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NEW QUESTION 21
A company receives clickstream data files to Amazon S3 every five minutes. A Python script runs as a cron job once a day on an Amazon EC2 instance to process each file and load it into a database hosted on Amazon RDS. The cron job takes 15 to 30 minutes to process 24 hours of dat a. The data consumers ask for the data be available as soon as possible.
Which solution would accomplish the desired outcome?

A. Create an AWS Lambda function that runs when a file is delivered to Amazon S3 using S3 event notifications.B. Convert the cron job to an AWS Lambda function and schedule it to run once an hour using Amazon CloudWatch events.C. Increase the size of the instance to speed up processing and update the schedule to run once an hour.D. Convert the cron job to an AWS Lambda function and trigger this new function using a cron job on an EC2 instance.

Answer: A

Explanation:
https://docs.aws.amazon.com/lambda/latest/dg/with-s3.html

 

NEW QUESTION 22
A user is trying to create a PIOPS EBS volume with 3 GB size and 90 IOPS. Will AWS create the volume?

A. No, the EBS size is less than 4GBB. Yes, since PIOPS is higher than 100C. Yes, since the ratio between EBS and IOPS is less than 30D. No, since the PIOPS and EBS size ratio is less than 30

Answer: A

Explanation:
Explanation
A Provisioned IOPS (SSD) volume can range in size from 4 GiB to 16 TiB and you can provision up to 20,000 IOPS per volume.
http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSVolumeTypes.html#EBSVolumeTypes_piops

 

NEW QUESTION 23
A company has a large on-premises Apache Hadoop cluster with a 20 PB HDFS database. The cluster is growing every quarter by roughly 200 instances and 1 PB. The company's goals are to enable resiliency for its Hadoop data, limit the impact of losing cluster nodes, and significantly reduce costs. The current cluster runs
24/7 and supports a variety of analysis workloads, including interactive queries and batch processing.
Which solution would meet these requirements with the LEAST expense and down time?

A. Use AWS Direct Connect to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.B. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster of similar size and configuration to the current cluster. Store the data on EMRFS.
Minimize costs by using Reserved Instances. As the workload grows each quarter, purchase additional Reserved Instances and add to the cluster.C. Use AWS Snowball to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workloads based on historical data from the on-premises cluster. Store the on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.D. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.

Answer: C

 

NEW QUESTION 24
A company is using AWS CodePipeline for the CI/CO of an application to an Amazon EC2 Auto Scaling group. All AWS resources are defined in AWS CloudFormation templates. The application artifacts are stored in an Amazon S3 bucket and deployed to the Auto Scaling group using instance user data scripts. As the application has become more complex, recent resource changes in the Cloud Formation templates have caused unplanned downtime.
How should a solutions architect improve the CI'CD pipeline to reduce the likelihood that changes in the templates will cause downtime?

A. Use AWS CodeDeploy and a blue/green deployment pattern with CloudFormation to replace the user data deployment scripts. Have the operators log in to running instances and go through a manual test plan to verify the application is running as expected.B. Implement automated testing using AWS CodeBuild in a test environment. Use CloudFormation change sets to evaluate changes before deployment. Use AWS CodeDeploy to leverage blue/green deployment patterns to allow evaluations and the ability to revert changes, if needed.C. Use plugins for the integrated development environment (IDE) to check the templates for errors, and use the AWS CLI to validate that the templates are correct. Adapt the deployment code to check for error conditions and generate notifications on errors. Deploy to a test environment and execute a manual test plan before approving the change for production.D. Adapt the deployment scripts to detect and report CloudFormation error conditions when performing deployments. Write test plans for a testing team to execute in a non-production environment before approving the change for production.

Answer: B

Explanation:
https://aws.amazon.com/blogs/devops/performing-bluegreen-deployments-with-aws-codedeploy-and-auto-scaling-groups/
When one adopts go infrastructure as code, we need to test the infrastructure code as well via automated testing, and revert to original if things are not performing correctly.

 

NEW QUESTION 25
A company has multiple business units Each business unit has its own AWS account and runs a single website within that account. The company also has a single logging account. Logs from each business unit website are aggregated into a single Amazon S3 bucket in the logging account The S3 bucket policy provides each business unit with access to write data into the bucket and requires data to be encrypted.
The company needs to encrypt logs uploaded into the bucket us-ng a 5 ngle AWS Key Management Service {AWS KMS) CMK The CMK that protects the data must be rotated once every 365 days
Which strategy is the MOST operationally efficient for the company to use to meet these requirements'?

A. Create a customer managed CMK in the logging account. Update the CMK key policy to provide access to the logging account and business unit accounts. Enable automatic rotation of the CMKB. Use an AWS managed CMK m the togging account. Update the CMK key policy to provide access to the logging account and business unit accounts Manually rotate the CMK every 365 days.C. Use an AWS managed CMK in the togging account Update the CMK key policy to provide access to the togging account only. Enable automatic rotation of the CMK.D. Create a customer managed CMK ri the logging account Update the CMK key policy to provide access to the logging account only Manually rotate the CMK every 365 days.

Answer: B

 

NEW QUESTION 26
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