ab-test-setup
FreePlan, design, and implement A/B tests and experiments with statistical rigor. Covers hypothesis frameworks, sample sizing, metrics, and result analysis.
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Design and operate AWS: architectures with CloudFormation/CDK IaC, serverless patterns and cost optimization, plus day-2 operations for IAM, ECS Fargate, Lambda, RDS, S3, VPC, EC2, CloudTrail and Secrets Manager.
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See how to installReview the instructions the agent will receive before you install.
Design scalable, cost-effective AWS architectures for startups with infrastructure-as-code templates.
Collect application specifications:
Select from recommended patterns:
See references/architecture_patterns.md for detailed pattern specifications with service stacks, CloudFormation templates, and cost estimates.
Validation checkpoint: Confirm the recommended pattern matches the team's operational maturity and compliance requirements before proceeding.
Write CloudFormation YAML (SAM), CDK TypeScript or Terraform HCL for the chosen pattern, starting from the template examples in references/architecture_patterns.md (API Gateway, Cognito, IAM roles, CloudWatch logging). Validate before deploying: aws cloudformation validate-template, cdk synth or terraform validate.
python scripts/cost_optimizer.py --resources current_setup.json --monthly-spend 2000
Output includes monthly cost breakdown by service, right-sizing recommendations, Savings Plans opportunities, and potential monthly savings.
# CloudFormation
aws cloudformation create-stack --stack-name my-app-stack \
--template-body file://template.yaml --capabilities CAPABILITY_IAM
# CDK
cdk deploy
# Terraform
terraform init && terraform apply
aws cloudformation describe-stacks --stack-name my-app-stack
Common failure causes:
--capabilities CAPABILITY_IAM and role trust policiesaws cloudformation validate-template before deployingGenerates architecture patterns based on requirements.
python scripts/architecture_designer.py --input requirements.json --output design.json
Analyzes costs and recommends optimizations: idle removal, right-sizing, reserved capacity, storage tier transitions.
python scripts/cost_optimizer.py --resources inventory.json --monthly-spend 5000
| Scenario | Architecture | Estimated Cost |
|---|---|---|
| MVP Backend (<1k users) | Lambda + API Gateway + DynamoDB + Cognito + S3/CloudFront | $20-50/mo |
| Scaling SaaS (50k users) | ECS Fargate + Aurora Serverless + ElastiCache + CodePipeline | $500-2000/mo |
| Cost Optimization | Right-sizing + Savings Plans + storage lifecycle | Target 30% savings |
| IaC Generation | VPC + ALB + ECS Fargate + Aurora + IAM | Full template |
Once it runs, read only the file for the service at hand. Engine-level database work is in /database-ops, backups in /backup-strategy, incidents in /incident-response.
| Service | Reference | Covers |
|---|---|---|
| IAM | references/ops-iam.md | Roles over users, GitHub Actions through OIDC, auditing keys and policies, debugging AccessDenied |
| ECS on Fargate | references/ops-ecs-fargate.md | Task vs execution role, deploys with the circuit breaker, why tasks stop, scaling |
| Lambda | references/ops-lambda.md | Memory, timeout and concurrency, versions and aliases, async retries and SQS, debugging |
| RDS / Aurora | references/ops-rds.md | Production baseline, changes and Blue/Green, alarms, PITR and failover drills |
| S3 | references/ops-s3.md | Secure defaults, presigned URLs, lifecycle and cost, debugging access |
| VPC | references/ops-vpc.md | Subnet layout, NAT and endpoints, security groups, debugging connectivity |
| EC2 | references/ops-ec2.md | Launch templates and ASGs, IMDSv2, Session Manager, status checks |
| CloudTrail | references/ops-cloudtrail.md | Organization trail, alarms on sensitive events, investigating a principal |
| Secrets Manager | references/ops-secrets-manager.md | Secrets Manager vs Parameter Store, reading secrets per platform, rotation |
| Document | Contents |
|---|---|
references/architecture_patterns.md | 6 patterns: serverless, microservices, three-tier, data processing, GraphQL, multi-region |
references/service_selection.md | Decision matrices for compute, database, storage, messaging |
references/best_practices.md | Serverless design, cost optimization, security hardening, scalability |
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Plan, design, and implement A/B tests and experiments with statistical rigor. Covers hypothesis frameworks, sample sizing, metrics, and result analysis.
The English summary is being prepared. Showing the original description.
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The English summary is being prepared. Showing the original description.