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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q251-Q256):
NEW QUESTION # 251
A company is migrating its on-premises Windows applications and Linux applications to AWS. The company will use automation to launch Amazon EC2 instances to mirror the on-premises configurations. The migrated applications require access to shared storage that uses SMB for Windows and NFS for Linux.
The company is also creating a pilot light disaster recovery (DR) environment in another AWS Region. The company will use automation to launch and configure the EC2 instances in the DR Region. The company needs to replicate the storage to the DR Region.
Which storage solution will meet these requirements?
Answer: D
Explanation:
To meet the requirements of migrating its on-premises Windows and Linux applications to AWS and creating a pilot light DR environment in another AWS Region, the company should use Amazon FSx for NetApp ONTAP for the application storage. Amazon FSx for NetApp ONTAP is a fully managed service that provides highly reliable, scalable, high-performing, and feature-rich file storage built on NetApp's popular ONTAP file system. FSx for ONTAP supports multiple protocols, including SMB for Windows and NFS for Linux, so the company can access the shared storage from both types of applications. FSx for ONTAP also supports NetApp SnapMirror replication, which enables the company to replicate the storage to the DR Region. NetApp SnapMirror replication is efficient, secure, and incremental, and it preserves the data deduplication and compression benefits of FSx for ONTAP. The company can use automation to launch and configure the EC2 instances in the DR Region and then use NetApp SnapMirror to restore the data from the primary Region.
The other options are not correct because they do not meet the requirements or follow best practices. Using Amazon S3 for the application storage is not a good option because S3 is an object storage service that does not support SMB or NFS protocols natively. The company would need to use additional services or software to mount S3 buckets as file systems, which would add complexity and cost. Using Amazon EBS for the application storage is also not a good option because EBS is a block storage service that does not support SMB or NFS protocols natively. The company would need to set up and manage file servers on EC2 instances to provide shared access to the EBS volumes, which would add overhead and maintenance. Using a Volume Gateway in AWS Storage Gateway for the application storage is not a valid option because Volume Gateway does not support SMB protocol. Volume Gateway only supports iSCSI protocol, which means that only Linux applications can access the shared storage.
1: What is Amazon FSx for NetApp ONTAP? - FSx for ONTAP
2: Amazon FSx for NetApp ONTAP
3: Amazon FSx for NetApp ONTAP | NetApp
4: AWS Announces General Availability of Amazon FSx for NetApp ONTAP
Replicating Data with NetApp SnapMirror - FSx for ONTAP
What Is Amazon S3? - Amazon Simple Storage Service
What Is Amazon Elastic Block Store (Amazon EBS)? - Amazon Elastic Compute Cloud What Is AWS Storage Gateway? - AWS Storage Gateway
NEW QUESTION # 252
A company is implementing a well-architected design for its globally accessible API stack. The design needs to ensure both high reliability and fast response times for users located in North America and Europe.
The API stack contains the following three tiers:
Amazon API Gateway
AWS Lambda
Amazon DynamoDB
Which solution will meet the requirements?
Answer: A
NEW QUESTION # 253
A company is building a web and mobile application that uses a serverless architecture powered by AWS Lambda and Amazon API Gateway The company wants to fully automate the backend Lambda deployment based on code that is pushed to the appropriate environment branch in an AWS CodeCommit repository The deployment must have the following:
* Separate environment pipelines for testing and production
* Automatic deployment that occurs for test environments only
Which steps should be taken to meet these requirements'?
Answer: C
Explanation:
Explanation
The correct approach to meet the requirements for separate environment pipelines and automatic deployment for test environments is to create two AWS CodePipeline configurations, one for each environment. The production pipeline should have a manual approval step to ensure that changes are reviewed before being deployed to production. A single AWS CodeCommit repository with separate branches for each environment allows for organized and efficient code management. Each CodePipeline retrieves the source code from the appropriate branch in the repository. The deployment step utilizes AWS CloudFormation to deploy the Lambda functions, ensuring that the infrastructure as code is maintained and version-controlled.
References:
* AWS Lambda with Amazon API Gateway: Using AWS Lambda with Amazon API Gateway
* Tutorial on using Lambda with API Gateway: Tutorial: Using Lambda with API Gateway
* AWS CodePipeline automatic deployment: Set Up a Continuous Deployment Pipeline Using AWS CodePipeline
* Building a pipeline for test and production stacks: Walkthrough: Building a pipeline for test and production stacks
NEW QUESTION # 254
A company has a single developer writing code for an automated deployment pipeline. The developer is storing source code in an Amazon S3 bucket for each project. The company wants to add more developers to the team but is concerned about code conflicts and lost work The company also wants to build a test environment to deploy newer versions of code for testing and allow developers to automatically deploy to both environments when code is changed in the repository.
What is the MOST efficient way to meet these requirements?
Answer: C
Explanation:
Explanation
Creating an AWS CodeCommit repository for each project, using the main branch for production code, and creating a testing branch for code deployed to testing will meet the requirements. AWS CodeCommit is a managed revision control service that hosts Git repositories and works with all Git-based tools1. By using feature branches to develop new features and pull requests to merge code to testing and main branches, the developers can avoid code conflicts and lost work, and also implement code reviews and approvals. Option B is incorrect because creating another S3 bucket for each project for testing code and using an AWS Lambda function to promote code changes between testing and production buckets will not provide the benefits of revision control, such as tracking changes, branching, merging, and collaborating. Option C is incorrect because using the main branch for production and test code with different deployment pipelines for each environment will not allow the developers to test their code changes before deploying them to production.
Option D is incorrect because enabling versioning and branching on each S3 bucket will not work with Git-based tools and will not provide the same level of revision control as AWS CodeCommit. References:
* AWS CodeCommit
* Certified DevOps Engineer - Professional (DOP-C02) Study Guide (page 182)
NEW QUESTION # 255
A company hosts applications in its AWS account Each application logs to an individual Amazon CloudWatch log group. The company's CloudWatch costs for ingestion are increasing A DevOps engineer needs to Identify which applications are the source of the increased logging costs.
Which solution Will meet these requirements?
Answer: B
Explanation:
Explanation
The correct answer is C.
A comprehensive and detailed explanation is:
Option A is incorrect because using CloudWatch metrics to create a custom expression that identifies the CloudWatch log groups that have the most data being written to them is not a valid solution.
CloudWatch metrics do not provide information about the size or volume of data being ingested by CloudWatch logs. CloudWatch metrics only provide information about the number of events, bytes, and errors that occur within a log group or stream. Moreover, creating a custom expression with CloudWatch metrics would require using the search_web tool, which is not necessary for this use case.
Option B is incorrect because using CloudWatch Logs Insights to create a set of queries for the application log groups to identify the number of logs written for a period of time is not a valid solution.
CloudWatch Logs Insights can help analyze and filter log events based on patterns and expressions, but it does not provide information about the cost or billing of CloudWatch logs. CloudWatch Logs Insights also charges based on the amount of data scanned by each query, which could increase the logging costs further.
Option C is correct because using AWS Cost Explorer to generate a cost report that details the cost for CloudWatch usage is a valid solution. AWS Cost Explorer is a tool that helps visualize, understand, and manage AWS costs and usage over time. AWS Cost Explorer can generate custom reports that show the breakdown of costs by service, region, account, tag, or any other dimension. AWS Cost Explorer can also filter and group costs by usage type, which can help identify the specific CloudWatch log groups that are the source of the increased logging costs.
Option D is incorrect because using AWS CloudTrail to filter for CreateLogStream events for each application is not a valid solution. AWS CloudTrail is a service that records API calls and account activity for AWS services, including CloudWatch logs. However, AWS CloudTrail does not provide information about the cost or billing of CloudWatch logs. Filtering for CreateLogStream events would only show when a new log stream was created within a log group, but not how much data was ingested or stored by that log stream.
References:
CloudWatch Metrics
CloudWatch Logs Insights
AWS Cost Explorer
AWS CloudTrail
NEW QUESTION # 256
......
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