Aws Solution Architect

# AWS Solution Architect

Design scalable, cost-effective AWS architectures for startups with infrastructure-as-code templates.

---

Workflow

Step 1: Gather Requirements

Collect application specifications:

• ```
• Application type (web app, mobile backend, data pipeline, SaaS)
• Expected users and requests per second
• Budget constraints (monthly spend limit)
• Team size and AWS experience level
• Compliance requirements (GDPR, HIPAA, SOC 2)
• Availability requirements (SLA, RPO/RTO)
• ```

Step 2: Design Architecture

Run the architecture designer to get pattern recommendations:

```bash python scripts/architecture_designer.py --input requirements.json ```

Example output:

```json { "recommended_pattern": "serverless_web", "service_stack": ["S3", "CloudFront", "API Gateway", "Lambda", "DynamoDB", "Cognito"], "estimated_monthly_cost_usd": 35, "pros": ["Low ops overhead", "Pay-per-use", "Auto-scaling"], "cons": ["Cold starts", "15-min Lambda limit", "Eventual consistency"] } ```

• Select from recommended patterns:
• Serverless Web: S3 + CloudFront + API Gateway + Lambda + DynamoDB
• Event-Driven Microservices: EventBridge + Lambda + SQS + Step Functions
• Three-Tier: ALB + ECS Fargate + Aurora + ElastiCache
• GraphQL Backend: AppSync + Lambda + DynamoDB + Cognito

See `references/architecture_patterns.md` for detailed pattern specifications.

Validation checkpoint: Confirm the recommended pattern matches the team's operational maturity and compliance requirements before proceeding to Step 3.

Step 3: Generate IaC Templates

Create infrastructure-as-code for the selected pattern:

```bash # Serverless stack (CloudFormation) python scripts/serverless_stack.py --app-name my-app --region us-east-1 ```

Example CloudFormation YAML output (core serverless resources):

```yaml AWSTemplateFormatVersion: '2010-09-09' Transform: AWS::Serverless-2016-10-31

Parameters: AppName: Type: String Default: my-app

Resources: ApiFunction: Type: AWS::Serverless::Function Properties: Handler: index.handler Runtime: nodejs20.x MemorySize: 512 Timeout: 30 Environment: Variables: TABLE_NAME: !Ref DataTable Policies: - DynamoDBCrudPolicy: TableName: !Ref DataTable Events: ApiEvent: Type: Api Properties: Path: /{proxy+} Method: ANY

DataTable: Type: AWS::DynamoDB::Table Properties: BillingMode: PAY_PER_REQUEST AttributeDefinitions: - AttributeName: pk AttributeType: S - AttributeName: sk AttributeType: S KeySchema: - AttributeName: pk KeyType: HASH - AttributeName: sk KeyType: RANGE ```

> Full templates including API Gateway, Cognito, IAM roles, and CloudWatch logging are generated by `serverless_stack.py` and also available in `references/architecture_patterns.md`.

Example CDK TypeScript snippet (three-tier pattern):

```typescript import * as ecs from 'aws-cdk-lib/aws-ecs'; import * as ec2 from 'aws-cdk-lib/aws-ec2'; import * as rds from 'aws-cdk-lib/aws-rds';

const vpc = new ec2.Vpc(this, 'AppVpc', { maxAzs: 2 });

const cluster = new ecs.Cluster(this, 'AppCluster', { vpc });

const db = new rds.ServerlessCluster(this, 'AppDb', { engine: rds.DatabaseClusterEngine.auroraPostgres({ version: rds.AuroraPostgresEngineVersion.VER_15_2, }), vpc, scaling: { minCapacity: 0.5, maxCapacity: 4 }, }); ```

Step 4: Review Costs

Analyze estimated costs and optimization opportunities:

```bash python scripts/cost_optimizer.py --resources current_setup.json --monthly-spend 2000 ```

Example output:

```json { "current_monthly_usd": 2000, "recommendations": [ { "action": "Right-size RDS db.r5.2xlarge → db.r5.large", "savings_usd": 420, "priority": "high" }, { "action": "Purchase 1-yr Compute Savings Plan at 40% utilization", "savings_usd": 310, "priority": "high" }, { "action": "Move S3 objects >90 days to Glacier Instant Retrieval", "savings_usd": 85, "priority": "medium" } ], "total_potential_savings_usd": 815 } ```

• Output includes:
• Monthly cost breakdown by service
• Right-sizing recommendations
• Savings Plans opportunities
• Potential monthly savings

Step 5: Deploy

Deploy the generated infrastructure:

```bash # 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 ```

Step 6: Validate and Handle Failures

Verify deployment and set up monitoring:

```bash # Check stack status aws cloudformation describe-stacks --stack-name my-app-stack

# Set up CloudWatch alarms aws cloudwatch put-metric-alarm --alarm-name high-errors ... ```

If stack creation fails:

1. Check the failure reason:
2. ```bash
3. aws cloudformation describe-stack-events \
4. --stack-name my-app-stack \
5. --query 'StackEvents[?ResourceStatus==`CREATE_FAILED`]'
6. ```
7. Review CloudWatch Logs for Lambda or ECS errors.
8. Fix the template or resource configuration.
9. Delete the failed stack before retrying:
10. ```bash
11. aws cloudformation delete-stack --stack-name my-app-stack
12. # Wait for deletion
13. aws cloudformation wait stack-delete-complete --stack-name my-app-stack
14. # Redeploy
15. aws cloudformation create-stack ...
16. ```

• Common failure causes:
• IAM permission errors → verify `--capabilities CAPABILITY_IAM` and role trust policies
• Resource limit exceeded → request quota increase via Service Quotas console
• Invalid template syntax → run `aws cloudformation validate-template --template-body file://template.yaml` before deploying

---

Tools

architecture_designer.py

Generates architecture patterns based on requirements.

```bash python scripts/architecture_designer.py --input requirements.json --output design.json ```

Input: JSON with app type, scale, budget, compliance needs Output: Recommended pattern, service stack, cost estimate, pros/cons

serverless_stack.py

Creates serverless CloudFormation templates.

```bash python scripts/serverless_stack.py --app-name my-app --region us-east-1 ```

• Output: Production-ready CloudFormation YAML with:
• API Gateway + Lambda
• DynamoDB table
• Cognito user pool
• IAM roles with least privilege
• CloudWatch logging

cost_optimizer.py

Analyzes costs and recommends optimizations.

```bash python scripts/cost_optimizer.py --resources inventory.json --monthly-spend 5000 ```

• Output: Recommendations for:
• Idle resource removal
• Instance right-sizing
• Reserved capacity purchases
• Storage tier transitions
• NAT Gateway alternatives

---

Quick Start

MVP Architecture (< $100/month)

``` Ask: "Design a serverless MVP backend for a mobile app with 1000 users"

• Result:
• Lambda + API Gateway for API
• DynamoDB pay-per-request for data
• Cognito for authentication
• S3 + CloudFront for static assets
• Estimated: $20-50/month
• ```

Scaling Architecture ($500-2000/month)

``` Ask: "Design a scalable architecture for a SaaS platform with 50k users"

• Result:
• ECS Fargate for containerized API
• Aurora Serverless for relational data
• ElastiCache for session caching
• CloudFront for CDN
• CodePipeline for CI/CD
• Multi-AZ deployment
• ```

Cost Optimization

``` Ask: "Optimize my AWS setup to reduce costs by 30%. Current spend: $3000/month"

Provide: Current resource inventory (EC2, RDS, S3, etc.)

• Result:
• Idle resource identification
• Right-sizing recommendations
• Savings Plans analysis
• Storage lifecycle policies
• Target savings: $900/month
• ```

IaC Generation

``` Ask: "Generate CloudFormation for a three-tier web app with auto-scaling"

• Result:
• VPC with public/private subnets
• ALB with HTTPS
• ECS Fargate with auto-scaling
• Aurora with read replicas
• Security groups and IAM roles
• ```

---

Input Requirements

Provide these details for architecture design:

| Requirement | Description | Example | |-------------|-------------|---------| | Application type | What you're building | SaaS platform, mobile backend | | Expected scale | Users, requests/sec | 10k users, 100 RPS | | Budget | Monthly AWS limit | $500/month max | | Team context | Size, AWS experience | 3 devs, intermediate | | Compliance | Regulatory needs | HIPAA, GDPR, SOC 2 | | Availability | Uptime requirements | 99.9% SLA, 1hr RPO |

JSON Format:

```json { "application_type": "saas_platform", "expected_users": 10000, "requests_per_second": 100, "budget_monthly_usd": 500, "team_size": 3, "aws_experience": "intermediate", "compliance": ["SOC2"], "availability_sla": "99.9%" } ```

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Output Formats

Architecture Design

• Pattern recommendation with rationale
• Service stack diagram (ASCII)
• Monthly cost estimate and trade-offs

IaC Templates

• CloudFormation YAML: Production-ready SAM/CFN templates
• CDK TypeScript: Type-safe infrastructure code
• Terraform HCL: Multi-cloud compatible configs

Cost Analysis

• Current spend breakdown with optimization recommendations
• Priority action list (high/medium/low) and implementation checklist

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Reference Documentation

| 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 |