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NEW QUESTION 22
Your serverless architecture using AWS API Gateway, AWS Lambda, and AWS DynamoDB experienced a large increase in traffic to a sustained 400 requests per second, and dramatically increased in failure rates. Your requests, during normal operation, last 500 milliseconds on average. Your DynamoDB table did not exceed 50% of provisioned throughput, and Table primary keys are designed correctly. What is the most likely issue?
- A. You did not request a limit increase on concurrent Lambda function executions.
- B. You used Consistent Read requests on DynamoDB and are experiencing semaphore lock.
- C. Your AWS API Gateway Deployment is bottlenecking on request (de)serialization.
- D. Your API Gateway deployment is throttling your requests.
Answer: A
Explanation:
AWS API Gateway by default throttles at 500 requests per second steady-state, and 1000 requests per second at spike. Lambda, by default, throttles at 100 concurrent requests for safety.
At 500 milliseconds (half of a second) per request, you can expect to support 200 requests per second at 100 concurrency. This is less than the 400 requests per second your system now requires. Make a limit increase request via the AWS Support Console.
AWS Lambda: Concurrent requests safety throttle per account -> 100
http://docs.aws.amazon.com/general/latest/gr/aws_service_limits.html#limits_lambda
NEW QUESTION 23
You recently encountered a major bug in your Windows-based web application during a deployment cycle.
During this failed deployment, it took the team four hours to roll back to a previously working state, which left customers with a poor user experience.
During the post-mortem, your team discussed the need to provide a quicker way to roll back failed deployments.
You currently run your web application on Amazon EC2 using Windows 2012R2 and use Elastic Load Balancing for your load balancing needs.
Which technique should you use to solve this problem?
- A. Create deployable versioned bundles of your application. Store the bundles on Amazon S3.
Re-deploy your web application on Elastic Beanstalk, and enable the Elastic Beanstalk auto- rollback feature tied to CloudWatch metrics that define failure. - B. Re-deploy your web application using an AWS OpsWorks stack, and use the AWS OpsWorks auto-rollback feature to initiate a rollback during failures.
- C. Re-deploy your web application using Elastic Beanstalk, and use the Elastic Beanstalk application versions when deploying.
During failures, re-deploy the previous version to the Elastic Beanstalk environment. - D. Re-deploy your web application using Elastic Beanstalk, and use the Elastic Beanstalk API to trigger a FailedDeployment API call to initiate a rollback to the previous version.
- E. Create deployable versioned bundles of your application.
Store the bundle on Amazon S3. Re-deploy your web application using an AWS OpsWorks stack, and use AWS OpsWorks application versioning to initiate a rollback during failures.
Answer: C
NEW QUESTION 24
Amazon Inspector agent collects telemetry data during assessment run and sends this data to Amazon Inspector dedicated S3 bucket for analysis. How can you access telemetry data out of Amazon Inspector and how can you benefit from this data in securing your resources?
- A. Telemetry data is deleted immediately after assessment run, therefore data can NOT be accessed or analyzed by any other tools.
- B. Telemetry data is stored in Amazon Inspector dedicated S3 bucket that does NOT belong to your account, Amazon Inspector currently does NOT provide an API or an S3 bucket access mechanism to collected telemetry. Data is retained temporarily only to allow for assistance with support requests.
- C. Telemetry data is saved on S3 bucket in your account, therefore telemetry data is accessible with proper permissions on that bucket.
- D. Telemetry data is kept in S3 and encrypted with a pre-assessment test key configured in KMS, as long as you have access to that key you can download and decrypt telemetry data.
Answer: B
Explanation:
The telemetry data stored in S3 is retained only to allow for assistance with support requests and is not used or aggregated by Amazon for any other purpose. After 30 days, telemetry data is permanently deleted per a standard Amazon Inspector-dedicated S3 bucket lifecycle policy. At present, Amazon Inspector does not provide an API or an S3 bucket access mechanism to collected telemetry.
Reference: https://docs.aws.amazon.com/inspector/latest/userguide/inspector_agents.html
NEW QUESTION 25
An online company uses Amazon EC2 Auto Scaling extensively to provide an excellent customer experience while minimizing the number of running EC2 instances. The company’s self-hosted Puppet environment in the application layer manages the configuration of the instances. The IT manager wants the lowest licensing costs and wants to ensure that whenever the EC2 Auto Scaling group scales down, removed EC2 instances are deregistered from the Puppet master as soon as possible.
How can the requirement be met?
- A. Bake the AWS Systems Manager agent into the base AMI. When the Auto Scaling group scales out, use the AWS Systems Manager to install the Puppet agent, and run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the Systems Manager instance stop lifecycle hook to run a script to de-register the instance from the Puppet master.
- B. At instance launch time, use EC2 user data to deploy the AWS CodeDeploy agent. Use CodeDeploy to install the Puppet agent. When the Auto Scaling group scales out, run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the EC2 Auto Scaling EC2_INSTANCE_TERMINATING lifecycle hook to trigger de-registration from the Puppet master.
- C. At instance launch time, use EC2 user data to deploy the AWS CodeDeploy agent. When the Auto Scaling group scales out, use CodeDeploy to install the Puppet agent, and run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the EC2 user data instance stop script to run a script to de-register the instance from the Puppet master.
- D. Bake the AWS CodeDeploy agent into the base AMI. When the Auto Scaling group scales out, use CodeDeploy to install the Puppet agent, and execute a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the CodeDeploy ApplicationStop lifecycle hook to run a script to de-register the instance from the Puppet master.
Answer: C
NEW QUESTION 26
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