Question

Exam Question

A solutions architect is designing a customer-facing application for a company. The application’s Database will have a clearly defined access pattern throughout the year and will have a variable number of reads and writes that depend on the time of year.

The company must retain audit records for the database for 7 days.

The recovery point objective (RPO) must be less than 5 hours.

Which solution meets these requirements?

A. Use Amazon DynamoDB with auto scaling Use on-demand backups and Amazon DynamoDB Streams
B. Use Amazon Redshift. Configure concurrency scaling. Activate audit logging. Perform database snapshots every 4 hours
C. Use Amazon RDS with Provisioned IOPS Activate the database auditing parameter. Perform database snapshots every 5 hours
D. Use Amazon Aurora MySQL with auto scaling. Activate the database auditing parameter

Amazon AWS Certified Solutions Architect – Associate SAA-C02 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Amazon AWS Certified Solutions Architect – Associate SAA-C02 exam and earn Amazon AWS Certified Solutions Architect – Associate SAA-C02 certification.

Correct Answer

C. Use Amazon RDS with Provisioned IOPS Activate the database auditing parameter. Perform database snapshots every 5 hours

Explanation 1

The answer to your question is C. Use Amazon RDS with Provisioned IOPS Activate the database auditing parameter. Perform database snapshots every 5 hours.

This means that you should use Amazon DynamoDB with DAX for data that is frequently accessed by the customer-facing application, and use Amazon S3 and Amazon Athena for historical data analysis.

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and consistent performance with seamless scalability. DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to a 10x performance improvement – from milliseconds to microseconds – even at millions of requests per second.

Amazon S3 is an object storage service that offers industry-leading scalability, data availability, security, and performance. Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL.

By using DynamoDB with DAX, you can achieve sub-millisecond latency for your customer-facing application data, without any operational overhead of managing servers or clusters. By using DynamoDB table export, you can export your data to an S3 bucket in Apache Parquet format, which is optimized for analytics. By using Amazon Athena, you can run one-time queries on your historical data in S3 without any server setup or data loading.

Explanation 2

The correct answer is D. Use Amazon Aurora MySQL with auto scaling. Activate the database auditing parameter.

Amazon Aurora MySQL is a fully managed MySQL database service that offers high performance, availability, and compatibility. It is a good choice for this application because it can scale up or down automatically to meet demand, and it supports database auditing.

To meet the RPO requirement, database snapshots can be taken every 5 hours. This will ensure that the database can be restored to a point in time within 5 hours of a failure.

To meet the audit requirement, the database auditing parameter can be activated. This will record all database activity, including reads and writes. The audit logs can be stored in Amazon S3 for 7 days.

Here is a more detailed explanation of each option:

A. Use Amazon DynamoDB with auto scaling Use on-demand backups and Amazon DynamoDB Streams

Amazon DynamoDB is a fully managed NoSQL database service that offers high performance and scalability. It is a good choice for applications that require high throughput and low latency. However, DynamoDB does not support database auditing.

On-demand backups are a good way to protect data in DynamoDB. However, they can be expensive, especially if the database is large. Amazon DynamoDB Streams can be used to capture changes to data in DynamoDB. However, they do not provide a complete audit trail.

B. Use Amazon Redshift. Configure concurrency scaling. Activate audit logging. Perform database snapshots every 4 hours

Amazon Redshift is a fully managed data warehouse service that offers high performance and scalability. It is a good choice for applications that require large amounts of data to be processed quickly. However, Redshift does not support database auditing.

Concurrency scaling can be used to increase the number of nodes in a Redshift cluster. This can improve performance, but it can also increase costs. Audit logging can be activated to record all database activity. However, audit logs are not stored for 7 days by default.

C. Use Amazon RDS with Provisioned IOPS Activate the database auditing parameter. Perform database snapshots every 5 hours

Amazon RDS is a fully managed relational database service that offers high performance, availability, and compatibility. It is a good choice for applications that require a relational database. However, RDS does not support database auditing by default.

Provisioned IOPS can be used to increase the performance of an RDS database. This can improve performance, but it can also increase costs. The database auditing parameter can be activated to record all database activity. However, audit logs are not stored for 7 days by default.

Overall, Amazon Aurora MySQL is the best choice for this application because it offers the required performance, availability, compatibility, and audit logging.

Explanation 3

To meet the requirements of a customer-facing application with a clearly defined access pattern, variable read/write demands, and specific data retention and recovery objectives, the most suitable solution is:

C. Use Amazon RDS with Provisioned IOPS, activate the database auditing parameter, and perform database snapshots every 5 hours.

A. Using Amazon DynamoDB with auto scaling is a valid option for a highly scalable NoSQL database. However, it does not provide native audit logging functionality for the database. While DynamoDB Streams can capture changes to the data, it does not address the audit record retention requirement.

B. Amazon Redshift is a powerful data warehousing solution, but it may not be the best fit for this scenario. It is optimized for analytics workloads rather than a customer-facing application with variable read/write demands. Database snapshots every 4 hours may not meet the specified recovery point objective (RPO) of less than 5 hours.

C. Amazon RDS with Provisioned IOPS is a good choice for a customer-facing application with a clearly defined access pattern. It allows you to provision the required input/output operations per second (IOPS) for the database to handle the workload efficiently. Activating the database auditing parameter ensures that audit logs are generated and retained as required. Performing database snapshots every 5 hours helps meet the RPO of less than 5 hours, allowing for relatively frequent recovery points.

D. While Amazon Aurora MySQL with auto scaling is a scalable and high-performance database option, it does not provide native audit logging functionality. Therefore, it does not meet the requirement for retaining audit records for 7 days.

In summary, Option C is the most suitable solution as it combines the benefits of Amazon RDS with Provisioned IOPS, database auditing, and regular database snapshots. This solution meets the specific requirements of the customer-facing application, including the defined access pattern, variable read/write demands, audit record retention, and recovery point objective (RPO) of less than 5 hours.

Explanation 4

The correct answer is D. Amazon Aurora MySQL with auto scaling and database auditing enabled meets all of the requirements in the question.

• Amazon Aurora MySQL is a fully managed MySQL database service that offers high performance, availability, and durability. It is a good choice for customer-facing applications that require a high level of performance and availability.
• Auto scaling can be used to automatically scale the database up or down based on demand. This can help to ensure that the database is always running at the optimal level of performance and cost.
• Database auditing can be enabled to track all changes made to the database. This can be helpful for compliance purposes and for troubleshooting problems.
• The RPO of less than 5 hours can be met by performing database snapshots every 5 hours. Database snapshots are point-in-time copies of the database that can be used to restore the database to a previous state.

The other options do not meet all of the requirements in the question.

• Amazon DynamoDB is a NoSQL database that is not designed for high-volume read and write operations. It is also not a good choice for applications that require database auditing.
• Amazon Redshift is a data warehouse that is not designed for customer-facing applications. It is also not a good choice for applications that require database auditing.
• Amazon RDS with Provisioned IOPS is a good choice for customer-facing applications that require high performance. However, it does not offer database auditing.

In conclusion, Amazon Aurora MySQL with auto scaling and database auditing enabled is the best solution for this scenario.

Explanation 5

To answer your question, we need to compare the features and benefits of different AWS database services: Amazon DynamoDB, Amazon Redshift, Amazon RDS, and Amazon Aurora.

Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It is a fully managed, multi-region, multi-active, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications. Some of the advantages of DynamoDB are:

• It supports both key-value and document data models
• It provides consistent, low-latency performance at any scale
• It offers flexible schema and data types
• It supports auto scaling, on-demand backups, point-in-time recovery, and global tables
• It integrates with other AWS services such as Lambda, Kinesis, S3, etc.

Some of the disadvantages of DynamoDB are:

• It has limited query capabilities and does not support complex joins or aggregations
• It has a provisioned throughput model that requires careful capacity planning and monitoring
• It has a maximum item size of 400 KB and a maximum partition key size of 1 KB
• It has a higher cost per GB than other relational databases

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers. Some of the advantages of Redshift are:

• It supports SQL and integrates with popular business intelligence tools
• It provides fast query performance using columnar storage, massively parallel processing (MPP), and advanced compression techniques
• It offers high availability, durability, encryption, and backup options
• It supports concurrency scaling, elastic resize, and automatic workload management

Some of the disadvantages of Redshift are:

• It requires schema design and data loading before querying
• It has a higher learning curve than other relational databases
• It has a minimum cluster size of two nodes and a maximum node size of 16 TB
• It has a higher cost per hour than other relational databases

Amazon RDS is a managed service that makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups. It frees you to focus on your applications so you can give them the fast performance, high availability, security and compatibility they need. Some of the advantages of RDS are:

• It supports six popular database engines: Amazon Aurora, MySQL, MariaDB, PostgreSQL, Oracle Database, and SQL Server
• It provides consistent performance and availability using Multi-AZ deployments, read replicas, automatic failover, and backup/restore options
• It offers security features such as encryption at rest and in transit, IAM integration, VPC isolation, etc.
• It allows you to scale compute and storage resources with minimal downtime

Some of the disadvantages of RDS are:

• It has some limitations on database configuration and administration compared to self-managed databases
• It has a maximum database size of 64 TB for Aurora and 16 TB for other engines
• It has a higher cost per IOPS than other relational databases

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. Aurora is up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases. It provides the security, availability, and reliability of commercial databases at 1/10th the cost. Some of the advantages of Aurora are:

• It is fully compatible with MySQL and PostgreSQL engines
• It delivers high performance using a distributed storage system that scales up to 64 TB per database instance
• It offers high availability using six-way replication across three Availability Zones (AZs) with sub-second failover
• It supports auto scaling, backup/restore, point-in-time recovery, and cross-region replication

Some of the disadvantages of Aurora are:

• It is not compatible with other database engines such as Oracle or SQL Server
• It has some limitations on database features and functions compared to MySQL and PostgreSQL
• It has a higher cost per hour than other RDS engines

Based on the above comparison, the best solution for your question would depend on the specific requirements and constraints of your application. However, a possible answer could be:

A. Use Amazon DynamoDB with auto scaling. Use on-demand backups and Amazon DynamoDB Streams

This solution meets the following requirements:

• The application’s database will have a clearly defined access pattern throughout the year and will have a variable number of reads and writes that depend on the time of year. DynamoDB supports both key-value and document data models, which can accommodate different types of data and access patterns. It also provides consistent, low-latency performance at any scale, which can handle variable workloads. Auto scaling can adjust the provisioned throughput capacity of your tables and global secondary indexes in response to actual traffic patterns, which can optimize performance and cost.
• The company must retain audit records for the database for 7 days. On-demand backups enable you to create full backups of your DynamoDB tables data for data archiving, helping you meet your corporate and governmental regulatory requirements. You can backup tables from a few megabytes to hundreds of terabytes of data, with no impact on performance or availability to your production applications. You can restore backups as new DynamoDB tables within minutes, regardless of the size of your table. You can also use Amazon DynamoDB Streams to capture a time-ordered sequence of item-level modifications in any DynamoDB table, and store this information in a log for up to 24 hours. You can use this stream data for various purposes, such as triggering AWS Lambda functions, replicating data to other databases, or auditing table activity.
• The recovery point objective (RPO) must be less than 5 hours. RPO is the maximum acceptable amount of data loss measured in time. With on-demand backups, you can create backups at any time with a single click in the AWS Management Console or a single API call. You can also automate backups using AWS Lambda functions triggered by Amazon CloudWatch Events or other AWS services. With DynamoDB Streams, you can capture every data change in your table and replay them in near real-time or at any point in time within the 24-hour window. This way, you can achieve an RPO of less than 5 hours using either backups or streams, depending on your recovery scenario.

Explanation 6

The correct answer is D. Use Amazon Aurora MySQL with auto scaling. Activate the database auditing parameter.

Amazon Aurora MySQL is a fully managed MySQL database service that offers high performance, availability, and compatibility. It is a good choice for a customer-facing application that requires a clearly defined access pattern throughout the year and a variable number of reads and writes that depend on the time of year.

Aurora MySQL supports auto scaling, which means that the number of database instances can be automatically increased or decreased based on demand. This can help to ensure that the application is always running at peak performance, regardless of the number of users.

Aurora MySQL also supports database auditing, which can be used to track changes to the database. This can be helpful for compliance purposes or for troubleshooting problems.

Aurora MySQL offers a 5-minute RPO for database snapshots. This means that if a database snapshot is taken every 5 hours, the application can be restored to its state within 5 minutes of a failure.

Here are the other options and why they are not the best choice:

• A. Use Amazon DynamoDB with auto scaling. Use on-demand backups and Amazon DynamoDB Streams. Amazon DynamoDB is a NoSQL database service that is not as well suited for OLTP applications as a relational database like MySQL. DynamoDB also does not support database auditing.
• B. Use Amazon Redshift. Configure concurrency scaling. Activate audit logging. Perform database snapshots every 4 hours. Amazon Redshift is a data warehouse service that is not as well suited for OLTP applications as a relational database like MySQL. Redshift also does not support database auditing.
• C. Use Amazon RDS with Provisioned IOPS. Activate the database auditing parameter. Perform database snapshots every 5 hours. Amazon RDS is a fully managed relational database service that offers high performance, availability, and compatibility. However, it is more expensive than Aurora MySQL. RDS also does not offer a 5-minute RPO for database snapshots.

Explanation 7

The solution that meets the requirements of the customer-facing application is A. Using Amazon DynamoDB with auto scaling and on-demand backups and Amazon DynamoDB Streams will provide a scalable and highly available database that can handle variable reads and writes throughout the year.

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. With auto scaling, DynamoDB can automatically adjust capacity to maintain steady, predictable performance at the lowest possible cost. On-demand backups provide continuous backups of your DynamoDB table data. Amazon DynamoDB Streams captures a time-ordered sequence of item-level modifications in any DynamoDB table and stores this information in a log for up to 24 hours.

Option B is incorrect because Amazon Redshift is not designed for transactional workloads like those required by customer-facing applications. Concurrency scaling is used to improve query performance when many users are accessing the same data at the same time. Database snapshots every 4 hours do not meet the requirement of an RPO less than 5 hours.

Option C is incorrect because Amazon RDS does not provide the scalability required by customer-facing applications with variable reads and writes throughout the year. The database snapshots every 5 hours do not meet the requirement of an RPO less than 5 hours.

Option D is incorrect because Amazon Aurora MySQL does not provide the scalability required by customer-facing applications with variable reads and writes throughout the year.

Reference

• AWS Certified Solutions Architect – Associate Certification (amazon.com)
• New version of AWS Certified Solutions Architect – Associate exam is now available (amazon.com)
• Exam Readiness: AWS Certified Solutions Architect – Associate | Classroom Training | AWS (amazon.com)
• AWS Certified Solutions Architect – Professional Certification | AWS Certification | AWS (amazon.com)
• Database – Overview of Amazon Web Services
• Purpose-Built Databases on AWS | Amazon Web Services

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