The AWS DBS-C01 exam preparation guide is designed to provide candidates with necessary information about the Database Specialty exam. It includes exam summary, sample questions, practice test, objectives and ways to interpret the exam objectives to enable candidates to assess the types of questions-answers that may be asked during the AWS Certified Database - Specialty exam.
It is recommended for all the candidates to refer the DBS-C01 objectives and sample questions provided in this preparation guide. The AWS Database Specialty certification is mainly targeted to the candidates who want to build their career in Specialty domain and demonstrate their expertise. We suggest you to use practice exam listed in this cert guide to get used to with exam environment and identify the knowledge areas where you need more work prior to taking the actual AWS Certified Database - Specialty exam.
AWS DBS-C01 Exam Summary:
|
Exam Name
|
AWS Certified Database - Specialty |
| Exam Code | DBS-C01 |
| Exam Price | $300 USD |
| Duration | 180 minutes |
| Number of Questions | 65 |
| Passing Score | 750 / 1000 |
| Recommended Training / Books |
AWS Database Offerings Planning and Designing Databases on AWS Exam Readiness - AWS Certified Database - Specialty |
| Schedule Exam | AWS Certification |
| Sample Questions | AWS DBS-C01 Sample Questions |
| Recommended Practice | AWS Certified Database - Specialty Practice Test |
AWS Database Specialty Syllabus:
| Section | Objectives |
|---|---|
Workload-Specific Database Design - 26% |
|
| Select appropriate database services for specific types of data and workloads. |
- Differentiate between ACID and BASE workloads. - Explain appropriate uses of types of databases (for example, relational, key-value, document, in-memory, graph, time series, ledger). - Identify use cases for persisted data compared with 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 and high availability strategies. - Differentiate use cases for read replicas and Multi-AZ deployments. |
| Design database solutions for performance, compliance, and scalability. |
- Recommend serverless compared with 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 DynamoDB capacity units, including on-demand capacity compared with 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 (for example, AWS CloudFormation, AWS CLI). |
| Determine data preparation and migration strategies. |
- Determine the data migration method (for example, snapshots, replication, restore). - Evaluate database migration tools and services (for example, AWS Database Migration Service [AWS DMS], native database tools). - Prepare data sources and targets. - Determine schema conversion methods (for example, AWS Schema Conversion Tool [AWS SCT]). - Determine heterogeneous compared with homogeneous migration strategies. |
| Perform 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 and snapshots. - Differentiate backup and restore strategies (for example, 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 (for example, in Amazon RDS option groups and parameter groups, or 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 (for example, 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 (for example, Amazon Simple Notification Service [Amazon SNS], Amazon Simple Queue Service [Amazon SQS], CloudWatch dashboards). |
| Troubleshoot and resolve common database issues. |
- Identify, evaluate, and respond to categories of failures (for example, 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 (for example, AWS Key Management Service [AWS KMS], AWS CloudHSM). |
| Evaluate auditing solutions. |
- Determine auditing strategies for structural and schema changes (for example, DDL). - Determine auditing strategies for data changes (for example, DML). - Determine auditing strategies for data access (for example, queries). - Determine auditing strategies for infrastructure changes (for example, 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 (for example, IAM, native credentials, Active Directory). - Recommend authorization controls for users (for example, policies). |
| Recognize potential security vulnerabilities within database solutions. |
- Determine security group rules and Network ACLs for database access. - Identify relevant VPC configurations (for example, VPC endpoints, public subnets compared with private subnets, perimeter zone). - Determine appropriate storage methods for sensitive data. |