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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security and Compliance Automation | 13% | - Security automation in CI/CD and infrastructure
|
| Topic 2: Monitoring and Logging | 15% | - Observability and metrics
|
| Topic 3: Configuration Management and Infrastructure as Code | 17% | - Infrastructure provisioning and automation
|
| Topic 4: Incident and Event Management | 18% | - Operational response and recovery
|
| Topic 5: SDLC Automation | 22% | - CI/CD pipeline design and implementation
|
| Topic 6: Resilient Cloud Solutions | 15% | - High availability and fault tolerance design
|
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NEW QUESTION # 233
A DevOps engineer is building an application that uses an AWS Lambda function to query an Amazon Aurora MySQL DB cluster. The Lambda function performs only read queries. Amazon EventBridge events invoke the Lambda function.
As more events invoke the Lambda function each second, the database's latency increases and the database's throughput decreases. The DevOps engineer needs to improve the performance of the application.
Which combination of steps will meet these requirements? (Select THREE.)
Answer: A,E,F
Explanation:
Explanation
Verified answer: A, C, and E.
Short Explanation: To improve the performance of the application, the DevOps engineer should use Amazon RDS Proxy, implement the database connection opening outside the Lambda event handler code, and connect to the proxy endpoint from the Lambda function.
References:
* Amazon RDS Proxy is a fully managed, highly available database proxy for Amazon Relational Database Service (RDS) that makes applications more scalable, more resilient to database failures, and more secure1. By using Amazon RDS Proxy, the DevOps engineer can reduce the overhead of opening and closing connections to the database, which can improve latency and throughput2.
* The DevOps engineer should connect the proxy to the Aurora cluster reader endpoint, which allows read-only connections to one of the Aurora Replicas in the DB cluster3. This can help balance the load across multiple read replicas and improve performance for read-intensive workloads4.
* The DevOps engineer should implement the database connection opening outside the Lambda event handler code, which means using a global variable to store the database connection object5. This can enable connection reuse across multiple invocations of the Lambda function, which can reduce latency and improve performance.
* The DevOps engineer should connect to the proxy endpoint from the Lambda function, which is a unique URL that represents the proxy. This can allow the Lambda function to access the database through the proxy, which can provide benefits such as connection pooling, load balancing, failover handling, and enhanced security.
* The other options are incorrect because:
* Implementing database connection pooling inside the Lambda code is unnecessary and redundant when using Amazon RDS Proxy, which already provides connection pooling as a service.
* Implementing the database connection opening and closing inside the Lambda event handler code is inefficient and costly, as it can increase latency and consume more resources for each invocation of the Lambda function.
* Connecting to the Aurora cluster endpoint from the Lambda function is not optimal for read-only queries, as it can direct traffic to either the primary instance or one of the Aurora Replicas in the DB cluster. This can result in inconsistent performance and potential conflicts with write operations on the primary instance.
NEW QUESTION # 234
A company uses machine learning on transactional data that a development team uploads from multiple sources to an Amazon S3 bucket. The development team finds duplicate objects in the S3 bucket across multiple prefixes. The duplications are increasing the company ' s storage costs.
The company wants to implement an automated solution to identify and remove duplicate objects from the S3 bucket.
Which solution will meet this requirement?
Answer: D
Explanation:
Amazon S3 Inventory generates scheduled reports listing all objects in a bucket with metadata including the ETag, which is an MD5 hash of the object content. Objects with the same ETag value have identical content regardless of their key or prefix location and can therefore be identified as duplicates. Amazon Athena can query the inventory report stored in S3 using SQL to group objects by ETag and identify keys where more than one object shares the same hash. Once duplicate keys are identified, S3 Batch Operations can invoke an AWS Lambda function to programmatically delete the duplicate entries, completing the automated cleanup workflow. S3 Storage Lens (Option A) provides visibility into storage usage metrics but does not identify content-level duplicates. CloudTrail (Option B) tracks API activity but cannot compare object content. AWS Config (Option D) is designed for resource configuration compliance, not S3 object deduplication.
NEW QUESTION # 235
A company has a stateless web application that is deployed on Amazon EC2 instances. The EC2 instances are in a target group behind an Application Load Balancer (ALB). Amazon Route 53 manages the application domain.
The company updates the application UI and develops a beta version of the application. The company wants to test the beta version on 10% of its traffic.
Which solution will meet these requirements with the LEAST number of configuration changes?
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of DevOps Engineer Documents Only:
ALB supports weighted target groups for traffic splitting between versions without DNS-level changes. By attaching multiple target groups (old & beta) to the same ALB listener rule with weights (90/10), partial traffic testing can occur seamlessly. This is the recommended least-change method per Application Load Balancer advanced request routing documentation.
NEW QUESTION # 236
A company is using AWS CodePipeline to deploy an application. According to a new guideline, a member of the company's security team must sign off on any application changes before the changes are deployed into production. The approval must be recorded and retained.
Which combination of actions will meet these requirements? (Select TWO.)
Answer: A,E
Explanation:
Explanation
To meet the new guideline for application deployment, the company can use a combination of AWS CodePipeline and AWS CloudTrail. A manual approval action in CodePipeline allows the security team to review and approve changes before they are deployed. This action can be configured to pause the pipeline until approval is granted, ensuring that no changes move to production without the necessary sign-off.
Additionally, by creating an AWS CloudTrail trail, all actions taken within CodePipeline, including approvals, are recorded and delivered to an Amazon S3 bucket. This provides an audit trail that can be retained for compliance and review purposes.
References:
* AWS CodePipeline's manual approval action provides a way to ensure that a member of the security team can review and approve changes before they are deployed1.
* AWS CloudTrail integration with CodePipeline allows for the recording and retention of all pipeline actions, including approvals, which can be stored in Amazon S3 for record-keeping2.
NEW QUESTION # 237
A DevOps engineer manages an AWS CodePipeline pipeline that builds and deploys a web application on AWS. The pipeline has a source stage, a build stage, and a deploy stage. When deployed properly, the web application responds with a 200 OK HTTP response code when the URL of the home page is requested.
The home page recently returned a 503 HTTP response code after CodePipeline deployed the application. The DevOps engineer needs to add an automated test into the pipeline. The automated test must ensure that the application returns a 200 OK HTTP response code after the application is deployed. The pipeline must fail if the response code is not present during the test.
The DevOps engineer has added a CheckURL stage after the deploy stage in the pipeline.
What should the DevOps engineer do next to implement the automated test?
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
To add an automated test in AWS CodePipeline that checks the HTTP response code of a deployed application, the most straightforward and operationally efficient method is to create an AWS Lambda function that makes an HTTP request to the application URL, checks the response code, and then reports success or failure back to CodePipeline.
* The Lambda function can be invoked as an action in the pipeline stage.
* If the response code is not 200 OK, the Lambda function can return a failure, causing the pipeline stage to fail and halt further execution.
* Option A's CloudWatch synthetic canary monitors are useful for ongoing monitoring but are not natively integrated as CodePipeline actions to control pipeline flow.
* Option C incorrectly uses CodeDeploy action for testing, which is not designed for this purpose.
* Option D introduces unnecessary complexity by deploying API Gateway and Device Farm, which is not required for a simple HTTP status check.Therefore, option B provides a clean, simple, and fully automated way to enforce HTTP response validation within the pipeline.
Reference from AWS Official Documentation:
* AWS CodePipeline Custom Actions:"You can create Lambda invoke actions in your pipeline stages to run custom validation or testing functions."(AWS CodePipeline User Guide - Lambda Actions)
* AWS Lambda Function for Health Checks:"Lambda functions can be used to perform health checks or API response validations and report results back to invoking services."(AWS Lambda Developer Guide)
NEW QUESTION # 238
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