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Tutorials › AWS Solutions Architect › AWS Architecture Patterns

AWS Architecture Patterns

5 min read Quiz at the end
Learn the four key architecture patterns: serverless, three-tier HA, event-driven, and data lake. Understand when to apply each pattern.

Common AWS Architecture Patterns

A Solutions Architect must recognise and apply proven patterns. These patterns appear repeatedly in the SAA-C03 exam and in real-world AWS architectures.

Pattern 1 — Serverless Web Application

Route 53 --> CloudFront --> API Gateway --> Lambda --> DynamoDB
                |                                      |
                v                                      v
              S3 (static files)               ElastiCache (caching)

Benefits: Zero servers, auto-scale to millions, pay per request
Best for: New applications, variable traffic, mobile backends

Pattern 2 — Three-Tier High Availability

Internet --> Route 53 --> ALB (2 AZs)
                              |
                    Auto Scaling Group
                  EC2 in Private Subnets
                  (us-east-1a + us-east-1b)
                              |
                   RDS Multi-AZ + Read Replicas
                   ElastiCache (Redis)

Benefits: Handles failures, scales with traffic
Best for: Traditional web apps, complex SQL, stateful sessions

Pattern 3 — Event-Driven Decoupled Processing

S3 Upload --> S3 Event --> SNS Topic
                               |
              +----------------+----------------+
              |                |                |
          SQS Queue        SQS Queue        Lambda
              |                |            (immediate)
          Lambda            Lambda
        (process image)   (send email)

Benefits: Components fail independently, auto-retry, scales separately
Best for: File processing, order processing, notifications

Pattern 4 — Data Lake and Analytics

Various Sources --> Kinesis Firehose --> S3 (Raw Data)
                                              |
                                            Glue ETL
                                              |
                                        S3 (Clean Parquet)
                                              |
                               Athena (SQL) + QuickSight (dashboards)

Benefits: Petabyte-scale, serverless queries, pay per query
Best for: Analytics, business intelligence, log analysis

Key Design Principles

  • Design for FAILURE: assume everything can fail — use Multi-AZ, health checks, auto-recovery
  • Use MANAGED services: RDS instead of MySQL on EC2, Lambda instead of EC2 for event processing
  • DECOUPLE components: SQS between services so one slow component does not block others
  • SCALE HORIZONTALLY: add more small servers instead of making one server bigger
  • Keep STATELESS: store session data in ElastiCache or DynamoDB, not on the EC2 instance
Exam Tip: The SAA-C03 exam tests whether you can identify the RIGHT pattern for requirements. Key clues: 'scalable and cost-effective' = serverless pattern. 'Legacy relational database' = three-tier HA. 'Process files asynchronously' = event-driven. 'Analyse petabytes of logs' = data lake.
Topic Quiz · 2 questions

Test your understanding before moving on

1. A startup wants to build a mobile application backend. Traffic will be low initially but could grow to millions of users. There are no servers to manage. Which pattern is BEST?
💡 The serverless pattern (API Gateway + Lambda + DynamoDB) scales from zero to millions automatically, has no server management overhead, and charges only for actual usage — perfect for unknown growth.
2. A company needs to process uploaded images: resize them, extract metadata, and send a notification email. The order of processing does not matter. Which pattern is BEST?
💡 The event-driven pattern with SNS fan-out means each task (resize, extract metadata, send email) is handled by a dedicated Lambda via its own SQS queue — independently, in parallel, with automatic retry.