A DevOps engineer is building a continuous deployment pipeline for a serverless application that uses AWS Lambda functions. The company wants to reduce the customer impact of an unsuccessful deployment. The company also wants to monitor for issues.
Which deploy stage configuration will meet these requirements?

1. A. Use an AWS Serverless Application Model (AWS SAM) template to define the serverless applicatio
2. B. Use AWS CodeDeploy to deploy the Lambda functions with the Canary10Percent15Minutes Deployment Preference Typ
3. C. Use Amazon CloudWatch alarms to monitor the health of the functions.
4. D. Use AWS CloudFormation to publish a new stack update, and include Amazon CloudWatch alarms on all resource
5. E. Set up an AWS CodePipeline approval action for a developer to verify and approve the AWS CloudFormation change set.
6. F. Use AWS CloudFormation to publish a new version on every stack update, and include Amazon CloudWatch alarms on all resource
7. G. Use the RoutingConfig property of the AWS::Lambda::Alias resource to update the traffic routing during the stack update.
8. H. Use AWS CodeBuild to add sample event payloads for testing to the Lambda function
9. I. Publish a new version of the functions, and include Amazon CloudWatch alarm
10. J. Update the production alias to point to the new versio
11. K. Configure rollbacks to occur when an alarm is in the ALARM state.

Correct Answer: D
Use routing configuration on an alias to send a portion of traffic to a second function version. For example, you can reduce the risk of deploying a new version by configuring the alias to send most of the traffic to the existing version, and only a small percentage of traffic to the new version. https://docs.aws.amazon.com/lambda/latest/dg/configuration-aliases.html
The following are the steps involved in the deploy stage configuration that will meet the requirements:
✑ Use AWS CodeBuild to add sample event payloads for testing to the Lambda
functions.
✑ Publish a new version of the functions, and include Amazon CloudWatch alarms.
✑ Update the production alias to point to the new version.
✑ Configure rollbacks to occur when an alarm is in the ALARM state.
This configuration will help to reduce the customer impact of an unsuccessful deployment
by deploying the new version of the functions to a staging environment first. This will allow the DevOps engineer to test the new version of the functions before deploying it to production.
The configuration will also help to monitor for issues by including Amazon CloudWatch alarms. These alarms will alert the DevOps engineer if there are any problems with the new version of the functions.

A space exploration company receives telemetry data from multiple satellites. Small packets of data are received through Amazon API Gateway and are placed directly into an Amazon Simple Queue Service (Amazon SQS) standard queue. A custom application is subscribed to the queue and transforms the data into a standard format.
Because of inconsistencies in the data that the satellites produce, the application is occasionally unable to transform the data. In these cases, the messages remain in the SQS queue. A DevOps engineer must develop a solution that retains the failed messages and makes them available to scientists for review and future processing.
Which solution will meet these requirements?

1. A. Configure AWS Lambda to poll the SQS queue and invoke a Lambda function to check whether the queue messages are vali
2. B. If validation fails, send a copy of the data that is not valid to an Amazon S3 bucket so that the scientists can review and correct the dat
3. C. When the data is corrected, amend the message in the SQS queue by using a replay Lambda function with the corrected data.
4. D. Convert the SQS standard queue to an SQS FIFO queu
5. E. Configure AWS Lambda to poll the SQS queue every 10 minutes by using an Amazon EventBridge schedul
6. F. Invoke the Lambda function to identify any messages with a SentTimestamp value that is older than 5 minutes, push the data to the same location as the application's output location, and remove the messages from the queue.
7. G. Create an SQS dead-letter queu
8. H. Modify the existing queue by including a redrive policy that sets the Maximum Receives setting to 1 and sets the dead-letter queue ARN to the ARN of the newly created queu
9. I. Instruct the scientists to use the dead-letter queue to review the data that is not vali
10. J. Reprocess this data at a later time.
11. K. Configure API Gateway to send messages to different SQS virtual queues that are named for each of the satellite
12. L. Update the application to use a new virtual queue for any data that it cannot transform, and send the message to the new virtual queu
13. M. Instruct the scientists to use the virtual queue to review the data that is not vali
14. N. Reprocess this data at a later time.

Correct Answer: C
Create an SQS dead-letter queue. Modify the existing queue by including a redrive policy that sets the Maximum Receives setting to 1 and sets the dead-letter queue ARN to the ARN of the newly created queue. Instruct the scientists to use the dead-letter queue to review the data that is not valid. Reprocess this data at a later time.

A company is hosting a static website from an Amazon S3 bucket. The website is available to customers at example.com. The company uses an Amazon Route 53 weighted routing policy with a TTL of 1 day. The company has decided to replace the existing static website with a dynamic web application. The dynamic web application uses an Application Load Balancer (ALB) in front of a fleet of Amazon EC2 instances.
On the day of production launch to customers, the company creates an additional Route 53 weighted DNS record entry that points to the ALB with a weight of 255 and a TTL of 1 hour. Two days later, a DevOps engineer notices that the previous static website is displayed sometimes when customers navigate to example.com.
How can the DevOps engineer ensure that the company serves only dynamic content for example.com?

1. A. Delete all objects, including previous versions, from the S3 bucket that contains the static website content.
2. B. Update the weighted DNS record entry that points to the S3 bucke
3. C. Apply a weight of 0. Specify the domain reset option to propagate changes immediately.
4. D. Configure webpage redirect requests on the S3 bucket with a hostname that redirects to the ALB.
5. E. Remove the weighted DNS record entry that points to the S3 bucket from the example.com hosted zon
6. F. Wait for DNS propagation to become complete.

Correct Answer: D

A DevOps team uses AWS CodePipeline, AWS CodeBuild, and AWS CodeDeploy to deploy an application. The application is a REST API that uses AWS Lambda functions and Amazon API Gateway Recent deployments have introduced errors that have affected many customers.
The DevOps team needs a solution that reverts to the most recent stable version of the application when an error is detected. The solution must affect the fewest customers possible.
Which solution Will meet these requirements With the MOST operational efficiency?

1. A. Set the deployment configuration in CodeDepIoy to LambdaAlIAtOnce Configure automatic rollbacks on the deployment group Create an Amazon CloudWatch alarm that detects HTTP Bad Gateway errors on API Gateway Configure the deployment group to roll back when the number of alarms meets the alarm threshold
2. B. Set the deployment configuration in CodeDeploy to LambdaCanary10Percent10Minute
3. C. Configure automatic rollbacks on the deployment group Create an Amazon CloudWatch alarm that detects HTTP Bad Gateway errors on API Gateway Configure the deployment group to roll back when the number of alarms meets the alarm threshold
4. D. Set the deployment configuration in CodeDeploy to LambdaAllAtOnce Configure manual rollbacks on the deployment grou
5. E. Create an Amazon Simple Notification Service (Amazon SNS) topc to send notifications every time a deployrnent fad
6. F. Configure the SNS topc to Invoke a new Lambda function that stops the current deployment and starts the most recent successful deployment
7. G. Set the deployment configuration in CodeDeploy to LambdaCanaryIOPercentIOMinutes Configure manual rollbacks on the deployment group Create a metric filter on an Amazon CloudWatch log group for API Gateway to monitor HTTP Bad Gateway error
8. H. Configure the metric filter to Invoke a new Lambda function that stops the current eployment and starts the most recent successful deployment

Correct Answer: B
✑ Option A is incorrect because setting the deployment configuration to LambdaAllAtOnce means that the new version of the application will be deployed to all Lambda functions at once, affecting all customers. This does not meet the requirement of affecting the fewest customers possible. Moreover, configuring automatic rollbacks on the deployment group is not operationally efficient, as it requires manual intervention to fix the errors and redeploy the application.
✑ Option B is correct because setting the deployment configuration to LambdaCanary10Percent10Minutes means that the new version of the application will be deployed to 10 percent of the Lambda functions first, and then to the remaining 90 percent after 10 minutes. This minimizes the impact of errors on customers, as only 10 percent of them will be affected by a faulty deployment. Configuring automatic rollbacks on the deployment group also meets the requirement of reverting to the most recent stable version of the application when an error is detected. Creating a CloudWatch alarm that detects HTTP Bad Gateway errors on API Gateway is a valid way to monitor the health of the application and trigger a rollback if needed.
✑ Option C is incorrect because setting the deployment configuration to LambdaAllAtOnce means that the new version of the application will be deployed to all Lambda functions at once, affecting all customers. This does not meet the requirement of affecting the fewest customers possible. Moreover, configuring manual rollbacks on the deployment group is not operationally efficient, as it requires human intervention to stop the current deployment and start a new one. Creating an SNS topic to send notifications every time a deployment fails is not sufficient to detect errors in the application, as it does not monitor the API Gateway responses.
✑ Option D is incorrect because configuring manual rollbacks on the deployment
group is not operationally efficient, as it requires human intervention to stop the current deployment and start a new one. Creating a metric filter on a CloudWatch log group for API Gateway to monitor HTTP Bad Gateway errors is a valid way to monitor the health of the application, but invoking a new Lambda function to perform a rollback is unnecessary and complex, as CodeDeploy already provides automatic rollback functionality.
References:
✑ AWS CodeDeploy Deployment Configurations
✑ [AWS CodeDeploy Rollbacks]
✑ Amazon CloudWatch Alarms

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.)

1. A. Create a data stream consumer with enhanced fan-ou
2. B. Set the Lambda function that processes the logs as the consumer.
3. C. Increase the ParallelizationFactor setting in the Lambda event source mapping.
4. D. Configure reserved concurrency for the Lambda function that processes the logs.
5. E. Increase the batch size in the Kinesis data stream.
6. F. Turn off the ReportBatchltemFailures setting in the Lambda event source mapping.
7. G. Increase the number of shards in the Kinesis data stream.

Correct Answer: ABC
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.
References:
✑ 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
✑ : AWS Lambda event source mappings - AWS Lambda
✑ : Scaling Amazon Kinesis Data Streams with AWS CloudFormation - Amazon Kinesis Data Streams