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NEW QUESTION # 46
A company requires its developers to tag all Amazon Elastic Block Store (Amazon EBS) volumes in an account to indicate a desired backup frequency. This requirement Includes EBS volumes that do not require backups. The company uses custom tags named Backup_Frequency that have values of none, dally, or weekly that correspond to the desired backup frequency. An audit finds that developers are occasionally not tagging the EBS volumes.
A DevOps engineer needs to ensure that all EBS volumes always have the Backup_Frequency tag so that the company can perform backups at least weekly unless a different value is specified.
Which solution will meet these requirements?
Answer: B
Explanation:
The following are the steps that the DevOps engineer should take to ensure that all EBS volumes always have the Backup_Frequency tag so that the company can perform backups at least weekly unless a different value is specified:
* Set up AWS Config in the account.
* Use a managed rule that returns a compliance failure for EC2::Volume resources that do not have a Backup Frequency tag applied.
* Configure a remediation action that uses a custom AWS Systems Manager Automation runbook to apply the Backup_Frequency tag with a value of weekly.
The managed ruleAWS::Config::EBSVolumesWithoutBackupTagwill return a compliance failure for any EBS volume that does not have the Backup_Frequency tag applied. The remediation action will then use the Systems Manager Automation runbook to apply the Backup_Frequency tag with a value of weekly to the EBS volume.
NEW QUESTION # 47
A large enterprise is deploying a web application on AWS. The application runs on Amazon EC2 instances behind an Application Load Balancer. The instances run in an Auto Scaling group across multiple Availability Zones. The application stores data in an Amazon RDS for Oracle DB instance and Amazon DynamoDB.
There are separate environments tor development testing and production.
What is the MOST secure and flexible way to obtain password credentials during deployment?
Answer: B
Explanation:
AWS Secrets Manager is a secrets management service that helps you protect access to your applications, services, and IT resources. This service enables you to easily rotate, manage, and retrieve database credentials, API keys, and other secrets throughout their lifecycle. Using Secrets Manager, you can secure and manage secrets used to access resources in the AWS Cloud, on third-party services, and on-premises. SSM parameter store and AWS Secret manager are both a secure option. However, Secrets manager is more flexible and has more options like password generation.Reference:https://www.1strategy.com/blog/2019/02/28
/aws-parameter-store-vs-aws-secrets-manager/
NEW QUESTION # 48
A company has implemented a new microservices-based application on an Amazon Elastic Container Service (Amazon ECS) cluster. After each deployment, the company wants to validate the critical user journeys and API endpoints before routing traffic to the new application version.
The company must implement an automated solution to detect issues in the new deployment and to initiate a rollback if necessary.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: C
Explanation:
The requirement is specifically to validate critical user journeys and API endpoints after each deployment and before routing traffic. The most direct AWS-native way to test "real" user flows and endpoints automatically is CloudWatch Synthetics canaries, which can run scripted checks (HTTP/API and browser-style journeys).
Option D minimizes operational overhead because it uses a straightforward managed pattern:
Canaries run against the new deployment to validate endpoints and journeys.
CloudWatch alarms trigger when the canaries fail (objective signal of broken journeys/APIs).
The solution then uses alarm-driven rollback (the intent here is automated rollback without writing custom analysis code or managing multi-service workflows).
Why the other options have more overhead or miss the "user journey/API validation" goal as cleanly:
A focuses on ECS task states (healthy/unhealthy tasks). That can detect deployment failures, but it doesn't validate critical user journeys or API correctness. Also requires custom Lambda logic for analysis + rollback control.
B adds even more moving parts (Application Insights + alarms + EventBridge + Step Functions). Also, monitoring KPIs is not the same as explicitly validating journeys/endpoints before routing traffic.
C is the highest overhead: canaries plus X-Ray instrumentation across all microservices, trace exporting, custom Lambda analysis, etc. That's heavy compared to canary + alarm.
NEW QUESTION # 49
A company uses AWS CodeArtifact to centrally store Python packages. The CodeArtifact repository is configured with the following repository policy.
A development team is building a new project in an account that is in an organization in AWS Organizations.
The development team wants to use a Python library that has already been stored in the CodeArtifact repository in the organization. The development team uses AWS CodePipeline and AWS CodeBuild to build the new application. The CodeBuild job that the development team uses to build the application is configured to run in a VPC Because of compliance requirements the VPC has no internet connectivity.
The development team creates the VPC endpoints for CodeArtifact and updates the CodeBuild buildspec yaml file. However, the development team cannot download the Python library from the repository.
Which combination of steps should a DevOps engineer take so that the development team can use Code Artifact? (Select TWO.)
Answer: A,B
Explanation:
Explanation
"AWS CodeArtifact operates in multiple Availability Zones and stores artifact data and metadata in Amazon S3 and Amazon DynamoDB. Your encrypted data is redundantly stored across multiple facilities and multiple devices in each facility, making it highly available and highly durable."
https://aws.amazon.com/codeartifact/features/ With no internet connectivity, a gateway endpoint becomes necessary to access S3.
NEW QUESTION # 50
A company uses Amazon Redshift as its data warehouse solution. The company wants to create a dashboard to view changes to the Redshift users and the queries the users perform.
Which combination of steps will meet this requirement? (Select TWO.)
Answer: A,C
Explanation:
Amazon Redshift supports audit logging which can be configured to log user activity, including queries and user changes. The logs can be delivered to an S3 bucket (Option B), which is the standard location for Redshift audit logs.
While Redshift can send some logs to CloudWatch, the native audit logging is typically routed to S3. Creating a CloudWatch dashboard with a log widget (Option D) allows visualization of user activities from logs ingested into CloudWatch Logs or through custom processing.
Option A is invalid because CloudTrail does not capture Redshift query logs directly. Option C incorrectly assumes Redshift audit logs can be delivered directly to CloudWatch. Option E adds complexity by requiring Lambda and Athena unnecessarily when direct visualization in CloudWatch is simpler.
References:
Amazon Redshift Audit Logging
Visualizing Logs with Amazon CloudWatch Dashboards
NEW QUESTION # 51
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