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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Configuration Management and Infrastructure as Code | 22% | - Design and implement data management strategies
|
| Topic 2: High Availability and Disaster Recovery | 16% | - Design and implement high availability and scalability
|
| Topic 3: Monitoring and Logging | 12% | - Design and implement monitoring and observability strategies
|
| Topic 4: SDLC Automation | 22% | - Design and implement source code management strategies
|
| Topic 5: Incident and Event Response | 18% | - Design and implement chaos engineering practices
|
| Topic 6: Policies and Standards Automation | 10% | - Design and implement preventive and detective controls
|
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NEW QUESTION # 414
A company uses AWS CloudFormation to deploy application environments. A deployment failed due to manual modifications in stack resources. The DevOps engineer wants to detect manual modifications and alert the DevOps lead with the least effort.
Which solution meets these requirements?
Answer: C
Explanation:
AWS Config offers a managed rule called CLOUDFORMATION_STACK_DRIFT_DETECTION_CHECK to detect stack drift automatically.
* Creating an SNS topic and subscribing the DevOps lead enables simple notification without custom Lambda functions.
* An EventBridge rule that triggers on NON_COMPLIANT status (when drift is detected) can send alerts directly to SNS.Option B adds complexity by requiring custom rules and Lambda. Option C incorrectly triggers on COMPLIANT, not NON_COMPLIANT. Option D needs a Lambda for email, while SNS can send email directly.Hence, Option A offers the least operational effort.
References:
AWS Config Drift Detection
AWS Config Managed Rules
NEW QUESTION # 415
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: B,E,F
Explanation:
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.
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 # 416
A DevOps engineer needs to configure an AWS CodePipeline pipeline that publishes container images to an Amazon Elastic Container Registry (Amazon ECR) repository. The pipeline must wait for the previous run to finish and must run when new Git tags are pushed to a Git repository that is connected to AWS CodeConnections. An existing deployment pipeline needs to run in response to the publication of new container images.
Which solution will meet these requirements?
Answer: D
Explanation:
The requirements clearly indicate the need for modern CodePipeline capabilities, strict execution ordering, Git tag-based triggers, and loose coupling between pipelines. CodePipeline V2 introduces execution modes such as QUEUED and SUPERSEDED, along with native support for advanced trigger filtering when using AWS CodeConnections.
The requirement that the pipeline must wait for the previous run to finish directly maps to QUEUED mode, which ensures that pipeline executions run sequentially rather than replacing in-progress executions.
SUPERSEDED mode would cancel the running execution, which violates the requirement.
Triggering the pipeline when new Git tags are pushed is supported through CodePipeline V2 trigger filters using refs/tags/*. Branch-based triggers would not satisfy this condition.
Finally, the requirement that an existing deployment pipeline runs in response to new container images is best met using Amazon EventBridge, which natively emits events for ECR image push actions. EventBridge allows decoupled, event-driven orchestration between pipelines without tight dependencies or custom scripting. This is the AWS-recommended approach for pipeline-to-pipeline coordination.
Options C and D rely on CodePipeline V1, which lacks modern trigger filtering and execution control.
Option B incorrectly uses SUPERSEDED mode and branch-based triggers.
Therefore, Option A correctly combines CodePipeline V2, QUEUED execution mode, tag-based triggers, and EventBridge-driven pipeline chaining, meeting all requirements with best practices and minimal operational complexity.
NEW QUESTION # 417
A company hosts applications in its AWS account Each application logs to an individual Amazon CloudWatch log group. The companys 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:
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.
Reference:
CloudWatch Metrics
CloudWatch Logs Insights
AWS Cost Explorer
AWS CloudTrail
NEW QUESTION # 418
A company is developing an application that uses AWS Lambda functions. A DevOps engineer must create an AWS CloudFormation template that defines a deployment configuration for gradual traffic shifting to new Lambda function versions.
Which CloudFormation resource configuration will meet this requirement?
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
For gradual traffic shifting in Lambda deployments,AWS Lambda aliasessupport the RoutingConfig property, which specifies the percentage of traffic routed to different versions of the Lambda function. This enables weighted traffic shifting between versions as part of deployment strategies.
* The AWS::Lambda::Alias resource's RoutingConfig can specify multiple versions with weights, enabling canary or linear deployment strategies without needing CodeDeploy resources explicitly.
* AWS CodeDeploy resources like DeploymentConfig and DeploymentGroup are used primarily for blue
/green deployments and managing deployment strategies outside Lambda aliases.
* Lambda versions themselves do not have a VersionWeight property; instead, weighted routing is managed via aliases.
Reference:
AWS::Lambda::Alias - RoutingConfig:"Specifies the versions of the function and the percentage of traffic to send to each version."(AWS CloudFormation Lambda Alias) AWS Lambda Deployment Preferences:"Weighted aliases enable gradual traffic shifting between Lambda function versions."(AWS Lambda Deployment Preferences)
NEW QUESTION # 419
......
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