Aws solution architect
Design AWS architectures for startups using serverless patterns and IaC templates.
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Source of Aws solution architect
Show the full text382 lines
| name | description |
|---|---|
| aws-solution-architect | Design AWS architectures for startups using serverless patterns and IaC templates. Use when asked to design serverless architecture, create CloudFormation templates, optimize AWS costs, set up CI/CD pipelines, or migrate to AWS. Covers Lambda, API Gateway, DynamoDB, ECS, Aurora, and cost optimization. |
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:
python scripts/architecture_designer.py --input requirements.json
Example output:
{
"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:
# Serverless stack (CloudFormation)
python scripts/serverless_stack.py --app-name my-app --region us-east-1
Example CloudFormation YAML output (core serverless resources):
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.pyand also available inreferences/architecture_patterns.md.
Example CDK TypeScript snippet (three-tier pattern):
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:
python scripts/cost_optimizer.py --resources current_setup.json --monthly-spend 2000
Example output:
{
"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:
# 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:
# 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:
- Check the failure reason:
aws cloudformation describe-stack-events \ --stack-name my-app-stack \ --query 'StackEvents[?ResourceStatus==`CREATE_FAILED`]' - Review CloudWatch Logs for Lambda or ECS errors.
- Fix the template or resource configuration.
- Delete the failed stack before retrying:
aws cloudformation delete-stack --stack-name my-app-stack # Wait for deletion aws cloudformation wait stack-delete-complete --stack-name my-app-stack # Redeploy aws cloudformation create-stack ...
Common failure causes:
- IAM permission errors → verify
--capabilities CAPABILITY_IAMand 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.yamlbefore deploying
Tools
architecture_designer.py
Generates architecture patterns based on requirements.
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.
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.
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:
{
"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%"
}
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
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 |
| 1 | |
| 2 | name "aws-solution-architect" |
| 3 | description Design AWS architectures for startups using serverless patterns and IaC templates. Use when asked to design serverless architecture, create CloudFormation templates, optimize AWS costs, set up CI/CD pipelines, or migrate to AWS. Covers Lambda, API Gateway, DynamoDB, ECS, Aurora, and cost optimization. |
| 4 | |
| 5 | |
| 6 | # AWS Solution Architect |
| 7 | |
| 8 | Design scalable, cost-effective AWS architectures for startups with infrastructure-as-code templates. |
| 9 | |
| 10 | |
| 11 | |
| 12 | ## Workflow |
| 13 | |
| 14 | ### Step 1: Gather Requirements |
| 15 | |
| 16 | Collect application specifications: |
| 17 | |
| 18 | |
| 19 | - Application type (web app, mobile backend, data pipeline, SaaS) |
| 20 | - Expected users and requests per second |
| 21 | - Budget constraints (monthly spend limit) |
| 22 | - Team size and AWS experience level |
| 23 | - Compliance requirements (GDPR, HIPAA, SOC 2) |
| 24 | - Availability requirements (SLA, RPO/RTO) |
| 25 | |
| 26 | |
| 27 | ### Step 2: Design Architecture |
| 28 | |
| 29 | Run the architecture designer to get pattern recommendations: |
| 30 | |
| 31 | |
| 32 | python scripts/architecture_designer.py --input requirements.json |
| 33 | |
| 34 | |
| 35 | **Example output:** |
| 36 | |
| 37 | |
| 38 | { |
| 39 | "recommended_pattern": "serverless_web", |
| 40 | "service_stack": ["S3", "CloudFront", "API Gateway", "Lambda", "DynamoDB", "Cognito"], |
| 41 | "estimated_monthly_cost_usd": 35, |
| 42 | "pros": ["Low ops overhead", "Pay-per-use", "Auto-scaling"], |
| 43 | "cons": ["Cold starts", "15-min Lambda limit", "Eventual consistency"] |
| 44 | } |
| 45 | |
| 46 | |
| 47 | Select from recommended patterns: |
| 48 | **Serverless Web**: S3 + CloudFront + API Gateway + Lambda + DynamoDB |
| 49 | **Event-Driven Microservices**: EventBridge + Lambda + SQS + Step Functions |
| 50 | **Three-Tier**: ALB + ECS Fargate + Aurora + ElastiCache |
| 51 | **GraphQL Backend**: AppSync + Lambda + DynamoDB + Cognito |
| 52 | |
| 53 | See `references/architecture_patterns.md` for detailed pattern specifications. |
| 54 | |
| 55 | **Validation checkpoint:** Confirm the recommended pattern matches the team's operational maturity and compliance requirements before proceeding to Step 3. |
| 56 | |
| 57 | ### Step 3: Generate IaC Templates |
| 58 | |
| 59 | Create infrastructure-as-code for the selected pattern: |
| 60 | |
| 61 | |
| 62 | # Serverless stack (CloudFormation) |
| 63 | python scripts/serverless_stack.py --app-name my-app --region us-east-1 |
| 64 | |
| 65 | |
| 66 | **Example CloudFormation YAML output (core serverless resources):** |
| 67 | |
| 68 | |
| 69 | AWSTemplateFormatVersion: '2010-09-09' |
| 70 | Transform: AWS::Serverless-2016-10-31 |
| 71 | |
| 72 | Parameters: |
| 73 | AppName: |
| 74 | Type: String |
| 75 | Default: my-app |
| 76 | |
| 77 | Resources: |
| 78 | ApiFunction: |
| 79 | Type: AWS::Serverless::Function |
| 80 | Properties: |
| 81 | Handler: index.handler |
| 82 | Runtime: nodejs20.x |
| 83 | MemorySize: 512 |
| 84 | Timeout: 30 |
| 85 | Environment: |
| 86 | Variables: |
| 87 | TABLE_NAME: !Ref DataTable |
| 88 | Policies: |
| 89 | - DynamoDBCrudPolicy: |
| 90 | TableName: !Ref DataTable |
| 91 | Events: |
| 92 | ApiEvent: |
| 93 | Type: Api |
| 94 | Properties: |
| 95 | Path: /{proxy+} |
| 96 | Method: ANY |
| 97 | |
| 98 | DataTable: |
| 99 | Type: AWS::DynamoDB::Table |
| 100 | Properties: |
| 101 | BillingMode: PAY_PER_REQUEST |
| 102 | AttributeDefinitions: |
| 103 | - AttributeName: pk |
| 104 | AttributeType: S |
| 105 | - AttributeName: sk |
| 106 | AttributeType: S |
| 107 | KeySchema: |
| 108 | - AttributeName: pk |
| 109 | KeyType: HASH |
| 110 | - AttributeName: sk |
| 111 | KeyType: RANGE |
| 112 | |
| 113 | |
| 114 | > 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`. |
| 115 | |
| 116 | **Example CDK TypeScript snippet (three-tier pattern):** |
| 117 | |
| 118 | |
| 119 | import * as ecs from 'aws-cdk-lib/aws-ecs'; |
| 120 | import * as ec2 from 'aws-cdk-lib/aws-ec2'; |
| 121 | import * as rds from 'aws-cdk-lib/aws-rds'; |
| 122 | |
| 123 | const vpc = new ec2.Vpc(this, 'AppVpc', { maxAzs: 2 }); |
| 124 | |
| 125 | const cluster = new ecs.Cluster(this, 'AppCluster', { vpc }); |
| 126 | |
| 127 | const db = new rds.ServerlessCluster(this, 'AppDb', { |
| 128 | engine: rds.DatabaseClusterEngine.auroraPostgres({ |
| 129 | version: rds.AuroraPostgresEngineVersion.VER_15_2, |
| 130 | }), |
| 131 | vpc, |
| 132 | scaling: { minCapacity: 0.5, maxCapacity: 4 }, |
| 133 | }); |
| 134 | |
| 135 | |
| 136 | ### Step 4: Review Costs |
| 137 | |
| 138 | Analyze estimated costs and optimization opportunities: |
| 139 | |
| 140 | |
| 141 | python scripts/cost_optimizer.py --resources current_setup.json --monthly-spend 2000 |
| 142 | |
| 143 | |
| 144 | **Example output:** |
| 145 | |
| 146 | |
| 147 | { |
| 148 | "current_monthly_usd": 2000, |
| 149 | "recommendations": [ |
| 150 | { "action": "Right-size RDS db.r5.2xlarge → db.r5.large", "savings_usd": 420, "priority": "high" }, |
| 151 | { "action": "Purchase 1-yr Compute Savings Plan at 40% utilization", "savings_usd": 310, "priority": "high" }, |
| 152 | { "action": "Move S3 objects >90 days to Glacier Instant Retrieval", "savings_usd": 85, "priority": "medium" } |
| 153 | ], |
| 154 | "total_potential_savings_usd": 815 |
| 155 | } |
| 156 | |
| 157 | |
| 158 | Output includes: |
| 159 | Monthly cost breakdown by service |
| 160 | Right-sizing recommendations |
| 161 | Savings Plans opportunities |
| 162 | Potential monthly savings |
| 163 | |
| 164 | ### Step 5: Deploy |
| 165 | |
| 166 | Deploy the generated infrastructure: |
| 167 | |
| 168 | |
| 169 | # CloudFormation |
| 170 | aws cloudformation create-stack \ |
| 171 | --stack-name my-app-stack \ |
| 172 | --template-body file://template.yaml \ |
| 173 | --capabilities CAPABILITY_IAM |
| 174 | |
| 175 | # CDK |
| 176 | cdk deploy |
| 177 | |
| 178 | # Terraform |
| 179 | terraform init && terraform apply |
| 180 | |
| 181 | |
| 182 | ### Step 6: Validate and Handle Failures |
| 183 | |
| 184 | Verify deployment and set up monitoring: |
| 185 | |
| 186 | |
| 187 | # Check stack status |
| 188 | aws cloudformation describe-stacks --stack-name my-app-stack |
| 189 | |
| 190 | # Set up CloudWatch alarms |
| 191 | aws cloudwatch put-metric-alarm --alarm-name high-errors ... |
| 192 | |
| 193 | |
| 194 | **If stack creation fails:** |
| 195 | |
| 196 | Check the failure reason: |
| 197 | |
| 198 | aws cloudformation describe-stack-events \ |
| 199 | --stack-name my-app-stack \ |
| 200 | --query 'StackEvents[?ResourceStatus==`CREATE_FAILED`]' |
| 201 | |
| 202 | Review CloudWatch Logs for Lambda or ECS errors. |
| 203 | Fix the template or resource configuration. |
| 204 | Delete the failed stack before retrying: |
| 205 | |
| 206 | aws cloudformation delete-stack --stack-name my-app-stack |
| 207 | # Wait for deletion |
| 208 | aws cloudformation wait stack-delete-complete --stack-name my-app-stack |
| 209 | # Redeploy |
| 210 | aws cloudformation create-stack ... |
| 211 | |
| 212 | |
| 213 | **Common failure causes:** |
| 214 | IAM permission errors → verify `--capabilities CAPABILITY_IAM` and role trust policies |
| 215 | Resource limit exceeded → request quota increase via Service Quotas console |
| 216 | Invalid template syntax → run `aws cloudformation validate-template --template-body file://template.yaml` before deploying |
| 217 | |
| 218 | |
| 219 | |
| 220 | ## Tools |
| 221 | |
| 222 | ### architecture_designer.py |
| 223 | |
| 224 | Generates architecture patterns based on requirements. |
| 225 | |
| 226 | |
| 227 | python scripts/architecture_designer.py --input requirements.json --output design.json |
| 228 | |
| 229 | |
| 230 | **Input:** JSON with app type, scale, budget, compliance needs |
| 231 | **Output:** Recommended pattern, service stack, cost estimate, pros/cons |
| 232 | |
| 233 | ### serverless_stack.py |
| 234 | |
| 235 | Creates serverless CloudFormation templates. |
| 236 | |
| 237 | |
| 238 | python scripts/serverless_stack.py --app-name my-app --region us-east-1 |
| 239 | |
| 240 | |
| 241 | **Output:** Production-ready CloudFormation YAML with: |
| 242 | API Gateway + Lambda |
| 243 | DynamoDB table |
| 244 | Cognito user pool |
| 245 | IAM roles with least privilege |
| 246 | CloudWatch logging |
| 247 | |
| 248 | ### cost_optimizer.py |
| 249 | |
| 250 | Analyzes costs and recommends optimizations. |
| 251 | |
| 252 | |
| 253 | python scripts/cost_optimizer.py --resources inventory.json --monthly-spend 5000 |
| 254 | |
| 255 | |
| 256 | **Output:** Recommendations for: |
| 257 | Idle resource removal |
| 258 | Instance right-sizing |
| 259 | Reserved capacity purchases |
| 260 | Storage tier transitions |
| 261 | NAT Gateway alternatives |
| 262 | |
| 263 | |
| 264 | |
| 265 | ## Quick Start |
| 266 | |
| 267 | ### MVP Architecture (< $100/month) |
| 268 | |
| 269 | |
| 270 | Ask: "Design a serverless MVP backend for a mobile app with 1000 users" |
| 271 | |
| 272 | Result: |
| 273 | - Lambda + API Gateway for API |
| 274 | - DynamoDB pay-per-request for data |
| 275 | - Cognito for authentication |
| 276 | - S3 + CloudFront for static assets |
| 277 | - Estimated: $20-50/month |
| 278 | |
| 279 | |
| 280 | ### Scaling Architecture ($500-2000/month) |
| 281 | |
| 282 | |
| 283 | Ask: "Design a scalable architecture for a SaaS platform with 50k users" |
| 284 | |
| 285 | Result: |
| 286 | - ECS Fargate for containerized API |
| 287 | - Aurora Serverless for relational data |
| 288 | - ElastiCache for session caching |
| 289 | - CloudFront for CDN |
| 290 | - CodePipeline for CI/CD |
| 291 | - Multi-AZ deployment |
| 292 | |
| 293 | |
| 294 | ### Cost Optimization |
| 295 | |
| 296 | |
| 297 | Ask: "Optimize my AWS setup to reduce costs by 30%. Current spend: $3000/month" |
| 298 | |
| 299 | Provide: Current resource inventory (EC2, RDS, S3, etc.) |
| 300 | |
| 301 | Result: |
| 302 | - Idle resource identification |
| 303 | - Right-sizing recommendations |
| 304 | - Savings Plans analysis |
| 305 | - Storage lifecycle policies |
| 306 | - Target savings: $900/month |
| 307 | |
| 308 | |
| 309 | ### IaC Generation |
| 310 | |
| 311 | |
| 312 | Ask: "Generate CloudFormation for a three-tier web app with auto-scaling" |
| 313 | |
| 314 | Result: |
| 315 | - VPC with public/private subnets |
| 316 | - ALB with HTTPS |
| 317 | - ECS Fargate with auto-scaling |
| 318 | - Aurora with read replicas |
| 319 | - Security groups and IAM roles |
| 320 | |
| 321 | |
| 322 | |
| 323 | |
| 324 | ## Input Requirements |
| 325 | |
| 326 | Provide these details for architecture design: |
| 327 | |
| 328 | | Requirement | Description | Example | |
| 329 | |-------------|-------------|---------| |
| 330 | | Application type | What you're building | SaaS platform, mobile backend | |
| 331 | | Expected scale | Users, requests/sec | 10k users, 100 RPS | |
| 332 | | Budget | Monthly AWS limit | $500/month max | |
| 333 | | Team context | Size, AWS experience | 3 devs, intermediate | |
| 334 | | Compliance | Regulatory needs | HIPAA, GDPR, SOC 2 | |
| 335 | | Availability | Uptime requirements | 99.9% SLA, 1hr RPO | |
| 336 | |
| 337 | **JSON Format:** |
| 338 | |
| 339 | |
| 340 | { |
| 341 | "application_type": "saas_platform", |
| 342 | "expected_users": 10000, |
| 343 | "requests_per_second": 100, |
| 344 | "budget_monthly_usd": 500, |
| 345 | "team_size": 3, |
| 346 | "aws_experience": "intermediate", |
| 347 | "compliance": ["SOC2"], |
| 348 | "availability_sla": "99.9%" |
| 349 | } |
| 350 | |
| 351 | |
| 352 | |
| 353 | |
| 354 | ## Output Formats |
| 355 | |
| 356 | ### Architecture Design |
| 357 | |
| 358 | Pattern recommendation with rationale |
| 359 | Service stack diagram (ASCII) |
| 360 | Monthly cost estimate and trade-offs |
| 361 | |
| 362 | ### IaC Templates |
| 363 | |
| 364 | **CloudFormation YAML**: Production-ready SAM/CFN templates |
| 365 | **CDK TypeScript**: Type-safe infrastructure code |
| 366 | **Terraform HCL**: Multi-cloud compatible configs |
| 367 | |
| 368 | ### Cost Analysis |
| 369 | |
| 370 | Current spend breakdown with optimization recommendations |
| 371 | Priority action list (high/medium/low) and implementation checklist |
| 372 | |
| 373 | |
| 374 | |
| 375 | ## Reference Documentation |
| 376 | |
| 377 | | Document | Contents | |
| 378 | |----------|----------| |
| 379 | | `references/architecture_patterns.md` | 6 patterns: serverless, microservices, three-tier, data processing, GraphQL, multi-region | |
| 380 | | `references/service_selection.md` | Decision matrices for compute, database, storage, messaging | |
| 381 | | `references/best_practices.md` | Serverless design, cost optimization, security hardening, scalability | |
| 382 |
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