It is crucial that you implement various best architectural practices when using Amazon Relational Database Service (RDS), such as enabling automatic backups and monitoring your memory, CPU, and storage usage. However, managing your Relational Database Service (RDS) configurations and continuously evaluating configuration changes, across your databases can be challenging. Join Clare as she explores how to leverage AWS Config and Conformance Packs to ensure database optimization and resiliency for production workloads. This video provides valuable insights into:
✅ Defining resiliency at the data tier level, including disaster recovery, instance protection, version control, and monitoring.
✅ Understanding AWS Config and its ability to assess and audit AWS infrastructure through resource configuration monitoring.
✅ Utilizing Conformance Packs to bundle multiple AWS Config rules for deployment as a single entity.
✅ Implementing best practices for database optimization, such as:
- Enabling Multi-AZ support for high availability
- Encrypting storage and snapshots for enhanced security
- Setting up enhanced monitoring for deeper insights into database performance
- Exploring remediation options for non-compliant resources using Lambda functions or AWS Systems Manager Automation Documents.
✅ Configuring notifications through email or third-party communication tools.
Additional Resources:
AWS Config: https://docs.aws.amazon.com/config/index.html
Sample Conformance Packs: https://github.com/awslabs/aws-config-rules/blob/master/aws-config-conformance-packs/Operational-Best-Practices-for-Data-Resiliency.yaml
Operational Best Practices for Database Services: https://github.com/awslabs/aws-config-rules/blob/master/aws-config-conformance-packs/Operational-Best-Practices-for-Database-Services.yaml
AWS Systems Manager Documents: https://docs.aws.amazon.com/systems-manager/latest/userguide/sysman-ssm-docs.html
Check out more resources for architecting in the #AWS cloud:
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