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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q224-Q229):

NEW QUESTION # 224
A DevOps team manages an API running on-premises that serves as a backend for an Amazon API Gateway endpoint. Customers have been complaining about high response latencies, which the development team has verified using the API Gateway latency metrics in Amazon CloudWatch. To identify the cause, the team needs to collect relevant data without introducing additional latency.
Which actions should be taken to accomplish this? (Choose two.)

  • A. Modify the on-premises application to send log information back to API Gateway with each request.
  • B. Enable AWS X-Ray tracing in API Gateway, modify the application to capture request segments, and use the X-Ray daemon to upload segments to X-Ray.
  • C. Modify the on-premises application to calculate and upload statistical data relevant to the API service requests to CloudWatch metrics.
  • D. Enable AWS X-Ray tracing in API Gateway, modify the application to capture request segments, and upload those segments to X-Ray during each request.
  • E. Install the CloudWatch agent server side and configure the agent to upload relevant logs to CloudWatch.

Answer: B,E

Explanation:
Explanation
https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/install-CloudWatch-Agent-on-premise.htm
https://docs.aws.amazon.com/xray/latest/devguide/xray-api-sendingdata.html


NEW QUESTION # 225
A company is developing an application that will generate log events. The log events consist of five distinct metrics every one tenth of a second and produce a large amount of data The company needs to configure the application to write the logs to Amazon Time stream The company will configure a daily query against the Timestream table.
Which combination of steps will meet these requirements with the FASTEST query performance? (Select THREE.)

  • A. Treat each log as a multi-measure record
  • B. Configure the memory store retention period to be shorter than the magnetic store retention period
  • C. Treat each log as a single-measure record
  • D. Use batch writes to write multiple log events in a Single write operation
  • E. Configure the memory store retention period to be longer than the magnetic store retention period
  • F. Write each log event as a single write operation

Answer: A,B,D

Explanation:
Explanation
A comprehensive and detailed explanation is:
* Option A is correct because using batch writes to write multiple log events in a single write operation is a recommended practice for optimizing the performance and cost of data ingestion in Timestream. Batch writes can reduce the number of network round trips and API calls, and can also take advantage of parallel processing by Timestream. Batch writes can also improve the compression ratio of data in the
* memory store and the magnetic store, which can reduce the storage costs and improve the query performance1.
* Option B is incorrect because writing each log event as a single write operation is not a recommended practice for optimizing the performance and cost of data ingestion in Timestream. Writing each log event as a single write operation would increase the number of network round trips and API calls, and would also reduce the compression ratio of data in the memory store and the magnetic store. This would increase the storage costs and degrade the query performance1.
* Option C is incorrect because treating each log as a single-measure record is not a recommended practice for optimizing the query performance in Timestream. Treating each log as a single-measure record would result in creating multiple records for each timestamp, which would increase the storage size and the query latency. Moreover, treating each log as a single-measure record would require using joins to query multiple measures for the same timestamp, which would add complexity and overhead to the query processing2.
* Option D is correct because treating each log as a multi-measure record is a recommended practice for optimizing the query performance in Timestream. Treating each log as a multi-measure record would result in creating a single record for each timestamp, which would reduce the storage size and the query latency. Moreover, treating each log as a multi-measure record would allow querying multiple measures for the same timestamp without using joins, which would simplify and speed up the query processing2.
* Option E is incorrect because configuring the memory store retention period to be longer than the magnetic store retention period is not a valid option in Timestream. The memory store retention period must always be shorter than or equal to the magnetic store retention period. This ensures that data is moved from the memory store to the magnetic store before it expires out of the memory store3.
* Option F is correct because configuring the memory store retention period to be shorter than the magnetic store retention period is a valid option in Timestream. The memory store retention period determines how long data is kept in the memory store, which is optimized for fast point-in-time queries.
The magnetic store retention period determines how long data is kept in the magnetic store, which is optimized for fast analytical queries. By configuring these retention periods appropriately, you can balance your storage costs and query performance according to your application needs3.
References:
* 1: Batch writes
* 2: Multi-measure records vs. single-measure records
* 3: Storage


NEW QUESTION # 226
A company is launching an application that stores raw data in an Amazon S3 bucket. Three applications need to access the data to generate reports. The data must be redacted differently for each application before the applications can access the data.
Which solution will meet these requirements?

  • A. Create an S3 bucket for each application. Configure S3 Same-Region Replication (SRR) from the raw data's S3 bucket to each application's S3 bucket. Configure each application to consume data from its own S3 bucket.
  • B. Create an S3 access point that uses the raw data's S3 bucket as the destination. For each application, create an S3 Object Lambda access point that uses the S3 access point. Configure the AWS Lambda function for each S3 Object Lambda access point to redact data when objects are retrieved. Configure each application to consume data from its own S3 Object Lambda access point.
  • C. For each application, create an S3 access point that uses the raw data's S3 bucket as the destination.
    Create an AWS Lambda function that is invoked by object creation events in the raw data's S3 bucket.
    Program the Lambda function to redact data for each application. Store the data in each application's S3 access point. Configure each application to consume data from its own S3 access point.
  • D. Create an Amazon Kinesis data stream. Create an AWS Lambda function that is invoked by object creation events in the raw data's S3 bucket. Program the Lambda function to redact data for each application. Publish the data on the Kinesis data stream. Configure each application to consume data from the Kinesis data stream.

Answer: B

Explanation:
Explanation
The best solution is to use S3 Object Lambda1, which allows you to add your own code to S3 GET, LIST, and HEAD requests to modify and process data as it is returned to an application2. This way, you can redact the data differently for each application without creating and storing multiple copies of the data or running proxies.
The other solutions are less efficient or scalable because they require replicating the data to multiple buckets, streaming the data through Kinesis, or storing the data in S3 access points.
References: 1: Amazon S3 Features | Object Lambda | AWS 2: Transforming objects with S3 Object Lambda - Amazon Simple Storage Service


NEW QUESTION # 227
A Company uses AWS CodeCommit for source code control. Developers apply their changes to various feature branches and create pull requests to move those changes to the main branch when the changes are ready for production.
The developers should not be able to push changes directly to the main branch. The company applied the AWSCodeCommitPowerUser managed policy to the developers' IAM role, and now these developers can push changes to the main branch directly on every repository in the AWS account.
What should the company do to restrict the developers' ability to push changes to the main branch directly?

  • A. Remove the IAM policy, and add an AWSCodeCommitReadOnly managed policy. Add an Allow rule for the GitPush and PutFile actions for the specific repositories in the policy statement with a condition that references the mam branch.
  • B. Create an additional policy to include an Allow rule for the GitPush and PutFile actions. Include a restriction for the specific repositories in the policy statement with a condition that references the feature branches.
  • C. Create an additional policy to include a Deny rule for the GitPush and PutFile actions. Include a restriction for the specific restriction for the specific repositories in the policy repositories in the policy statement with a condition that references the main branch.
    A Create an additional policy to include a Deny rule for the GitPush and PutFile actions Include a restriction for the specific repositories in the policy statement with a condition that references the main branch
  • D. Modify the IAM policy Include a Deny rule for the GitPush and PutFile actions for the specific repositories in the policy statement with a condition that references the main branch.

Answer: C

Explanation:
By default, the AWSCodeCommitPowerUser managed policy allows users to push changes to any branch in any repository in the AWS account. To restrict the developers' ability to push changes to the main branch directly, an additional policy is needed that explicitly denies these actions for the main branch.
The Deny rule should be included in a policy statement that targets the specific repositories and includes a condition that references the main branch. The policy statement should look something like this:
{
"Effect": "Deny",
"Action": [
"codecommit:GitPush",
"codecommit:PutFile"
],
"Resource": "arn:aws:codecommit:<region>:<account-id>:<repository-name>",
"Condition": {
"StringEqualsIfExists": {
"codecommit:References": [
"refs/heads/main"
]
}
}


NEW QUESTION # 228
A company uses an organization in AWS Organizations to manage its AWS accounts. The company recently acquired another company that has standalone AWS accounts. The acquiring company's DevOps team needs to consolidate the administration of the AWS accounts for both companies and retain full administrative control of the accounts. The DevOps team also needs to collect and group findings across all the accounts to implement and maintain a security posture.
Which combination of steps should the DevOps team take to meet these requirements? (Select TWO.)

  • A. Invite the acquired company's AWS accounts to join the organization. Create the OrganizationAccountAccessRole 1AM role in the invited accounts. Grant permission to the management account to assume the role.
  • B. Use Amazon Inspector to collect and group findings across all accounts. Designate an account in the organization as the delegated administrator account for Amazon Inspector.
  • C. Use AWS Security Hub to collect and group findings across all accounts. Use Security Hub to automatically detect new accounts as the accounts are added to the organization.
  • D. Use AWS Firewall Manager to collect and group findings across all accounts. Enable all features for the organization. Designate an account in the organization as the delegated administrator account for Firewall Manager.
  • E. Invite the acquired company's AWS accounts to join the organization. Create an SCP that has full administrative privileges. Attach the SCP to the management account.

Answer: A,C

Explanation:
The correct answer is B and C. Option B is correct because inviting the acquired company's AWS accounts to join the organization and creating the OrganizationAccountAccessRole IAM role in the invited accounts allows the management account to assume the role and gain full administrative access to the member accounts. Option C is correct because using AWS Security Hub to collect and group findings across all accounts enables the DevOps team to monitor and improve the security posture of the organization. Security Hub can automatically detect new accounts as the accounts are added to the organization and enable Security Hub for them. Option A is incorrect because creating an SCP that has full administrative privileges and attaching it to the management account does not grant the management account access to the member accounts. SCPs are used to restrict the permissions of the member accounts, not to grant permissions to the management account. Option D is incorrect because using AWS Firewall Manager to collect and group findings across all accounts is not a valid use case for Firewall Manager. Firewall Manager is used to centrally configure and manage firewall rules across the organization, not to collect and group security findings. Option E is incorrect because using Amazon Inspector to collect and group findings across all accounts is not a valid use case for Amazon Inspector. Amazon Inspector is used to assess the security and compliance of applications running on Amazon EC2 instances, not to collect and group security findings across accounts. Reference:
Inviting an AWS account to join your organization
Enabling and disabling AWS Security Hub
Service control policies
AWS Firewall Manager
Amazon Inspector


NEW QUESTION # 229
......

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