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AWS Architecture Patterns for Startups

Reference guide for selecting the right AWS architecture pattern based on application requirements.

Pattern Selection Matrix
Pattern 1: Serverless Web Application
Pattern 2: Event-Driven Microservices
Pattern 3: Modern Three-Tier Application
Pattern 4: Real-Time Data Processing
Pattern 5: GraphQL API Backend
Pattern 6: Multi-Region High Availability

Pattern Selection Matrix

Pattern	Best For	Users	Monthly Cost	Complexity
Serverless Web	MVP, SaaS, mobile backend	<50K	$50-500	Low
Event-Driven Microservices	Complex workflows, async processing	Any	$100-1000	Medium
Three-Tier	Traditional web, e-commerce	10K-500K	$300-2000	Medium
Real-Time Data	Analytics, IoT, streaming	Any	$200-1500	High
GraphQL Backend	Mobile apps, SPAs	<100K	$50-400	Medium
Multi-Region HA	Global apps, DR requirements	>100K	1.5-2x single	High

Pattern 1: Serverless Web Application

Use Case

SaaS platforms, mobile backends, low-traffic websites, MVPs

Architecture Diagram

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│  CloudFront │────▶│     S3      │     │   Cognito   │
│    (CDN)    │     │  (Static)   │     │   (Auth)    │
└─────────────┘     └─────────────┘     └──────┬──────┘
                                               │
┌─────────────┐     ┌─────────────┐     ┌──────▼──────┐
│   Route 53  │────▶│ API Gateway │────▶│   Lambda    │
│    (DNS)    │     │   (REST)    │     │ (Functions) │
└─────────────┘     └─────────────┘     └──────┬──────┘
                                               │
                                        ┌──────▼──────┐
                                        │  DynamoDB   │
                                        │ (Database)  │
                                        └─────────────┘

Service Stack

Layer	Service	Configuration
Frontend	S3 + CloudFront	Static hosting with HTTPS
API	API Gateway + Lambda	REST endpoints with throttling
Database	DynamoDB	Pay-per-request billing
Auth	Cognito	User pools with MFA support
CI/CD	Amplify or CodePipeline	Automated deployments

CloudFormation Template

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

Resources:
  # API Function
  ApiFunction:
    Type: AWS::Serverless::Function
    Properties:
      Runtime: nodejs18.x
      Handler: index.handler
      MemorySize: 512
      Timeout: 10
      Events:
        Api:
          Type: Api
          Properties:
            Path: /{proxy+}
            Method: ANY

  # DynamoDB Table
  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

Cost Breakdown (10K users)

Service	Monthly Cost
Lambda	$5-20
API Gateway	$10-30
DynamoDB	$10-50
CloudFront	$5-15
S3	$1-5
Cognito	$0-50
Total	$31-170

Pros and Cons

Pros:

Zero server management
Pay only for what you use
Auto-scaling built-in
Low operational overhead

Cons:

Cold start latency (100-500ms)
15-minute Lambda execution limit
Vendor lock-in

Pattern 2: Event-Driven Microservices

Use Case

Complex business workflows, asynchronous processing, decoupled systems

Architecture Diagram

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│   Service   │────▶│ EventBridge │────▶│   Service   │
│      A      │     │  (Event Bus)│     │      B      │
└─────────────┘     └──────┬──────┘     └─────────────┘
                           │
                    ┌──────▼──────┐
                    │     SQS     │
                    │   (Queue)   │
                    └──────┬──────┘
                           │
┌─────────────┐     ┌──────▼──────┐     ┌─────────────┐
│    Step     │◀────│   Lambda    │────▶│  DynamoDB   │
│  Functions  │     │ (Processor) │     │  (Storage)  │
└─────────────┘     └─────────────┘     └─────────────┘

Service Stack

Layer	Service	Purpose
Events	EventBridge	Central event bus
Processing	Lambda or ECS Fargate	Event handlers
Queue	SQS	Dead letter queue for failures
Orchestration	Step Functions	Complex workflow state
Storage	DynamoDB, S3	Persistent data

Event Schema Example

{
  "source": "orders.service",
  "detail-type": "OrderCreated",
  "detail": {
    "orderId": "ord-12345",
    "customerId": "cust-67890",
    "items": [...],
    "total": 99.99,
    "timestamp": "2024-01-15T10:30:00Z"
  }
}

Cost Breakdown

Service	Monthly Cost
EventBridge	$1-10
Lambda	$20-100
SQS	$5-20
Step Functions	$25-100
DynamoDB	$20-100
Total	$71-330

Pros and Cons

Pros:

Loose coupling between services
Independent scaling per service
Failure isolation
Easy to test individually

Cons:

Distributed system complexity
Eventual consistency
Harder to debug

Pattern 3: Modern Three-Tier Application

Use Case

Traditional web apps, e-commerce, CMS, applications with complex queries

Architecture Diagram

┌─────────────┐     ┌─────────────┐
│  CloudFront │────▶│     ALB     │
│    (CDN)    │     │ (Load Bal.) │
└─────────────┘     └──────┬──────┘
                           │
                    ┌──────▼──────┐
                    │ ECS Fargate │
                    │ (Auto-scale)│
                    └──────┬──────┘
                           │
        ┌──────────────────┼──────────────────┐
        │                  │                  │
 ┌──────▼──────┐    ┌──────▼──────┐    ┌──────▼──────┐
 │   Aurora    │    │ ElastiCache │    │     S3      │
 │ (Database)  │    │   (Redis)   │    │  (Storage)  │
 └─────────────┘    └─────────────┘    └─────────────┘

Service Stack

Layer	Service	Configuration
CDN	CloudFront	Edge caching, HTTPS
Load Balancer	ALB	Path-based routing, health checks
Compute	ECS Fargate	Container auto-scaling
Database	Aurora MySQL/PostgreSQL	Multi-AZ, auto-scaling
Cache	ElastiCache Redis	Session, query caching
Storage	S3	Static assets, uploads

Terraform Example

# ECS Service with Auto-scaling
resource "aws_ecs_service" "app" {
  name            = "app-service"
  cluster         = aws_ecs_cluster.main.id
  task_definition = aws_ecs_task_definition.app.arn
  desired_count   = 2

  capacity_provider_strategy {
    capacity_provider = "FARGATE"
    weight            = 100
  }

  load_balancer {
    target_group_arn = aws_lb_target_group.app.arn
    container_name   = "app"
    container_port   = 3000
  }
}

# Auto-scaling Policy
resource "aws_appautoscaling_target" "app" {
  max_capacity       = 10
  min_capacity       = 2
  resource_id        = "service/${aws_ecs_cluster.main.name}/${aws_ecs_service.app.name}"
  scalable_dimension = "ecs:service:DesiredCount"
  service_namespace  = "ecs"
}

Cost Breakdown (50K users)

Service	Monthly Cost
ECS Fargate (2 tasks)	$100-200
ALB	$25-50
Aurora	$100-300
ElastiCache	$50-100
CloudFront	$20-50
Total	$295-700

Pattern 4: Real-Time Data Processing

Use Case

Analytics, IoT data ingestion, log processing, streaming data

Architecture Diagram

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│  IoT Core   │────▶│   Kinesis   │────▶│   Lambda    │
│  (Devices)  │     │  (Stream)   │     │ (Process)   │
└─────────────┘     └─────────────┘     └──────┬──────┘
                                               │
┌─────────────┐     ┌─────────────┐     ┌──────▼──────┐
│  QuickSight │◀────│   Athena    │◀────│     S3      │
│   (Viz)     │     │  (Query)    │     │ (Data Lake) │
└─────────────┘     └─────────────┘     └─────────────┘
                                               │
                                        ┌──────▼──────┐
                                        │  CloudWatch │
                                        │  (Alerts)   │
                                        └─────────────┘

Service Stack

Layer	Service	Purpose
Ingestion	Kinesis Data Streams	Real-time data capture
Processing	Lambda or Kinesis Analytics	Transform and analyze
Storage	S3 (data lake)	Long-term storage
Query	Athena	SQL queries on S3
Visualization	QuickSight	Dashboards and reports
Alerting	CloudWatch + SNS	Threshold-based alerts

Kinesis Producer Example

import boto3
import json

kinesis = boto3.client('kinesis')

def send_event(stream_name, data, partition_key):
    response = kinesis.put_record(
        StreamName=stream_name,
        Data=json.dumps(data),
        PartitionKey=partition_key
    )
    return response['SequenceNumber']

# Send sensor reading
send_event(
    'sensor-stream',
    {'sensor_id': 'temp-01', 'value': 23.5, 'unit': 'celsius'},
    'sensor-01'
)

Cost Breakdown

Service	Monthly Cost
Kinesis (1 shard)	$15-30
Lambda	$10-50
S3	$5-50
Athena	$5-25
QuickSight	$24+
Total	$59-179

Pattern 5: GraphQL API Backend

Use Case

Mobile apps, single-page applications, flexible data queries

Architecture Diagram

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│  Mobile App │────▶│   AppSync   │────▶│   Lambda    │
│   or SPA    │     │  (GraphQL)  │     │ (Resolvers) │
└─────────────┘     └──────┬──────┘     └─────────────┘
                           │
                    ┌──────▼──────┐
                    │  DynamoDB   │
                    │  (Direct)   │
                    └──────┬──────┘
                           │
                    ┌──────▼──────┐
                    │   Cognito   │
                    │   (Auth)    │
                    └─────────────┘

AppSync Schema Example

type Query {
  getUser(id: ID!): User
  listPosts(limit: Int, nextToken: String): PostConnection
}

type Mutation {
  createPost(input: CreatePostInput!): Post
  updatePost(input: UpdatePostInput!): Post
}

type Subscription {
  onCreatePost: Post @aws_subscribe(mutations: ["createPost"])
}

type User {
  id: ID!
  email: String!
  posts: [Post]
}

type Post {
  id: ID!
  title: String!
  content: String!
  author: User!
  createdAt: AWSDateTime!
}

Cost Breakdown

Service	Monthly Cost
AppSync	$4-40
Lambda	$5-30
DynamoDB	$10-50
Cognito	$0-50
Total	$19-170

Pattern 6: Multi-Region High Availability

Use Case

Global applications, disaster recovery, data sovereignty compliance

Architecture Diagram

                    ┌─────────────┐
                    │  Route 53   │
                    │(Geo routing)│
                    └──────┬──────┘
                           │
          ┌────────────────┼────────────────┐
          │                                 │
   ┌──────▼──────┐                   ┌──────▼──────┐
   │ us-east-1   │                   │ eu-west-1   │
   │ CloudFront  │                   │ CloudFront  │
   └──────┬──────┘                   └──────┬──────┘
          │                                 │
   ┌──────▼──────┐                   ┌──────▼──────┐
   │ ECS/Lambda  │                   │ ECS/Lambda  │
   └──────┬──────┘                   └──────┬──────┘
          │                                 │
   ┌──────▼──────┐◀── Replication ──▶┌──────▼──────┐
   │  DynamoDB   │                   │  DynamoDB   │
   │Global Table │                   │Global Table │
   └─────────────┘                   └─────────────┘

Service Stack

Component	Service	Configuration
DNS	Route 53	Geolocation or latency routing
CDN	CloudFront	Multiple origins per region
Compute	Lambda or ECS	Deployed in each region
Database	DynamoDB Global Tables	Automatic replication
Storage	S3 CRR	Cross-region replication

Route 53 Failover Policy

# Primary record
HealthCheck:
  Type: AWS::Route53::HealthCheck
  Properties:
    HealthCheckConfig:
      Port: 443
      Type: HTTPS
      ResourcePath: /health
      FullyQualifiedDomainName: api-us-east-1.example.com

RecordSetPrimary:
  Type: AWS::Route53::RecordSet
  Properties:
    Name: api.example.com
    Type: A
    SetIdentifier: primary
    Failover: PRIMARY
    HealthCheckId: !Ref HealthCheck
    AliasTarget:
      DNSName: !GetAtt USEast1ALB.DNSName
      HostedZoneId: !GetAtt USEast1ALB.CanonicalHostedZoneID

Cost Considerations

Factor	Impact
Compute	2x (each region)
Database	25% premium for global tables
Data Transfer	Cross-region replication costs
Route 53	Health checks + geo queries
Total	1.5-2x single region

Pattern Comparison Summary

Latency

Pattern	Typical Latency
Serverless	50-200ms (cold: 500ms+)
Three-Tier	20-100ms
GraphQL	30-150ms
Multi-Region	<50ms (regional)

Scaling Characteristics

Pattern	Scale Limit	Scale Speed
Serverless	1000 concurrent/function	Instant
Three-Tier	Instance limits	Minutes
Event-Driven	Unlimited	Instant
Multi-Region	Regional limits	Instant

Operational Complexity

Pattern	Setup	Maintenance	Debugging
Serverless	Low	Low	Medium
Three-Tier	Medium	Medium	Low
Event-Driven	High	Medium	High
Multi-Region	High	High	High

17 KiB Raw Blame History

AWS Architecture Patterns for Startups

Table of Contents

Pattern Selection Matrix

Pattern 1: Serverless Web Application

Use Case

Architecture Diagram

Service Stack

CloudFormation Template

Cost Breakdown (10K users)

Pros and Cons

Pattern 2: Event-Driven Microservices

Use Case

Architecture Diagram

Service Stack

Event Schema Example

Cost Breakdown

Pros and Cons

Pattern 3: Modern Three-Tier Application

Use Case

Architecture Diagram

Service Stack

Terraform Example

Cost Breakdown (50K users)

Pattern 4: Real-Time Data Processing

Use Case

Architecture Diagram

Service Stack

Kinesis Producer Example

Cost Breakdown

Pattern 5: GraphQL API Backend

Use Case

Architecture Diagram

AppSync Schema Example

Cost Breakdown

Pattern 6: Multi-Region High Availability

Use Case

Architecture Diagram

Service Stack

Route 53 Failover Policy

Cost Considerations

Pattern Comparison Summary

Latency

Scaling Characteristics

Operational Complexity

17 KiB

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