Practice Free SAA-C03 Exam Online Questions
Question #201
A company has a regional subscription-based streaming service that runs in a single AWS Region. The architecture consists of web servers and application servers on Amazon EC2 instances. The EC2 instances are in Auto Scaling groups behind Elastic Load Balancers. The architecture includes an Amazon Aurora database cluster that extends across multiple Availability Zones.
The company wants to expand globally and to ensure that its application has minimal downtime.
- A . Extend the Auto Scaling groups for the web tier and the application tier to deploy instances in Availability Zones in a second Region. Use an Aurora global database to deploy the database in the primary Region and the second Region. Use Amazon Route 53 health checks with a failover routing policy to the second Region.
- B . Deploy the web tier and the application tier to a second Region. Add an Aurora PostgreSQL cross-Region Aurara Replica in the second Region. Use Amazon Route 53 health checks with a failovers routing policy to the second Region, Promote the secondary to primary as needed.
- C . Deploy the web tier and the applicatin tier to a second Region. Create an Aurora PostSQL database in the second Region. Use AWS Database Migration Service (AWS DMS) to replicate the primary database to the second Region. Use Amazon Route 53 health checks with a failover routing policy to the second Region.
- D . Deploy the web tier and the application tier to a second Region. Use an Amazon Aurora global database to deploy the database in the primary Region and the second Region. Use Amazon Route 53 health checks with a failover routing policy to the second Region. Promote the secondary to primary as needed.
Correct Answer: D
D
Explanation:
This option is the most efficient because it deploys the web tier and the application tier to a second Region, which provides high availability and redundancy for the application. It also uses an Amazon Aurora global database, which is a feature that allows a single Aurora database to span multiple AWS Regions1. It also deploys the database in the primary Region and the second Region, which provides low latency global reads and fast recovery from a Regional outage. It also uses Amazon Route 53 health checks with a failover routing policy to the second Region, which provides data protection by routing traffic to healthy endpoints in different Regions2. It also promotes the secondary to primary as needed, which provides data consistency by allowing write operations in one of the Regions at a time3. This solution meets the requirement of expanding globally and ensuring that its application has minimal downtime.
Option A is less efficient because it extends the Auto Scaling groups for the web tier and the application tier to deploy instances in Availability Zones in a second Region, which could incur higher costs and complexity than deploying them separately. It also uses an Aurora global database to deploy the database in the primary Region and the second Region, which is correct. However, it does not use Amazon Route 53 health checks with a failover routing policy to the second Region, which could result in traffic being routed to unhealthy endpoints.
Option B is less efficient because it deploys the web tier and the application tier to a second Region, which is correct. It also adds an Aurora PostgreSQL cross-Region Aurora Replica in the second Region, which provides read scalability across Regions. However, it does not use an Aurora global database, which provides faster replication and recovery than cross-Region replicas. It also uses Amazon Route 53 health checks with a failover routing policy to the second Region, which is correct. However, it does not promote the secondary to primary as needed, which could result in data inconsistency or loss.
Option C is less efficient because it deploys the web tier and the application tier to a second Region, which is correct. It also creates an Aurora PostgreSQL database in the second Region, which provides data redundancy across Regions. However, it does not use an Aurora global database or cross-Region replicas, which provide faster replication and recovery than creating separate databases. It also uses AWS Database Migration Service (AWS DMS) to replicate the primary database to the second Region, which provides data migration between different sources and targets. However, it does not use an Aurora global database or cross-Region replicas, which provide faster replication and recovery than using AWS DMS. It also uses Amazon Route 53 health checks with a failover routing policy to the second Region, which is correct.
D
Explanation:
This option is the most efficient because it deploys the web tier and the application tier to a second Region, which provides high availability and redundancy for the application. It also uses an Amazon Aurora global database, which is a feature that allows a single Aurora database to span multiple AWS Regions1. It also deploys the database in the primary Region and the second Region, which provides low latency global reads and fast recovery from a Regional outage. It also uses Amazon Route 53 health checks with a failover routing policy to the second Region, which provides data protection by routing traffic to healthy endpoints in different Regions2. It also promotes the secondary to primary as needed, which provides data consistency by allowing write operations in one of the Regions at a time3. This solution meets the requirement of expanding globally and ensuring that its application has minimal downtime.
Option A is less efficient because it extends the Auto Scaling groups for the web tier and the application tier to deploy instances in Availability Zones in a second Region, which could incur higher costs and complexity than deploying them separately. It also uses an Aurora global database to deploy the database in the primary Region and the second Region, which is correct. However, it does not use Amazon Route 53 health checks with a failover routing policy to the second Region, which could result in traffic being routed to unhealthy endpoints.
Option B is less efficient because it deploys the web tier and the application tier to a second Region, which is correct. It also adds an Aurora PostgreSQL cross-Region Aurora Replica in the second Region, which provides read scalability across Regions. However, it does not use an Aurora global database, which provides faster replication and recovery than cross-Region replicas. It also uses Amazon Route 53 health checks with a failover routing policy to the second Region, which is correct. However, it does not promote the secondary to primary as needed, which could result in data inconsistency or loss.
Option C is less efficient because it deploys the web tier and the application tier to a second Region, which is correct. It also creates an Aurora PostgreSQL database in the second Region, which provides data redundancy across Regions. However, it does not use an Aurora global database or cross-Region replicas, which provide faster replication and recovery than creating separate databases. It also uses AWS Database Migration Service (AWS DMS) to replicate the primary database to the second Region, which provides data migration between different sources and targets. However, it does not use an Aurora global database or cross-Region replicas, which provide faster replication and recovery than using AWS DMS. It also uses Amazon Route 53 health checks with a failover routing policy to the second Region, which is correct.
Question #202
A company sells ringtones created from clips of popular songs. The files containing the ringtones are stored in Amazon S3 Standard and are at least 128 KB in size. The company has millions of files, but downloads are infrequent for ringtones older than 90 days. The company needs to save money on storage while keeping the most accessed files readily available for its users.
Which action should the company take to meet these requirements MOST cost-effectively?
- A . Configure S3 Standard-Infrequent Access (S3 Standard-IA) storage for the initial storage tier of the objects.
- B . Move the files to S3 Intelligent-Tiering and configure it to move objects to a less expensive storage tier after 90 days.
- C . Configure S3 inventory to manage objects and move them to S3 Standard-Infrequent Access (S3 Standard-1A) after 90 days.
- D . Implement an S3 Lifecycle policy that moves the objects from S3 Standard to S3 Standard-Infrequent Access (S3 Standard-1A) after 90 days.
Correct Answer: D
D
Explanation:
This solution meets the requirements of saving money on storage while keeping the most accessed files readily available for the users. S3 Lifecycle policy can automatically move objects from one storage class to another based on predefined rules. S3 Standard-IA is a lower-cost storage class for data that is accessed less frequently, but requires rapid access when needed. It is suitable for ringtones older than 90 days that are downloaded infrequently.
Option A is incorrect because configuring S3 Standard-IA for the initial storage tier of the objects can incur higher costs for frequent access and retrieval fees.
Option B is incorrect because moving the files to S3 Intelligent-Tiering can incur additional monitoring and automation fees that may not be
necessary for ringtones older than 90 days.
Option C is incorrect because using S3 inventory to manage objects and move them to S3 Standard-IA can be complex and time-consuming, and it does not provide automatic cost savings.
Reference:
https://aws.amazon.com/s3/storage-classes/
https://aws.amazon.com/s3/cloud-storage-cost-optimization-ebook/
D
Explanation:
This solution meets the requirements of saving money on storage while keeping the most accessed files readily available for the users. S3 Lifecycle policy can automatically move objects from one storage class to another based on predefined rules. S3 Standard-IA is a lower-cost storage class for data that is accessed less frequently, but requires rapid access when needed. It is suitable for ringtones older than 90 days that are downloaded infrequently.
Option A is incorrect because configuring S3 Standard-IA for the initial storage tier of the objects can incur higher costs for frequent access and retrieval fees.
Option B is incorrect because moving the files to S3 Intelligent-Tiering can incur additional monitoring and automation fees that may not be
necessary for ringtones older than 90 days.
Option C is incorrect because using S3 inventory to manage objects and move them to S3 Standard-IA can be complex and time-consuming, and it does not provide automatic cost savings.
Reference:
https://aws.amazon.com/s3/storage-classes/
https://aws.amazon.com/s3/cloud-storage-cost-optimization-ebook/
Question #203
A company wants to build a scalable key management Infrastructure to support developers who need to encrypt data in their applications.
What should a solutions architect do to reduce the operational burden?
- A . Use multifactor authentication (MFA) to protect the encryption keys.
- B . Use AWS Key Management Service (AWS KMS) to protect the encryption keys
- C . Use AWS Certificate Manager (ACM) to create, store, and assign the encryption keys
- D . Use an IAM policy to limit the scope of users who have access permissions to protect the encryption keys
Correct Answer: B
B
Explanation:
https://aws.amazon.com/kms/faqs/#:~:text=If%20you%20are%20a%20developer%20who%20needs %20to%20digitally,a%20broad%20set%20of%20industry%20and%20regional%20compliance%20regi mes.
B
Explanation:
https://aws.amazon.com/kms/faqs/#:~:text=If%20you%20are%20a%20developer%20who%20needs %20to%20digitally,a%20broad%20set%20of%20industry%20and%20regional%20compliance%20regi mes.
Question #204
A company is developing a new application that will run on Amazon EC2 instances. The application needs to access multiple AWS services.
The company needs to ensure that the application will not use long-term access keys to access AWS services.
- A . Create an IAM user. Assign the IAM user to the application. Create programmatic access keys for
the IAM user. Embed the access keys in the application code. - B . Create an IAM user that has programmatic access keys. Store the access keys in AWS Secrets Manager. Configure the application to retrieve the keys from Secrets Manager when the application runs.
- C . Create an IAM role that can access AWS Systems Manager Parameter Store. Associate the role with each EC2 instance profile. Create IAM access keys for the AWS services, and store the keys in Parameter Store. Configure the application to retrieve the keys from Parameter Store when the application runs.
- D . Create an IAM role that has permissions to access the required AWS services. Associate the IAM role with each EC2 instance profile.
Correct Answer: D
D
Explanation:
Why Option D is Correct:
IAM Roles with Instance Profiles: Allow applications to access AWS services securely without hardcoding long-term access keys.
Short-Term Credentials: IAM roles issue short-term credentials dynamically managed by AWS.
Why Other Options Are Not Ideal:
Option A and B: Embedding or retrieving long-term access keys introduces security risks and operational overhead.
Option C: Combining IAM roles with Parameter Store adds unnecessary complexity.
AWS
Reference: IAM Roles and Instance Profiles:
AWS Documentation – IAM Roles
D
Explanation:
Why Option D is Correct:
IAM Roles with Instance Profiles: Allow applications to access AWS services securely without hardcoding long-term access keys.
Short-Term Credentials: IAM roles issue short-term credentials dynamically managed by AWS.
Why Other Options Are Not Ideal:
Option A and B: Embedding or retrieving long-term access keys introduces security risks and operational overhead.
Option C: Combining IAM roles with Parameter Store adds unnecessary complexity.
AWS
Reference: IAM Roles and Instance Profiles:
AWS Documentation – IAM Roles
Question #205
A company uses an organization in AWS Organizations to manage AWS accounts that contain applications. The company sets up a dedicated monitoring member account in the organization. The company wants to query and visualize observability data across the accounts by using Amazon CloudWatch.
Which solution will meet these requirements?
- A . Enable CloudWatch cross-account observability for the monitoring account. Deploy an AWS CloudFormation template provided by the monitoring account in each AWS account to share the data with the monitoring account.
- B . Set up service control policies (SCPs) to provide access to CloudWatch in the monitoring account under the Organizations root organizational unit (OU).
- C . Configure a new 1AM user in the monitoring account. In each AWS account, configure an 1AM policy to have access to query and visualize the CloudWatch data in the account. Attach the new 1AM policy to the new I AM user.
- D . Create a new 1AM user in the monitoring account. Create cross-account 1AM policies in each AWS account. Attach the 1AM policies to the new 1AM user.
Correct Answer: A
A
Explanation:
CloudWatch cross-account observability is a feature that allows you to monitor and troubleshoot applications that span multiple accounts within a Region. You can seamlessly search, visualize, and analyze your metrics, logs, traces, and Application Insights applications in any of the linked accounts without account boundaries1. To enable CloudWatch cross-account observability, you need to set up one or more AWS accounts as monitoring accounts and link them with multiple source accounts. A monitoring account is a central AWS account that can view and interact with observability data shared by other accounts. A source account is an individual AWS account that shares observability data and resources with one or more monitoring accounts1. To create links between monitoring accounts and source accounts, you can use the CloudWatch console, the AWS CLI, or the AWS API. You can also use AWS Organizations to link accounts in an organization or organizational unit to the monitoring account1. CloudWatch provides a CloudFormation template that you can deploy in each source account to share observability data with the monitoring account. The template creates a sink resource in the monitoring account and an observability link resource in the source account. The template also creates the necessary IAM roles and policies to allow cross-account access to the observability data2. Therefore, the solution that meets the requirements of the question is to enable CloudWatch cross-account observability for the monitoring account and deploy the CloudFormation template provided by the monitoring account in each AWS account to share the data with the monitoring account.
The other options are not valid because:
Service control policies (SCPs) are a type of organization policy that you can use to manage permissions in your organization. SCPs offer central control over the maximum available permissions for all accounts in your organization, allowing you to ensure your accounts stay within your organization’s access control guidelines3. SCPs do not provide access to CloudWatch in the monitoring account, but rather restrict the actions that users and roles can perform in the source accounts. SCPs are not required to enable CloudWatch cross-account observability, as the CloudFormation template creates the necessary IAM roles and policies for cross-account access2.
IAM users are entities that you create in AWS to represent the people or applications that use them to interact with AWS. IAM users can have permissions to access the resources in your AWS account4. Configuring a new IAM user in the monitoring account and an IAM policy in each AWS account to have access to query and visualize the CloudWatch data in the account is not a valid solution, as it does not enable CloudWatch cross-account observability. This solution would require the IAM user to switch between different accounts to view the observability data, which is not seamless and efficient. Moreover, this solution would not allow the IAM user to search, visualize, and analyze metrics, logs, traces, and Application Insights applications across multiple accounts in a single place1.
Cross-account IAM policies are policies that allow you to delegate access to resources that are in different AWS accounts that you own. You attach a cross-account policy to a user or group in one account, and then specify which accounts the user or group can access5. Creating a new IAM user in the monitoring account and cross-account IAM policies in each AWS account is not a valid solution, as it does not enable CloudWatch cross-account observability. This solution would also require the IAM user to switch between different accounts to view the observability data, which is not seamless and efficient. Moreover, this solution would not allow the IAM user to search, visualize, and analyze metrics, logs, traces, and Application Insights applications across multiple accounts in a single place1.
Reference: CloudWatch cross-account observability, CloudFormation template for CloudWatch cross-account observability, Service control policies, IAM users, Cross-account IAM policies
A
Explanation:
CloudWatch cross-account observability is a feature that allows you to monitor and troubleshoot applications that span multiple accounts within a Region. You can seamlessly search, visualize, and analyze your metrics, logs, traces, and Application Insights applications in any of the linked accounts without account boundaries1. To enable CloudWatch cross-account observability, you need to set up one or more AWS accounts as monitoring accounts and link them with multiple source accounts. A monitoring account is a central AWS account that can view and interact with observability data shared by other accounts. A source account is an individual AWS account that shares observability data and resources with one or more monitoring accounts1. To create links between monitoring accounts and source accounts, you can use the CloudWatch console, the AWS CLI, or the AWS API. You can also use AWS Organizations to link accounts in an organization or organizational unit to the monitoring account1. CloudWatch provides a CloudFormation template that you can deploy in each source account to share observability data with the monitoring account. The template creates a sink resource in the monitoring account and an observability link resource in the source account. The template also creates the necessary IAM roles and policies to allow cross-account access to the observability data2. Therefore, the solution that meets the requirements of the question is to enable CloudWatch cross-account observability for the monitoring account and deploy the CloudFormation template provided by the monitoring account in each AWS account to share the data with the monitoring account.
The other options are not valid because:
Service control policies (SCPs) are a type of organization policy that you can use to manage permissions in your organization. SCPs offer central control over the maximum available permissions for all accounts in your organization, allowing you to ensure your accounts stay within your organization’s access control guidelines3. SCPs do not provide access to CloudWatch in the monitoring account, but rather restrict the actions that users and roles can perform in the source accounts. SCPs are not required to enable CloudWatch cross-account observability, as the CloudFormation template creates the necessary IAM roles and policies for cross-account access2.
IAM users are entities that you create in AWS to represent the people or applications that use them to interact with AWS. IAM users can have permissions to access the resources in your AWS account4. Configuring a new IAM user in the monitoring account and an IAM policy in each AWS account to have access to query and visualize the CloudWatch data in the account is not a valid solution, as it does not enable CloudWatch cross-account observability. This solution would require the IAM user to switch between different accounts to view the observability data, which is not seamless and efficient. Moreover, this solution would not allow the IAM user to search, visualize, and analyze metrics, logs, traces, and Application Insights applications across multiple accounts in a single place1.
Cross-account IAM policies are policies that allow you to delegate access to resources that are in different AWS accounts that you own. You attach a cross-account policy to a user or group in one account, and then specify which accounts the user or group can access5. Creating a new IAM user in the monitoring account and cross-account IAM policies in each AWS account is not a valid solution, as it does not enable CloudWatch cross-account observability. This solution would also require the IAM user to switch between different accounts to view the observability data, which is not seamless and efficient. Moreover, this solution would not allow the IAM user to search, visualize, and analyze metrics, logs, traces, and Application Insights applications across multiple accounts in a single place1.
Reference: CloudWatch cross-account observability, CloudFormation template for CloudWatch cross-account observability, Service control policies, IAM users, Cross-account IAM policies
Question #206
A company stores confidential data in an Amazon Aurora PostgreSQL database in the ap-southeast-3 Region. The database is encrypted with an AWS Key Management Service (AWS KMS) customer managed key. The company was recently acquired and must securely share a backup of the database with the acquiring company’s AWS account in ap-southeast-3.
What should a solutions architect do to meet these requirements?
- A . Create a database snapshot Copy the snapshot to a new unencrypted snapshot Share the new snapshot with the acquiring company’s AWS account
- B . Create a database snapshot Add the acquiring company’s AWS account to the KMS key policy Share the snapshot with the acquiring company’s AWS account
- C . Create a database snapshot that uses a different AWS managed KMS key Add the acquiring company’s AWS account to the KMS key alias. Share the snapshot with the acquiring company’s AWS
account. - D . Create a database snapshot Download the database snapshot Upload the database snapshot to an Amazon S3 bucket Update the S3 bucket policy to allow access from the acquiring company’s AWS account
Correct Answer: B
B
Explanation:
https://docs.aws.amazon.com/kms/latest/developerguide/key-policy-modifying-external-accounts.html
There’s no need to create another custom AWS KMS key. https://aws.amazon.com/premiumsupport/knowledge-center/aurora-share-encrypted-snapshot/ Give target account access to the custom AWS KMS key within the source account 1. Log in to the source account, and go to the AWS KMS console in the same Region as the DB cluster snapshot. 2. Select Customer-managed keys from the navigation pane. 3. Select your custom AWS KMS key (ALREADY CREATED) 4. From the Other AWS accounts section, select Add another AWS account, and then enter the AWS account number of your target account. Then: Copy and share the DB cluster snapshot
B
Explanation:
https://docs.aws.amazon.com/kms/latest/developerguide/key-policy-modifying-external-accounts.html
There’s no need to create another custom AWS KMS key. https://aws.amazon.com/premiumsupport/knowledge-center/aurora-share-encrypted-snapshot/ Give target account access to the custom AWS KMS key within the source account 1. Log in to the source account, and go to the AWS KMS console in the same Region as the DB cluster snapshot. 2. Select Customer-managed keys from the navigation pane. 3. Select your custom AWS KMS key (ALREADY CREATED) 4. From the Other AWS accounts section, select Add another AWS account, and then enter the AWS account number of your target account. Then: Copy and share the DB cluster snapshot
Question #207
A company deploys its applications on Amazon Elastic Kubernetes Service (Amazon EKS) behind an Application Load Balancer in an AWS Region. The application needs to store data in a PostgreSQL database engine. The company wants the data in the database to be highly available. The company also needs increased capacity for read workloads.
Which solution will meet these requirements with the MOST operational efficiency?
- A . Create an Amazon DynamoDB database table configured with global tables.
- B . Create an Amazon RDS database with Multi-AZ deployments
- C . Create an Amazon RDS database with Multi-AZ DB cluster deployment.
- D . Create an Amazon RDS database configured with cross-Region read replicas.
Correct Answer: C
C
Explanation:
Amazon RDS Multi-AZ DB cluster deployment ensures high availability by automatically replicating data across multiple Availability Zones (AZs), and it supports failover in case of a failure in one AZ. This setup also provides increased capacity for read workloads by allowing read scaling with reader instances in different AZs. This solution offers the most operational efficiency with minimal manual intervention.
Option A (DynamoDB): DynamoDB is not suitable for a relational database workload, which requires a PostgreSQL engine.
Option B (RDS with Multi-AZ): While this provides high availability, it doesn’t offer read scaling capabilities.
Option D (Cross-Region Read Replicas): This adds complexity and is not necessary if the requirement is high availability within a single region.
AWS
Reference: Amazon RDS Multi-AZ DB Cluster
C
Explanation:
Amazon RDS Multi-AZ DB cluster deployment ensures high availability by automatically replicating data across multiple Availability Zones (AZs), and it supports failover in case of a failure in one AZ. This setup also provides increased capacity for read workloads by allowing read scaling with reader instances in different AZs. This solution offers the most operational efficiency with minimal manual intervention.
Option A (DynamoDB): DynamoDB is not suitable for a relational database workload, which requires a PostgreSQL engine.
Option B (RDS with Multi-AZ): While this provides high availability, it doesn’t offer read scaling capabilities.
Option D (Cross-Region Read Replicas): This adds complexity and is not necessary if the requirement is high availability within a single region.
AWS
Reference: Amazon RDS Multi-AZ DB Cluster
Question #208
A company uses Amazon API Gateway to run a private gateway with two REST APIs in the same VPC. The BuyStock RESTful web service calls the CheckFunds RESTful web service to ensure that enough funds are available before a stock can be purchased. The company has noticed in the VPC flow logs that the BuyStock RESTful web service calls the CheckFunds RESTful web service over the internet instead of through the VPC. A solutions architect must implement a solution so that the APIs communicate through the VPC.
Which solution will meet these requirements with the FEWEST changes to the code? (Select Correct Option/s and give detailed explanation from AWS Certified Solutions Architect – Associate (SAA-C03) Study Manual or documents)
- A . Add an X-APl-Key header in the HTTP header for authorization.
- B . Use an interface endpoint.
- C . Use a gateway endpoint.
- D . Add an Amazon Simple Queue Service (Amazon SQS) queue between the two REST APIs.
Correct Answer: B
B
Explanation:
Using an interface endpoint will allow the BuyStock RESTful web service and the CheckFunds RESTful web service to communicate through the VPC without any changes to the code. An interface endpoint creates an elastic network interface (ENI) in the customer’s VPC, and then configures the route tables to route traffic from the APIs to the ENI. This will ensure that the two APIs will communicate through the VPC without any changes to the code.
B
Explanation:
Using an interface endpoint will allow the BuyStock RESTful web service and the CheckFunds RESTful web service to communicate through the VPC without any changes to the code. An interface endpoint creates an elastic network interface (ENI) in the customer’s VPC, and then configures the route tables to route traffic from the APIs to the ENI. This will ensure that the two APIs will communicate through the VPC without any changes to the code.
Question #209
A company collects temperature, humidity, and atmospheric pressure data in cities across multiple continents. The average volume of data collected per site each day is 500 GB. Each site has a high-speed internet connection. The company’s weather forecasting applications are based in a single Region and analyze the data daily.
What is the FASTEST way to aggregate data from all of these global sites?
- A . Enable Amazon S3 Transfer Acceleration on the destination bucket. Use multipart uploads to directly upload site data to the destination bucket.
- B . Upload site data to an Amazon S3 bucket in the closest AWS Region. Use S3 cross-Region replication to copy objects to the destination bucket.
- C . Schedule AWS Snowball jobs daily to transfer data to the closest AWS Region. Use S3 cross-Region replication to copy objects to the destination bucket.
- D . Upload the data to an Amazon EC2 instance in the closest Region. Store the data in an Amazon Elastic Block Store (Amazon EBS) volume. Once a day take an EBS snapshot and copy it to the centralized Region. Restore the EBS volume in the centralized Region and run an analysis on the data daily.
Correct Answer: A
A
Explanation:
You might want to use Transfer Acceleration on a bucket for various reasons, including the following:
You have customers that upload to a centralized bucket from all over the world.
You transfer gigabytes to terabytes of data on a regular basis across continents.
You are unable to utilize all of your available bandwidth over the Internet when uploading to Amazon S3.
https://docs.aws.amazon.com/AmazonS3/latest/dev/transfer-acceleration.html
https://aws.amazon.com/s3/transfer-
acceleration/#:~:text=S3%20Transfer%20Acceleration%20(S3TA)%20reduces,to%20S3%20for%20rem
ote%20applications:
"Amazon S3 Transfer Acceleration can speed up content transfers to and from Amazon S3 by as much as 50-500%for long-distance transfer of larger objects. Customers who have either web or mobile applications with widespread users or applications hosted far away from their S3 bucket can experience long and variable upload and download speeds over the Internet"
https://docs.aws.amazon.com/AmazonS3/latest/userguide/mpuoverview.html
"Improved throughput – You can upload parts in parallel to improve throughput."
A
Explanation:
You might want to use Transfer Acceleration on a bucket for various reasons, including the following:
You have customers that upload to a centralized bucket from all over the world.
You transfer gigabytes to terabytes of data on a regular basis across continents.
You are unable to utilize all of your available bandwidth over the Internet when uploading to Amazon S3.
https://docs.aws.amazon.com/AmazonS3/latest/dev/transfer-acceleration.html
https://aws.amazon.com/s3/transfer-
acceleration/#:~:text=S3%20Transfer%20Acceleration%20(S3TA)%20reduces,to%20S3%20for%20rem
ote%20applications:
"Amazon S3 Transfer Acceleration can speed up content transfers to and from Amazon S3 by as much as 50-500%for long-distance transfer of larger objects. Customers who have either web or mobile applications with widespread users or applications hosted far away from their S3 bucket can experience long and variable upload and download speeds over the Internet"
https://docs.aws.amazon.com/AmazonS3/latest/userguide/mpuoverview.html
"Improved throughput – You can upload parts in parallel to improve throughput."
Question #210
A company migrated a MySQL database from the company’s on-premises data center to an Amazon RDS for MySQL DB instance. The company sized the RDS DB instance to meet the company’s average daily workload. Once a month, the database performs slowly when the company runs queries for a report. The company wants to have the ability to run reports and maintain the performance of the daily workloads.
Which solution will meet these requirements?
- A . Create a read replica of the database. Direct the queries to the read replica.
- B . Create a backup of the database. Restore the backup to another DB instance. Direct the queries to the new database.
- C . Export the data to Amazon S3. Use Amazon Athena to query the S3 bucket.
- D . Resize the DB instance to accommodate the additional workload.
Correct Answer: C
C
Explanation:
Amazon Athena is a service that allows you to run SQL queries on data stored in Amazon S3. It is serverless, meaning you do not need to provision or manage any infrastructure. You only pay for the queries you run and the amount of data scanned1.
By using Amazon Athena to query your data in Amazon S3, you can achieve the following benefits:
You can run queries for your report without affecting the performance of your Amazon RDS for MySQL DB instance. You can export your data from your DB instance to an S3 bucket and use Athena to query the data in the bucket. This way, you can avoid the overhead and contention of running queries on your DB instance.
You can reduce the cost and complexity of running queries for your report. You do not need to create a read replica or a backup of your DB instance, which would incur additional charges and require maintenance. You also do not need to resize your DB instance to accommodate the additional workload, which would increase your operational overhead.
You can leverage the scalability and flexibility of Amazon S3 and Athena. You can store large amounts of data in S3 and query them with Athena without worrying about capacity or performance limitations. You can also use different formats, compression methods, and partitioning schemes to optimize your data storage and query performance1.
C
Explanation:
Amazon Athena is a service that allows you to run SQL queries on data stored in Amazon S3. It is serverless, meaning you do not need to provision or manage any infrastructure. You only pay for the queries you run and the amount of data scanned1.
By using Amazon Athena to query your data in Amazon S3, you can achieve the following benefits:
You can run queries for your report without affecting the performance of your Amazon RDS for MySQL DB instance. You can export your data from your DB instance to an S3 bucket and use Athena to query the data in the bucket. This way, you can avoid the overhead and contention of running queries on your DB instance.
You can reduce the cost and complexity of running queries for your report. You do not need to create a read replica or a backup of your DB instance, which would incur additional charges and require maintenance. You also do not need to resize your DB instance to accommodate the additional workload, which would increase your operational overhead.
You can leverage the scalability and flexibility of Amazon S3 and Athena. You can store large amounts of data in S3 and query them with Athena without worrying about capacity or performance limitations. You can also use different formats, compression methods, and partitioning schemes to optimize your data storage and query performance1.