
- AWS RDS overview and core concepts (instances, parameter groups, security groups, subnet groups)
- How to scale RDS: Multi-AZ deployments, read replicas, and storage scaling
- Backup and recovery strategies: automated backups, snapshots, point-in-time recovery
- Security best practices for RDS: IAM integration, encryption at rest and in transit, network isolation
- Performance basics and tuning: monitoring, instance sizing, and basic indexing strategies
- Hands-on labs: creating instances, configuring Multi‑AZ and read replicas, and managing backups and snapshots
- Managed operations: automated backups, patching, and maintenance windows
- High availability: easy Multi‑AZ deployments for failover
- Scalability: read replicas and storage/compute scaling options
- Engine flexibility: choose the engine that fits your application needs
- Monitoring and metrics: integration with Amazon CloudWatch
Labs included in the course (hands-on topics):
- Creating RDS instances and selecting the right engine and instance class
- Configuring Multi‑AZ for high availability and testing failover
- Creating and promoting read replicas for read scaling
- Setting up automated backups and manual snapshots for point‑in‑time recovery
- Basic performance checks and tuning (monitoring, instance resizing, and indexing)
To follow the labs you will need an AWS account with sufficient permissions to create and manage RDS instances (or use a provided sandbox). Basic familiarity with AWS Console navigation and core database concepts will help you move faster.
- AWS RDS product page
- Amazon Aurora
- AWS RDS Documentation
- Kubernetes Basics (for related orchestration concepts)