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AWS Solutions Architect Associate Study Notes

Comprehensive study notes covering all SAA-C03 exam domains with detailed explanations, tables, and exam tips.

AWS Solutions Architect Associate Study Notes

Design Resilient Architectures

Multi-tier, scalable, and fault-tolerant designs

Domain Weight

This domain represents 26% of the exam. Focus on high availability, fault tolerance, and disaster recovery.

AWS Global Infrastructure

Component	Description	Key Use Cases
Regions	Geographic areas with 2+ AZs	Data residency, latency optimization, service availability
Availability Zones	Isolated data centers in a region	High availability, fault tolerance, multi-AZ deployments
Edge Locations	CDN points of presence (400+)	CloudFront caching, Route 53 DNS
Local Zones	AWS infrastructure closer to users	Low-latency applications, media rendering
Wavelength Zones	AWS in 5G networks	Ultra-low latency mobile applications

Multi-AZ Architecture Patterns

Active-Active

Traffic to all AZs simultaneously. Highest availability, requires stateless design or session management.

Active-Passive

Primary handles traffic, standby for failover. RDS Multi-AZ uses this pattern.

Pilot Light

Minimal resources running, scale up on disaster. Cost-effective DR strategy.

Warm Standby

Scaled-down but functional environment. Balance of cost and recovery time.

Exam Tip

For high availability: Multi-AZ (99.99% SLA). For disaster recovery: Multi-Region with appropriate RTO/RPO planning.

Decoupling Mechanisms

Loose coupling for resilience and scalability

Messaging Services

Service	Type	Use Cases	Key Features
SQS Standard	Queue	Decoupling, buffering, async processing	Unlimited throughput, at-least-once, best-effort ordering
SQS FIFO	Queue	Ordered processing, deduplication	300 TPS (3000 with batching), exactly-once, strict ordering
SNS	Pub/Sub	Fanout, notifications, event distribution	Push to multiple subscribers, filtering, various protocols
EventBridge	Event Bus	Event-driven architecture, SaaS integration	Schema registry, rules, 35+ AWS service targets
Amazon MQ	Message Broker	Migrate from ActiveMQ/RabbitMQ	Managed brokers, industry-standard protocols

Decoupling Patterns

Queue-Based Load Leveling

SQS absorbs traffic spikes, workers process at their own pace. Protects downstream services.

Fanout Pattern

SNS topic to multiple SQS queues. One message processed by multiple consumers differently.

Dead Letter Queue

Capture failed messages for analysis. Prevent message loss, debug issues.

Event Sourcing

Store events, not just current state. EventBridge + Lambda + DynamoDB.

SQS Visibility Timeout

Default is 30 seconds. If processing takes longer, message becomes visible again and may be processed twice. Set visibility timeout > expected processing time.

Scaling Strategies

Automatic capacity adjustment

EC2 Auto Scaling

Scaling Type	Description	Best For
Target Tracking	Maintain specific metric (e.g., 50% CPU)	Most common, simple to configure
Step Scaling	Scale based on CloudWatch alarm thresholds	More control, multiple scaling steps
Simple Scaling	Single adjustment per alarm	Legacy, use step scaling instead
Scheduled Scaling	Scale at specific times	Predictable traffic patterns
Predictive Scaling	ML-based forecasting	Recurring patterns, proactive scaling

Launch Templates vs Launch Configurations

Launch Templates (Recommended): Versioning, multiple instance types, Spot/On-Demand mix, T2 Unlimited
Launch Configurations (Legacy): Immutable, single instance type, being deprecated

Application Auto Scaling

DynamoDB

Scale read/write capacity. Target tracking on consumed capacity.

ECS

Scale tasks in a service. CPU/memory utilization targets.

Aurora

Scale read replicas. Based on connections or CPU.

Lambda

Provisioned concurrency scaling. Predictable latency.

Back to SAA-C03

AWS Solutions Architect Associate Study Notes

Comprehensive study notes covering all SAA-C03 exam domains with detailed explanations, tables, and exam tips.

AWS Solutions Architect Associate Study Notes

Design Resilient Architectures

Multi-tier, scalable, and fault-tolerant designs

Domain Weight

This domain represents 26% of the exam. Focus on high availability, fault tolerance, and disaster recovery.

AWS Global Infrastructure

Component	Description	Key Use Cases
Regions	Geographic areas with 2+ AZs	Data residency, latency optimization, service availability
Availability Zones	Isolated data centers in a region	High availability, fault tolerance, multi-AZ deployments
Edge Locations	CDN points of presence (400+)	CloudFront caching, Route 53 DNS
Local Zones	AWS infrastructure closer to users	Low-latency applications, media rendering
Wavelength Zones	AWS in 5G networks	Ultra-low latency mobile applications

Multi-AZ Architecture Patterns

Active-Active

Traffic to all AZs simultaneously. Highest availability, requires stateless design or session management.

Active-Passive

Primary handles traffic, standby for failover. RDS Multi-AZ uses this pattern.

Pilot Light

Minimal resources running, scale up on disaster. Cost-effective DR strategy.

Warm Standby

Scaled-down but functional environment. Balance of cost and recovery time.

Exam Tip

For high availability: Multi-AZ (99.99% SLA). For disaster recovery: Multi-Region with appropriate RTO/RPO planning.

Decoupling Mechanisms

Loose coupling for resilience and scalability

Messaging Services

Service	Type	Use Cases	Key Features
SQS Standard	Queue	Decoupling, buffering, async processing	Unlimited throughput, at-least-once, best-effort ordering
SQS FIFO	Queue	Ordered processing, deduplication	300 TPS (3000 with batching), exactly-once, strict ordering
SNS	Pub/Sub	Fanout, notifications, event distribution	Push to multiple subscribers, filtering, various protocols
EventBridge	Event Bus	Event-driven architecture, SaaS integration	Schema registry, rules, 35+ AWS service targets
Amazon MQ	Message Broker	Migrate from ActiveMQ/RabbitMQ	Managed brokers, industry-standard protocols

Decoupling Patterns

Queue-Based Load Leveling

SQS absorbs traffic spikes, workers process at their own pace. Protects downstream services.

Fanout Pattern

SNS topic to multiple SQS queues. One message processed by multiple consumers differently.

Dead Letter Queue

Capture failed messages for analysis. Prevent message loss, debug issues.

Event Sourcing

Store events, not just current state. EventBridge + Lambda + DynamoDB.

SQS Visibility Timeout

Default is 30 seconds. If processing takes longer, message becomes visible again and may be processed twice. Set visibility timeout > expected processing time.

Scaling Strategies

Automatic capacity adjustment

EC2 Auto Scaling

Scaling Type	Description	Best For
Target Tracking	Maintain specific metric (e.g., 50% CPU)	Most common, simple to configure
Step Scaling	Scale based on CloudWatch alarm thresholds	More control, multiple scaling steps
Simple Scaling	Single adjustment per alarm	Legacy, use step scaling instead
Scheduled Scaling	Scale at specific times	Predictable traffic patterns
Predictive Scaling	ML-based forecasting	Recurring patterns, proactive scaling

Launch Templates vs Launch Configurations

Launch Templates (Recommended): Versioning, multiple instance types, Spot/On-Demand mix, T2 Unlimited
Launch Configurations (Legacy): Immutable, single instance type, being deprecated

Application Auto Scaling

DynamoDB

Scale read/write capacity. Target tracking on consumed capacity.

ECS

Scale tasks in a service. CPU/memory utilization targets.

Aurora

Scale read replicas. Based on connections or CPU.

Lambda

Provisioned concurrency scaling. Predictable latency.