You need to replicate API calls across two systems in real time. What tool should you use as a buffer and transport mechanism for API call events?

• A.AWS SQS
• B.AWS Lambda
• C.AWS Kinesis
• D.AWS SNS

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You have written a server-side Node.Js application and a web application with an HTML/JavaScript front end that uses the Angular.js framework.
The server-side application connects to an Amazon Redshift cluster, issues queries, and then returns the results to the front end for display.
Your user base is very large and distributed, but it is important to keep the cost of running this application low.
Which deployment strategy is both technically valid and the most cost-effective?

• A.Upload the HTML, CSS, images, and JavaScript for the front end, plus the Node.js code for the server-side application, to an Amazon S3 bucket.
  Create a CloudFront distribution with this bucket as its origin.
  Launch an Amazon Redshift cluster, and point your application to its JDBC endpoint.
• B.Upload the HTML, CSS, images, and JavaScript for the front end to an Amazon S3 bucket.
  Use AWS Elastic Beanstalk to deploy the Node.js application.
  Launch an Amazon Redshift cluster, and point your application to its JDBC endpoint.
• C.Deploy an AWS Elastic Beanstalk application with two environments: one for the Node.js application and another for the web front end.
  Launch an Amazon Redshift cluster, and point your application to its Java Database Connectivity (JDBC) endpoint.
• D.Upload the HTML, CSS, images, and JavaScript for the front end to an Amazon Simple Storage Service (S3) bucket.
  Create an Amazon CloudFront distribution with this bucket as its origin. Use AWS Elastic Beanstalk to deploy the Node.js application.
  Launch an Amazon Redshift cluster, and point your application to its JDBC endpoint.
• E.Deploy an AWS OpsWorks stack with three layers: a static web server layer for your front end, a Node.js app server layer for your server-side application, and a Redshift DB layer for your Amazon Redshift duster.

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You need your CI to build AMIs with code pre-installed on the images on every new code push.
You need to do this as cheaply as possible. How do you do this?

• A.Bid on spot instances just above the asking price as soon as new commits come in, perform all instance configuration and setup, then create an AMI based on the spot instance.
• B.Have the CI launch a new on-demand EC2 instance when new commits come in, perform all instance configuration and setup, then create an AMI based on the on-demand instance.
• C.Purchase a Light Utilization Reserved Instance to save money on the continuous integration machine.
  Use these credits whenever your create AMIs on instances.
• D.When the CI instance receives commits, attach a new EBS volume to the CI machine. Perform all setup on this EBS volume so you don't need a new EC2 instance to create the AMI.

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A DevOps Engineer must track the health of a stateless RESTful service sitting behind a Classic Load Balancer. The deployment of new application revisions is through a Cl/CD pipeline. If the service's latency increases beyond a defined threshold, deployment should be stopped until the service has recovered. Which of the following methods allow for the QUICKEST detection time?

• A.Use Amazon CloudWatch metrics provided by Elastic Load Balancing to calculate average latency.
  Alarm and stop deployment when latency increases beyond the defined threshold.
• B.Use Metric Filters to parse application logs in Amazon CloudWatch Logs. Create a filter for latency.
  Alarm and stop deployment when latency increases beyond the defined threshold.
• C.Use AWS CodeDeploy's MinimumHealthyHosts setting to define thresholds for rolling back deployments. If these thresholds are breached, roll back the deployment.
• D.Use AWS Lambda and Elastic Load Balancing access logs to detect average latency. Alarm and stop deployment when latency increases beyond the defined threshold.

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You are building a Docker image with the following Dockerfile. How many layers will the resulting image have?
FROM scratch
CMD /app/hello.sh

• A.2
• B.4
• C.1
• D.3

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