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NEW QUESTION 30
A company is running an Apache Hadoop cluster on Amazon EC2 instances. The Hadoop cluster stores approximately 100 TB of data for weekly operational reports and allows occasional access for data scientists to retrieve dat a. The company needs to reduce the cost and operational complexity for storing and serving this data.
Which solution meets these requirements in the MOST cost-effective manner?
- A. Migrate the data to Amazon DynamoDB and modify the reports to fetch data from DynamoDB. Allow the data scientists to access the data directly in DynamoDB.
- B. Write a script that resizes the EC2 instances to a smaller instance type during downtime and resizes the instances to a larger instance type before the reports are created.
- C. Move the data to Amazon S3 and use Amazon Athena to query the data for reports. Allow the data scientists to access the data directly in Amazon S3.
- D. Move the Hadoop cluster from EC2 instances to Amazon EMR. Allow data access patterns to remain the same.
Answer: C
Explanation:
“The company needs to reduce the cost and operational complexity for storing and serving this data. Which solution meets these requirements in the MOST cost-effective manner?” EMR storage is ephemeral. The company has 100TB that need to persist, they would have to use EMRFS to backup to S3 anyway. https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-plan-storage.html
100TB
EBS – 8.109$
S3 – 2.355$
You have saved 5.752$
This amount can be used for Athen. BTW. we don’t know indexes, amount of data that is scanned. What we know is that tit will be: “occasional access for data scientists to retrieve data”
NEW QUESTION 31
A company is migrating its three-tier web application from on-premises to the AWS Cloud. The company has the following requirements for the migration process:
* Ingest machine images from the on-premises environment.
* Synchronize changes from the on-premises environment to the AWS environment until the production cutover.
* Minimize downtime when executing the production cutover.
* Migrate the virtual machines’ root volumes and data volumes.
Which solution will satisfy these requirements with minimal operational overhead?
- A. Use AWS Server Migration Service (SMS) to upload the operating system volumes. Use the AWS CLI import-snaps hot command ‘or the data volumes. Launch instances from the AMIs created by AWS SMS and attach the data volumes to the instances. After initial testing, perform a final replication, launch new instances from the replicated AMIs. and attach the data volumes to the instances.
- B. Create an AWS CLIVM Import/Export script to migrate each virtual machine. Schedule the script to run incrementally to maintain changes in the application. Launch instances from the AMIs created by VM Import/Export. Once testing is done, rerun the script to do a final import and launch the instances from the AMIs.
- C. Use AWS Server Migration Service (SMS) to create and launch a replication job for each tier of the application. Launch instances from the AMIs created by AWS SMS. After initial testing, perform a final replication and create new instances from the updated AMIs.
- D. Use AWS Application Discovery Service and AWS Migration Hub to group the virtual machines as an application. Use the AWS CLI VM Import/Export script to import the virtual machines as AMIs.
Schedule the script to run incrementally to maintain changes in the application. Launch instances from the AMIs. After initial testing, perform a final virtual machine import and launch new instances from the AMIs.
Answer: C
Explanation:
Explanation
SMS can handle migrating the data volumes:
https://aws.amazon.com/about-aws/whats-new/2018/09/aws-server-migration-service-adds-support-for-migrating
NEW QUESTION 32
A company that tracks medical devices in hospitals wants to migrate its existing storage solution to the AWS Cloud. The company equips all of its devices with sensors that collect location and usage information. This sensor data is sent in unpredictable patterns with large spikes. The data is stored in a MySQL database running on premises at each hospital. The company wants the cloud storage solution to scale with usage.
The company’s analytics team uses the sensor data to calculate usage by device type and hospital. The team needs to keep analysis tools running locally while fetching data from the cloud. The team also needs to use existing Java application and SQL queries with as few changes as possible.
How should a solutions architect meet these requirements while ensuring the sensor data is secure?
- A. Store the data in an Amazon S3 bucket. Serve the data through Amazon Athena using AWS PrivateLink to secure the data in transit.
- B. Store the data in an Amazon Aurora Serverless database. Serve the data through the Aurora Data API using an IAM user authorized with AWS Identity and Access Management (IAM) and the AWS Secrets Manager ARN.
- C. Store the data in an Amazon S3 bucket. Serve the data through Amazon QuickSight using an IAM user authorized with AWS Identity and Access Management (IAM) with the S3 bucket as the data source.
- D. Store the data in an Amazon Aurora Serverless database. Serve the data through a Network Load Balancer (NLB). Authenticate users using the NLB with credentials stored in AWS Secrets Manager.
Answer: B
Explanation:
Explanation
https://aws.amazon.com/blogs/aws/new-data-api-for-amazon-aurora-serverless/
https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/data-api.html
https://aws.amazon.com/blogs/aws/aws-privatelink-for-amazon-s3-now-available/
https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/data-api.html#data-api.access The data is currently stored in a MySQL database running on-prem. Storing MySQL data in S3 doesn’t sound good so B & D are out. Aurora Data API “enables the SQL HTTP endpoint, a connectionless Web Service API for running SQL queries against this database. When the SQL HTTP endpoint is enabled, you can also query your database from inside the RDS console (these features are free to use).”
NEW QUESTION 33
A company’s CI SO has asked a solutions architect to re-engineer the company’s current CI/CD practices to make sure patch deployments to its application can happen as quickly as possible with minimal downtime if vulnerabilities are discovered The company must also be able to quickly roll back a change in case of errors.
The web application is deployed in a fleet of Amazon EC2 instances behind an Application Load Balancer The company is currently using GitHub to host the application source code. and has configured an AWS CodeBuild project to build the application The company also intends to use AWS CodePipeline to trigger builds from GitHub commits using the existing CodeBuild project.
What CI/CD configuration meets all of the requirements?
- A. Configure CodePipeline with a deploy stage using AWS CloudFormation to create a pipeline for test and production stacks Monitor the newly deployed code, and, if there are any issues, push another code update
- B. Configure the CodePipeline with a deploy stage using AWS OpsWorks and m-place deployments Monitor the newly deployed code and. if there are any issues, push another code update
- C. Configure CodePipeline with a deploy stage using AWS CodeDeploy configured for in-place deployment Monitor the newly deployed code, and, if there are any issues, push another code update
- D. Configure CodePipeline with a deploy stage using AWS CodeDeploy configured for blue/green deployments Monitor the newly deployed code and if there are any issues, trigger a manual rollback using CodeDeploy
Answer: D
NEW QUESTION 34
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