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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: SDLC Automation | 22% | - CI/CD pipeline design and implementation
|
| Topic 2: Configuration Management and Infrastructure as Code | 17% | - Infrastructure provisioning and automation
|
| Topic 3: Monitoring and Logging | 15% | - Observability and metrics
|
| Topic 4: Security and Compliance Automation | 13% | - Security automation in CI/CD and infrastructure
|
| Topic 5: Resilient Cloud Solutions | 15% | - High availability and fault tolerance design
|
| Topic 6: Incident and Event Management | 18% | - Operational response and recovery
|
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NEW QUESTION # 317
A company has deployed an application in a production VPC in a single AWS account. The application is popular and is experiencing heavy usage. The company's security team wants to add additional security, such as AWS WAF, to the application deployment. However, the application's product manager is concerned about cost and does not want to approve the change unless the security team can prove that additional security is necessary.
The security team believes that some of the application's demand might come from users that have IP addresses that are on a deny list. The security team provides the deny list to a DevOps engineer. If any of the IP addresses on the deny list access the application, the security team wants to receive automated notification in near real time so that the security team can document that the application needs additional security. The DevOps engineer creates a VPC flow log for the production VPC.
Which set of additional steps should the DevOps engineer take to meet these requirements MOST cost- effectively?
Answer: B
NEW QUESTION # 318
A company has an application that runs on AWS Lambda and sends logs to Amazon CloudWatch Logs. An Amazon Kinesis data stream is subscribed to the log groups in CloudWatch Logs. A single consumer Lambda function processes the logs from the data stream and stores the logs in an Amazon S3 bucket.
The company's DevOps team has noticed high latency during the processing and ingestion of some logs.
Which combination of steps will reduce the latency? (Select THREE.)
Answer: A,B,D
Explanation:
The latency in processing and ingesting logs can be caused by several factors, such as the throughput of the Kinesis data stream, the concurrency of the Lambda function, and the configuration of the event source mapping. To reduce the latency, the following steps can be taken:
Create a data stream consumer with enhanced fan-out. Set the Lambda function that processes the logs as the consumer. This will allow the Lambda function to receive records from the data stream with dedicated throughput of up to 2 MB per second per shard, independent of other consumers1. This will reduce the contention and delay in accessing the data stream.
Increase the ParallelizationFactor setting in the Lambda event source mapping. This will allow the Lambda service to invoke more instances of the function concurrently to process the records from the data stream2. This will increase the processing capacity and reduce the backlog of records in the data stream.
Configure reserved concurrency for the Lambda function that processes the logs. This will ensure that the function has enough concurrency available to handle the increased load from the data stream3. This will prevent the function from being throttled by the account-level concurrency limit.
The other options are not effective or may have negative impacts on the latency. Option D is not suitable because increasing the batch size in the Kinesis data stream will increase the amount of data that the Lambda function has to process in each invocation, which may increase the execution time and latency4. Option E is not advisable because turning off the ReportBatchItemFailures setting in the Lambda event source mapping will prevent the Lambda service from retrying the failed records, which may result in data loss. Option F is not necessary because increasing the number of shards in the Kinesis data stream will increase the throughput of the data stream, but it will not affect the processing speed of the Lambda function, which is the bottleneck in this scenario.
Reference:
1: Using AWS Lambda with Amazon Kinesis Data Streams - AWS Lambda
2: AWS Lambda event source mappings - AWS Lambda
3: Managing concurrency for a Lambda function - AWS Lambda
4: AWS Lambda function scaling - AWS Lambda
5: AWS Lambda event source mappings - AWS Lambda
6: Scaling Amazon Kinesis Data Streams with AWS CloudFormation - Amazon Kinesis Data Streams
NEW QUESTION # 319
A company frequently creates Docker images of an application. The company stores the images in Amazon Elastic Container Registry (Amazon ECR) . The company creates both tagged images and untagged images.
The company wants to implement a solution to automatically delete images that have not been updated for a long time and are not frequently used. The solution must retain at least a specified number of images.
Which solution will meet these requirements with the LEAST operational overhead ?
Answer: D
Explanation:
Option B is the correct choice and has the least operational overhead because ECR lifecycle policies are the native, managed feature built specifically to automate image cleanup:
* ECR lifecycle policies can expire images based on image age (e.g., images older than X days) and can also enforce retaining a minimum number of images (count-based retention), which directly matches the requirement "retain at least a specified number of images."
* Lifecycle policies work for both tagged and untagged images using rule selection and tagging status filters, so the repository stays clean without custom automation.
Why the other options are not appropriate / higher overhead:
* A is invalid: ECR is not S3; S3 lifecycle policies do not manage ECR images .
* C and D introduce custom automation (Lambda or SSM scripting), scheduling, permissions, error handling, retries, logging, and ongoing maintenance-higher overhead than a managed lifecycle policy.
NEW QUESTION # 320
A company uses an AWS CodeCommit repository to store its source code and corresponding unit tests. The company has configured an AWS CodePipeline pipeline that includes an AWS CodeBuild project that runs when code is merged to the main branch of the repository.
The company wants the CodeBuild project to run the unit tests. If the unit tests pass, the CodeBuild project must tag the most recent commit.
How should the company configure the CodeBuild project to meet these requirements?
Answer: D
Explanation:
Step 1: Using Native Git in CodeBuildTo meet the requirement of running unit tests and tagging the most recent commit if the tests pass, the CodeBuild project should be configured to use native Git to clone the CodeCommit repository. Native Git support allows full functionality for managing the repository, including the ability to create and push tags.
Action: Configure the CodeBuild project to use native Git to clone the repository and run the tests.
Why: Using native Git provides flexibility for managing tags and other repository operations after the tests are successfully executed.
Step 2: Tagging the Most Recent CommitOnce the unit tests pass, the CodeBuild project can use native Git to create a tag for the most recent commit and push that tag to the repository. This ensures that the tagged commit is linked to the test results.
Action: Configure the project to use native Git to create and push a tag to the repository if the tests pass.
Why: This ensures the correct commit is tagged automatically, streamlining the workflow.
Reference: AWS documentation on AWS CodeBuild and Git integration.
This corresponds to Option A: Configure the CodeBuild project to use native Git to clone the CodeCommit repository. Configure the project to run the unit tests. Configure the project to use native Git to create a tag and to push the Git tag to the repository if the code passes the unit tests.
NEW QUESTION # 321
A DevOps team deploys an ECS app behind an ALB using CodeDeploy with all-at-once strategy. Recent deployment increased response times, requiring rollback. The team wants a deployment strategy to monitor new versions before full traffic shift and rollback quickly if issues occur.
Which steps meet these requirements? (Select TWO.)
Answer: A,E
Explanation:
* Canary deploymentsgradually shift traffic (10% at first), enabling monitoring before full rollout.
* MonitoringTargetResponseTimealigns with detecting increased latency, a key issue reported.
* Alarms tied to the deployment group trigger automatic rollback on threshold breach.
* UnHealthyHostCount and TargetConnectionErrorCount are less specific to response time issues.
* Linear deployment is valid but canary is preferred for quick detection.
References:
CodeDeploy Deployment Configurations
Automatic Rollback with CloudWatch Alarms
NEW QUESTION # 322
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