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| Section | Objectives |
|---|---|
Workload-Specific Database Design - 26% | |
| Select appropriate database services for specific types of data and workloads. | - Differentiate between ACID vs. BASE workloads - Explain appropriate uses of types of databases (e.g., relational, key-value, document, in-memory, graph, time series, ledger) - Identify use cases for persisted data vs. ephemeral data |
| Determine strategies for disaster recovery and high availability. | - Select Region and Availability Zone placement to optimize database performance - Determine implications of Regions and Availability Zones on disaster recovery/high availability strategies - Differentiate use cases for read replicas and Multi-AZ deployments |
| Design database solutions for performance, compliance, and scalability. | - Recommend serverless vs. instance-based database architecture - Evaluate requirements for scaling read replicas - Define database caching solutions - Evaluate the implications of partitioning, sharding, and indexing - Determine appropriate instance types and storage options - Determine auto-scaling capabilities for relational and NoSQL databases - Determine the implications of Amazon DynamoDB adaptive capacity - Determine data locality based on compliance requirements |
| Compare the costs of database solutions. | - Determine cost implications of Amazon DynamoDB capacity units, including on-demand vs. provisioned capacity - Determine costs associated with instance types and automatic scaling - Design for costs including high availability, backups, multi-Region, Multi-AZ, and storage type options - Compare data access costs |
Deployment and Migration - 20% | |
| Automate database solution deployments. | - Evaluate application requirements to determine components to deploy - Choose appropriate deployment tools and services (e.g., AWS CloudFormation, AWS CLI) |
| Determine data preparation and migration strategies. | - Determine the data migration method (e.g., snapshots, replication, restore) - Evaluate database migration tools and services (e.g., AWS DMS, native database tools) - Prepare data sources and targets - Determine schema conversion methods (e.g., AWS Schema Conversion Tool) - Determine heterogeneous vs. homogeneous migration strategies |
| Execute and validate data migration. | - Design and script data migration - Run data extraction and migration scripts - Verify the successful load of data |
Management and Operations - 18% | |
| Determine maintenance tasks and processes. | - Account for the AWS shared responsibility model for database services - Determine appropriate maintenance window strategies - Differentiate between major and minor engine upgrades |
| Determine backup and restore strategies. | - Identify the need for automatic and manual backups/snapshots - Differentiate backup and restore strategies (e.g., full backup, point-in-time, encrypting backups cross-Region) - Define retention policies - Correlate the backup and restore to recovery point objective (RPO) and recovery time objective (RTO) requirements |
| Manage the operational environment of a database solution. | - Orchestrate the refresh of lower environments - Implement configuration changes (e.g., in Amazon RDS option/parameter groups or Amazon DynamoDB indexing changes) - Automate operational tasks - Take action based on AWS Trusted Advisor reports |
Monitoring and Troubleshooting - 18% | |
| Determine monitoring and alerting strategies. | - Evaluate monitoring tools (e.g., Amazon CloudWatch, Amazon RDS Performance Insights, database native) - Determine appropriate parameters and thresholds for alert conditions - Use tools to notify users when thresholds are breached (e.g., Amazon SNS, Amazon SQS, Amazon CloudWatch dashboards) |
| Troubleshoot and resolve common database issues. | - Identify, evaluate, and respond to categories of failures (e.g., troubleshoot connectivity; instance, storage, and partitioning issues) - Automate responses when possible |
| Optimize database performance. | - Troubleshoot database performance issues - Identify appropriate AWS tools and services for database optimization - Evaluate the configuration, schema design, queries, and infrastructure to improve performance |
Database Security - 18% | |
| Encrypt data at rest and in transit. | - Encrypt data in relational and NoSQL databases - Apply SSL connectivity to databases - Implement key management (e.g., AWS KMS, AWS CloudHSM) |
| Evaluate auditing solutions. | - Determine auditing strategies for structural/schema changes (e.g., DDL) - Determine auditing strategies for data changes (e.g., DML) - Determine auditing strategies for data access (e.g., queries) - Determine auditing strategies for infrastructure changes (e.g., AWS CloudTrail) - Enable the export of database logs to Amazon CloudWatch Logs |
| Determine access control and authentication mechanisms. | - Recommend authentication controls for users and roles (e.g., IAM, native credentials, Active Directory) - Recommend authorization controls for users (e.g., policies) |
| Recognize potential security vulnerabilities within database solutions. | - Determine security group rules and NACLs for database access - Identify relevant VPC configurations (e.g., VPC endpoints, public vs. private subnets, demilitarized zone) - Determine appropriate storage methods for sensitive data |
Reference: https://aws.amazon.com/certification/certified-database-specialty/
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