Your own result can differ in layout and detail.
Swipe sideways to see the whole diagram.
VPCs, subnets, load balancers, managed databases and serverless functions are recognized and laid out with the right groupings.
View the same architecture as a deployment diagram, a flowchart, or a C4 container diagram with no extra AI calls.
Export clean diagrams for cloud migration proposals, security reviews, and onboarding docs.
Show the target AWS architecture in a migration plan or a client proposal.
Make public and private subnets, entry points and data stores obvious to reviewers.
Keep an up-to-date picture of what runs where for the engineers who get paged.
CloudSketch AI focuses on clear structural architecture diagrams (boxes, groupings, and connections) rather than official AWS icon sets — the goal is fast, accurate communication of the architecture, not a pixel-perfect AWS icon board.
Yes — describe your GCP or Azure setup the same way and CloudSketch AI will generate the equivalent architecture diagram.
Yes. This example uses the Network diagram type, which is on the free plan (10 diagrams a day with a free account, 3 without signing in). Pro adds unlimited diagrams plus the C4 and Deployment types.
Yes. Download it as PNG, SVG or PDF, or copy the Mermaid code into your docs, wiki or GitHub README.