Master essential AWS architecture patterns for building scalable, reliable cloud solutions. This comprehensive course covers foundational patterns for backup maintenance and redundancy management, progresses through high-availability design patterns, explores processing patterns for both static and dynamic data, addresses data upload strategies, and examines database and data processing patterns. You will also learn advanced architectural patterns for operations and networking while becoming familiar with throw-away environment strategies.
Course Audience:
This course is designed for professionals who will architect solutions on the AWS platform. It is specifically appropriate for individuals responsible for creating and maintaining data backups, implementing auto-scaling policies based on schedules and traffic patterns, provisioning servers and storage resources, optimizing database performance through caching and sharding techniques, and monitoring and managing data processing queues.
Prerequisites:
Learners should complete the AWS Essentials course first or possess equivalent foundational knowledge. You should have a solid understanding of system administration concepts, experience with enterprise server environments, knowledge of networking fundamentals, and basic familiarity with database management principles.
Certification Pathway:
This course, when combined with AWS Essentials, provides comprehensive preparation for the AWS Certified Solutions Architect: Associate certification exam.
Detailed Course Topics
1: AWS Introduction and Cloud Computing Overview
- Introduction to AWS platform and services
- Cloud computing service models and deployment options
- Strategic benefits of cloud migration
- Common challenges and problem-solving approaches in AWS
2: Basic Architecture Patterns
- Using Vagrant for development environments
- Snapshot pattern for data protection
- Stamp pattern for consistent deployments
- Scale up pattern for vertical scaling
- Scale out pattern for horizontal scaling
- On-demand disk pattern for dynamic storage
3: High Availability Architecture Patterns
- Multi-server pattern for redundancy
- Multi-data center pattern for geographic distribution
- Floating IP pattern for failover
- Deep health check pattern for monitoring
4: Static Data Processing Patterns
- High availability storage solutions
- Direct storage hosting approaches
- Private data delivery mechanisms
- Content delivery networks for performance
- Rename distribution pattern for data organization
5: Dynamic Data Processing Patterns
- Clone server pattern for load distribution
- NFS sharing pattern for shared storage
- State sharing pattern for consistency
- URL rewriting pattern for routing
- Cache proxy pattern for performance
6: Data Upload Patterns
- Write proxy pattern for write operations
- Storage index pattern for data organization
- Direct object upload pattern for efficiency
7: Database Architecture Patterns
- Database replication pattern for redundancy
- Read replica pattern for scaling queries
- In-memory cache pattern for performance
- Sharding write pattern for write scalability
8: Data Processing Patterns
- Queuing chain pattern for sequential processing
- Priority queue pattern for prioritized work
- Job observer pattern for monitoring
9: Operations and Maintenance Patterns
- Bootstrap pattern for automated setup
- Cloud dependency injection pattern for configuration
- Stack deployment pattern for infrastructure management
- Monitoring integration pattern for observability
- Web storage archive pattern for long-term retention
- Weighted transition pattern for gradual migration
- Hybrid backup pattern for multi-location protection
10: Network Architecture Patterns
- OnDemand NAT pattern for address translation
- Management network pattern for administrative access
- Functional firewall pattern for application security
- Operational firewall pattern for infrastructure security
- Web application firewall pattern for web protection
- Multiple load balancer pattern for distributed loading
11: Throw-Away Environments and DevOps
- Infrastructure as code for reproducible deployments
- Temporary development environments for testing
- Continuous integration for automated quality assurance
