Amazon Simple Queue Service (SQS) is commonly used to decouple application components. Instead of components communicating directly, messages are sent to a queue. Other components pick them up when they’re ready. This design prevents one slow or failing part of the system from blocking others, improving scalability and reliability.
Amazon S3 has different storage classes (e.g., Standard, Standard-IA, One Zone-IA, Glacier, Glacier Deep Archive). You can store frequently accessed data in S3 Standard and move rarely accessed data to lower-cost classes. Using lifecycle policies, AWS can automatically transition objects based on age or access frequency, reducing costs without losing durability.
To design for high availability, deploy application components in at least two Availability Zones (AZs) within a Region. For example, run EC2 instances in multiple AZs behind an Elastic Load Balancer, use Multi-AZ RDS databases, and store data in S3, which is inherently multi-AZ. This ensures that if one AZ fails, the application remains available in others.
Amazon Redshift is a fully managed, petabyte-scale data warehouse service. It is optimized for Online Analytical Processing (OLAP) workloads, letting you run complex queries on large datasets quickly. It integrates with popular BI tools and can scale both storage and compute.
There are two main ways:
Both methods can be used together for redundancy.
The AWS Well-Architected Framework provides best practices across five pillars: Operational Excellence, Security, Reliability, Performance Efficiency, and Cost Optimization. It helps architects evaluate and improve cloud architectures by identifying risks and providing practical steps to fix them, ensuring systems are secure, resilient, efficient, and cost-effective.