SAA-C03 – Deep Dive Prep

Resilient Systems: Ability to recover quickly from attacks, faults, or failures; essential for high availability and durability.

Scalable Architecture: Dynamically grow during high demand and shrink during low demand; ensures cost efficiency and performance.

Horizontal Scaling: Add more resources to existing pool; enhances overall system capacity and resilience.

Vertical Scaling: Increase capacity of existing resources; improves performance without adding more instances.

Elasticity: Automatically adjust resources to match demand; achieved through services like AWS Auto Scaling.

AWS Auto Scaling: Unified, predictive scaling for multiple AWS resources; efficient but can be costly.

EC2 Auto Scaling: Scales EC2 instances, supports mixed instances; non-predictive but versatile for varying workloads | Read more 

Virtual Machines: Full OS with kernel; manages resources on underlying hardware, enabling multiple VMs on one host.

Containers: Lightweight, share host OS kernel; platform-independent, run anywhere without a full OS install.

AWS Purpose-Built Databases: Optimized for performance, scalability, and reliability; tailored for specific use cases. | Read more

DynamoDB Overview: Fully managed NoSQL database; low latency and high performance for real-time applications.

DynamoDB Auto Scaling: Automatically adjusts read/write throughput; based on traffic patterns for cost efficiency.

DynamoDB Global Tables: Multi-region replication; provides low-latency access and high availability globally.

DynamoDB Use Cases: Ideal for real-time bidding, gaming leaderboards, and IoT data storage.

Amazon RDS Overview: Managed relational database service; supports multiple database engines for versatility.

Amazon RDS Read Replicas: Offloads read traffic; improves performance and scalability of the primary database.

Amazon RDS Sharding: Distributes data across multiple instances; handles larger datasets efficiently.

Amazon RDS Use Cases: Suitable for web applications, e-commerce platforms, and financial applications.

Amazon Aurora Overview: Cloud-native relational database; compatible with MySQL and PostgreSQL, offering enhanced performance.

Amazon Aurora Replicas: Supports up to 15 low-latency replicas; provides high availability across multiple AZs.

Amazon Aurora Serverless: Automatically adjusts capacity; ideal for variable workloads with pay-per-use pricing.

Amazon Aurora Use Cases: Fits enterprise applications, SaaS, and OLTP workloads.

Amazon Redshift Overview: Managed, scalable data warehouse service; optimized for large-scale analytics.

Amazon Redshift Elastic Resize: Quickly adds or removes nodes; enables on-demand scalability.

Amazon Redshift Concurrency Scaling: Automatically adds capacity; handles high query loads efficiently.

Amazon Redshift Use Cases: Ideal for data warehousing, business analytics, and reporting.

Amazon RDS Multi-AZ Deployments: Automated failover to standby instance; ensures high availability and fault tolerance.

Amazon RDS Read Replicas Performance: Improves read performance; provides fallback option in case of primary failure.

Amazon ElastiCache Caching: In-memory caching service; reduces database load by storing frequently accessed data.

Amazon ElastiCache Overview: Supports Redis and Memcached; fully managed for high-performance caching.

Amazon ElastiCache Use Cases: Suitable for session storage, database query caching, and real-time analytics.

Amazon ElastiCache + Read Replicas: Enhances performance; combines caching with read replicas for high throughput.

Amazon RDS Performance Bottlenecks: Identify and address issues; crucial under extreme loads for optimal performance.

Amazon RDS Query Optimization: Optimize SQL queries; reduces execution time and resource consumption.

Amazon RDS Indexing: Speeds up data retrieval; uses proper indexing strategies to enhance performance.

AWS Elastic Load Balancing: Distributes traffic; improves performance and availability across multiple instances.

AWS Auto Scaling: Adjusts instances based on demand; ensures resources match workload requirements.

DynamoDB Cost: Pay-per-request pricing; cost-effective scaling for varying workloads.

DynamoDB Security: Encryption at rest and in transit; integrates with IAM for secure access control.

DynamoDB Limitations: Best for NoSQL workloads; may not suit relational data needs.

Amazon RDS Cost: Instance-based pricing; varies by type and usage, reflecting performance needs.

Amazon RDS Security: VPC integration, IAM, and encryption; ensures data protection and secure access.

Amazon RDS Limitations: Requires instance scaling management; no automatic write scaling.

Amazon Aurora Cost: Pay-per-use and instance pricing; flexible for different workload demands.

Amazon Aurora Security: Automated backups, VPC integration, encryption; ensures comprehensive data protection.

Amazon Aurora Limitations: Some features specific to MySQL/PostgreSQL; not suitable for all database needs.

Amazon Redshift Cost: Pay-per-node hour pricing; optimized for large-scale analytics workloads.

Amazon Redshift Security: VPC integration, encryption, IAM; ensures secure data handling and access control.

Amazon Redshift Limitations: Best for read-heavy workloads; not ideal for OLTP applications.

DynamoDB Auto Scaling Cost: Additional charges based on usage; ensures cost-effective scaling.

DynamoDB Auto Scaling Security: Integrated with IAM; secure and automated scaling operations.

DynamoDB Auto Scaling Limitations: Fully automated; no manual control over scaling process.

DynamoDB Global Tables Cost: Charges for multi-region replication; provides global access with added cost.

DynamoDB Global Tables Security: IAM integration; secure global data replication and access.

DynamoDB Global Tables Limitations: Increased cost for global replication; requires careful planning.

Amazon RDS Read Replicas Cost: Additional instance costs; improves read scalability and performance.

Amazon RDS Read Replicas Security: VPC and IAM; secure access and isolation for replicas.

Amazon RDS Read Replicas Limitations: No write scaling; only improves read performance.

Amazon RDS Sharding Cost: Costs increase with shards; involves complex management for large datasets.

Amazon RDS Sharding Security: VPC and IAM; secure data partitioning and access control.

Amazon RDS Sharding Limitations: Complex implementation; requires significant planning and management.

Amazon Aurora Replicas Cost: Additional costs for replicas; enhances read scalability.

Amazon Aurora Replicas Security: Automated backups, VPC, encryption; ensures data protection.

Amazon Aurora Replicas Limitations: Only provides read scalability; not suitable for write-intensive workloads.

Amazon Aurora Serverless Cost: Pay-per-usage; cost-efficient for variable workloads.

Amazon Aurora Serverless Security: Automated backups, VPC; secure serverless operations.

Amazon Aurora Serverless Limitations: Not suitable for all workloads; especially high-throughput OLTP.

Amazon Redshift Elastic Resize Cost: Pay-per-node hour; scalable data warehousing.

Amazon Redshift Elastic Resize Security: VPC integration, encryption; secure resizing operations.

Amazon Redshift Elastic Resize Limitations: Possible downtime during resizing; affects availability.

Amazon Redshift Concurrency Scaling Cost: Additional pay-per-query charges; scales with query load.

Amazon Redshift Concurrency Scaling Security: VPC, encryption; secure concurrency scaling.

Amazon Redshift Concurrency Scaling Limitations: Cost increases with high concurrency; manage usage carefully.

Amazon RDS Multi-AZ Cost: Additional instance costs; ensures high availability.

Amazon RDS Multi-AZ Security: Automated backups, VPC; secure high availability.

Amazon RDS Multi-AZ Limitations: No performance improvement; only provides availability.

Amazon ElastiCache Cost: Costs based on cache instances; high-performance in-memory caching.

Amazon ElastiCache Security: VPC, IAM; secure access and management.

Amazon ElastiCache Limitations: Requires effective cache invalidation; maintain data accuracy.

Amazon RDS Query Optimization Cost: Developer expertise required; optimize SQL queries for performance.

Amazon RDS Query Optimization Security: N/A; focused on performance improvement.

Amazon RDS Query Optimization Limitations: Requires ongoing maintenance; expert knowledge needed.

Amazon RDS Indexing Cost: Developer time for maintenance; improves data retrieval speed.

Amazon RDS Indexing Security: N/A; performance enhancement strategy.

Amazon RDS Indexing Limitations: Increased storage usage; requires regular maintenance.

AWS Elastic Load Balancing Cost: Pay-per-usage; scales traffic management.

AWS Elastic Load Balancing Security: SSL termination, VPC; secure traffic distribution.

AWS Elastic Load Balancing Limitations: Requires proper configuration; ensure optimal performance.

AWS Auto Scaling Cost: Instance costs based on scaling; matches resources to demand.

AWS Auto Scaling Security: VPC, IAM integration; secure automated scaling.

AWS Auto Scaling Limitations: Requires continuous monitoring; define appropriate policies.

Microservices Architecture: Independent services, API communication; flexibility and scalability.

API-Driven Design: Services structured around APIs; API Gateway and Lambda for HTTP handling.

Event-Driven Design: React to real-time events; EventBridge and Lambda for asynchronous processing.

Data Streaming Design: Real-time data processing; Kinesis and Lambda for continuous ingestion.

Serverless Fundamentals: No server management; Lambda and API Gateway for scaling and fault tolerance.

High Throughput Messaging: Scalable message volume; SQS for decoupling and horizontal scaling.

Containers in AWS: Manage containerized apps; ECS and Fargate for simplified orchestration.

Resilient Microservices: Fault-tolerant systems; DynamoDB and RDS for scalable data storage.

Scalable User Interfaces: Low-latency content delivery; CloudFront and API Gateway.

Hybrid Cloud: Extend AWS on-premises; Outposts for hybrid cloud and low-latency access.

Monitoring and Logging: Ensure application health; CloudWatch and X-Ray for monitoring and tracing.

Security Best Practices: Protect applications; IAM and Shield for access control and DDoS protection.

Cost Optimization: Pay for usage; Lambda and Spot Instances for cost-efficient compute.

Automation and CI/CD: Streamline deployment; CodePipeline and CodeBuild for continuous delivery.

Infrastructure as Code: Programmatic infrastructure management; CloudFormation and CDK.

Scaling Lambda: Understand concurrency; Lambda auto-scales with incoming requests.

API Gateway Use Cases: Securely expose services; API Gateway for API management.

Event Processing with Lambda: Asynchronous events; Lambda for serverless event-driven compute.

Asynchronous Decoupling: Independent component operation, SQS and Lambda for fault tolerance and scalability | Introduction to decoupling techniques

API-Driven Design: Structured around APIs, API Gateway and Lambda for efficient HTTP request handling.

Event-Driven Design: Real-time event processing, EventBridge and Lambda for asynchronous workflows.

Data Streaming Design: Continuous data processing, Kinesis and Lambda for real-time