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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 |
NEW QUESTION # 208
A company has an application that uses an Amazon DynamoDB table to store user data. Every morning, a single-threaded process calls the DynamoDB API Scan operation to scan the entire table and generate a critical start-of-day report for management. A successful marketing campaign recently doubled the number of items in the table, and now the process takes too long to run and the report is not generated in time.
A database specialist needs to improve the performance of the process. The database specialist notes that, when the process is running, 15% of the table's provisioned read capacity units (RCUs) are being used.
What should the database specialist do?
Answer: A
Explanation:
Explanation
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Scan.html#Scan.ParallelScan
NEW QUESTION # 209
A financial company wants to store sensitive user data in an Amazon Aurora PostgreSQL DB cluster. The database will be accessed by multiple applications across the company. The company has mandated that all communications to the database be encrypted and the server identity must be validated. Any non-SSL-based connections should be disallowed access to the database.
Which solution addresses these requirements?
Answer: C
Explanation:
Explanation
PostgreSQL: sslrootcert=rds-cert.pem sslmode=[verify-ca | verify-full]
NEW QUESTION # 210
A company is running a website on Amazon EC2 instances deployed in multiple Availability Zones (AZs). The site performs a high number of repetitive reads and writes each second on an Amazon RDS for MySQL Multi- AZ DB instance with General Purpose SSD (gp2) storage. After comprehensive testing and analysis, a database specialist discovers that there is high read latency and high CPU utilization on the DB instance.
Which approach should the database specialist to take to resolve this issue without changing the application?
Answer: A
NEW QUESTION # 211
A company is migrating its on-premises database workloads to the AWS Cloud. A database specialist performing the move has chosen AWS DMS to migrate an Oracle database with a large table to Amazon RDS. The database specialist notices that AWS DMS is taking significant time to migrate the data.
Which actions would improve the data migration speed? (Choose three.)
Answer: C,D,F
NEW QUESTION # 212
A company is looking to move an on-premises IBM Db2 database running AIX on an IBM POWER7 server.
Due to escalating support and maintenance costs, the company is exploring the option of moving the workload to an Amazon Aurora PostgreSQL DB cluster.
What is the quickest way for the company to gather data on the migration compatibility?
Answer: A
NEW QUESTION # 213
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