Amazon DOP-C01 Online Practice Questions and Exam Preparation

Amazon DOP-C01 Online Questions & Answers

• Question 411:

  Your system uses a multi-master, multi-region DynamoDB configuration spanning two regions to achieve high availablity. For the first time since launching your system, one of the AWS Regions in which you operate over went down for 3 hours, and the failover worked correctly. However, after recovery, your users are experiencing strange bugs, in which users on different sides of the globe see different data. What is a likely design issue that was not accounted for when launching?

  A. The system does not have Lambda Functor Repair Automatons, to perform table scans and chack for corrupted partition blocks inside the Table in the recovered Region.
  B. The system did not implement DynamoDB Table Defragmentation for restoring partition performance in the Region that experienced an outage, so data is served stale.
  C. The system did not include repair logic and request replay buffering logic for post-failure, to resynchronize data to the Region that was unavailable for a number of hours.
  D. The system did not use DynamoDB Consistent Read requests, so the requests in different areas are not utilizing consensus across Regions at runtime.
  C. The system did not include repair logic and request replay buffering logic for post-failure, to resynchronize data to the Region that was unavailable for a number of hours.

  ---

  When using multi-region DynamoDB systems, it is of paramount importance to make sure that all requests made to one Region are replicated to the other. Under normal operation, the system in question would correctly perform write replays into the other Region. If a whole Region went down, the system would be unable to perform these writes for the period of downtime. Without buffering write requests somehow, there would be no way for the system to replay dropped crossregion writes, and the requests would be serviced differently depending on the Region from which they were served after recovery.

  Reference: http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/ Streams.CrossRegionRepl.html

• Question 412:

  When specifying more than one conditional requirements for a task, what is the proper method?

  A. - when: foo == "hello" and bar == "world"
  B. - when: foo == "hello" - when: bar == "world"
  C. - when: foo == "hello" andand bar == "world"
  D. - when: foo is "hello" and bar is "world"
  A. - when: foo == "hello" and bar == "world"

  ---

  Ansible will allow you to stack conditionals using `and' and `or'. It requires it to be in the same `when' statement, comparisons must be `==' for equals or `!=' for not equals and the `and/or' must be written as such, not `andand/||'.

  Reference: http://docs.ansible.com/ansible/playbooks_conditionals.html#the-when-statement

• Question 413:

  You meet once per month with your operations team to review the past month's data. During the meeting, you realize that 3 weeks ago, your monitoring system which pings over HTTP from outside AWS recorded a large spike in latency on your 3-tier web service API. You use DynamoDB for the database layer, ELB, EBS, and EC2 for the business logic tier, and SQS, ELB, and EC2 for the presentation layer. Which of the following techniques will NOT help you figure out what happened?

  A. Check your CloudTrail log history around the spike's time for any API calls that caused slowness.
  B. Review CloudWatch Metrics graphs to determine which component(s) slowed the system down.
  C. Review your ELB access logs in S3 to see if any ELBs in your system saw the latency.
  D. Analyze your logs to detect bursts in traffic at that time.
  B. Review CloudWatch Metrics graphs to determine which component(s) slowed the system down.

  ---

  Metrics data are available for 2 weeks. If you want to store metrics data beyond that duration, you can retrieve it using our GetMetricStatistics API as well as a number of applications and tools offered by AWS partners.

  Reference: https://aws.amazon.com/cloudwatch/faqs/

• Question 414:

  Which of these is not an instrinsic function in AWS CloudFormation?

  A. Fn::Equals
  B. Fn::If
  C. Fn::Not
  D. Fn::Parse
  D. Fn::Parse

  ---

  This is the complete list of Intrinsic Functions...: Fn::Base64, Fn::And, Fn::Equals, Fn::If, Fn::Not, Fn::Or, Fn::FindInMap, Fn::GetAtt, Fn::GetAZs, Fn::Join, Fn::Select, Ref Reference: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/intrinsic-function-reference.html

• Question 415:

  In which Docker Swarm model does the swarm manager distribute a specific number of replica tasks among the nodes based upon the scale you set in the desired state?

  A. distributed services
  B. scaled services
  C. replicated services
  D. global services
  C. replicated services

  ---

  A service is the definition of the tasks to execute on the worker nodes. It is the central structure of the swarm system and the primary root of user interaction with the swarm. When you create a service, you specify which container image to use and which commands to execute inside running containers. In the replicated services model, the swarm manager distributes a specific number of replica tasks among the nodes based upon the scale you set in the desired state. For global services, the swarm runs one task for the service on every available node in the cluster. A task carries a Docker container and the commands to run inside the container. It is the atomic scheduling unit of swarm. Manager nodes assign tasks to worker nodes according to the number of replicas set in the service scale. Once a task is assigned to a node, it cannot move to another node. It can only run on the assigned node or fail.

  Reference: https://docs.docker.com/engine/swarm/key-concepts/#services-and-tasks

• Question 416:

  Which EBS volume type is best for high performance NoSQL cluster deployments?

  A. io1
  B. gp1
  C. standard
  D. gp2
  A. io1

  ---

  io1 volumes, or Provisioned IOPS (PIOPS) SSDs, are best for: Critical business applications that require sustained IOPS performance, or more than 10,000 IOPS or 160 MiB/s of throughput per volume, like large database workloads, such as MongoDB. Reference: http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSVolumeTypes.html

• Question 417:

  You are responsible for a popular file sharing application that uses Elastic Load Balancing to distribute traffic to an Amazon EC2 application tier deployed in an Auto Scaling group that runs across multiple Availability Zones. You currently record the number of user file transfers to a log file on the application server, and then write data points from the logs to an Amazon RDS MySQL instance. You are not happy with how your application scales, and want to implement a new scaling policy based on the average number of user file transfers in a 10-minute period instead of average CPU utilization in the last five minutes. What steps should you take to ensure that your application tier scales based on this new policy? (Choose two.)

  A. Create a new CloudWatch alarm based on the Elastic Load Balancing "RequestCount" metric that triggers an Auto Scaling action to scale the application tier.
  B. Create a new CloudWatch alarm based on a custom metric streaming from the Amazon RDS MySQL instance that triggers an Auto Scaling action to scale the application tier.
  C. Create a new CloudWatch alarm based on a custom metric published from file transfer logs streaming to CloudWatch that triggers an Auto Scaling action to scale the application tier.
  D. Create a new Auto Scaling launch configuration that includes an Amazon EC2 user data script that installs a CloudWatch Logs Agent on newly launched instances in the application tier. The agent will be configured to stream the file transfers log tile to CloudWatch.
  E. Create a new Auto Scaling launch configuration for the application tier that scales based on an Auto Scaling policy that reads the file transfer log data from the Amazon RIDS MySQL instance.
  F. Create a new Auto Scaling launch configuration that includes an Amazon EC2 user data script that installs an Amazon RDS Logs Agent on newly launched instances in the application tier. The agent will be configured to stream the file transfer data points to the Auto Scaling group.
  C. Create a new CloudWatch alarm based on a custom metric published from file transfer logs streaming to CloudWatch that triggers an Auto Scaling action to scale the application tier.
  D. Create a new Auto Scaling launch configuration that includes an Amazon EC2 user data script that installs a CloudWatch Logs Agent on newly launched instances in the application tier. The agent will be configured to stream the file transfers log tile to CloudWatch.

• Question 418:

  A DevOps Engineer is architecting a continuous development strategy for a company's software as a service (SaaS) web application running on AWS. For application and security reasons, users subscribing to this application are distributed across multiple Application Load Balancers (ALBs), each of which has a dedicated Auto Scaling group and fleet of Amazon EC2 instances. The application does not require a build stage, and when it is committed to AWS CodeCommit, the application must trigger a simultaneous deployment to all ALBs, Auto Scaling groups, and EC2 fleets.

  Which architecture will meet these requirements with the LEAST amount of configuration?

  A. Create a single AWS CodePipeline pipeline that deploys the application in parallel using unique AWS CodeDeploy applications and deployment groups created for each ALB-Auto Scaling group pair.
  B. Create a single AWS CodePipeline pipeline that deploys the application using a single AWS CodeDeploy application and single deployment group.
  C. Create a single AWS CodePipeline pipeline that deploys the application in parallel using a single AWS CodeDeploy application and unique deployment group for each ALB-Auto Scaling group pair.
  D. Create an AWS CodePipeline pipeline for each ALB-Auto Scaling group pair that deploys the application using an AWS CodeDeploy application and deployment group created for the same ALB- Auto Scaling group pair.
  C. Create a single AWS CodePipeline pipeline that deploys the application in parallel using a single AWS CodeDeploy application and unique deployment group for each ALB-Auto Scaling group pair.

• Question 419:

  A company is using AWS CodeCommit as its source code repository. After an internal audit, the compliance team mandates that any code change that go into the master branch must be committed by senior developers.

  Which solution will meet these requirements?

  A. Create two repositories in CodeCommit: one for working and another for the master. Create separate IAM groups for senior developers and developers. Assign the resource-level permissions on the repositories tied to the IAM groups. After the code changes are reviewed, sync the approved files to the master code commit repository.
  B. Create a repository in CodeCommit. Create separate IAM groups for senior developers and developers. Assign code commit permissions for both groups, with code merge permissions for the senior developers group. Create a trigger to notify senior developers with a URL link to approve or deny commit requests delivered through Amazon SNS. Once a senior developer approves the code, the code gets merged to the master branch.
  C. Create a repository in CodeCommit with a working and master branch. Create separate IAM groups for senior developers and developers. Use an IAM policy to assign each IAM group their corresponding branches. Once the code is merged to the working branch, senior developers can pull the changes from the working branch to the master branch.
  D. Create a repository in CodeCommit. Create separate IAM groups for senior developers and developers. Use AWS Lambda triggers on the master branch and get the user name of the developer at the event object of the Lambda function. Validate the user name with the IAM group to approve or deny the commit.
  A. Create two repositories in CodeCommit: one for working and another for the master. Create separate IAM groups for senior developers and developers. Assign the resource-level permissions on the repositories tied to the IAM groups. After the code changes are reviewed, sync the approved files to the master code commit repository.

• Question 420:

  A company wants to automatically re-create its infrastructure using AWS CloudFormation as part of the company's quality assurance (QA) pipeline. For each QA run, a new VPC must be created in a single account, resources must be deployed into the VPC, and tests must be run against this new infrastructure. The company policy states that all VPCs must be peered with a central management VPC to allow centralized logging. The company has existing CloudFormation templates to deploy its VPC and associated resources.

  Which combination of steps will achieve the goal in a way that is automated and repeatable? (Choose two.)

  A. Create an AWS Lambda function that is invoked by an Amazon CloudWatch Events rule when a CreateVpcPeeringConnection API call is made. The Lambda function should check the source of the peering request, accepts the request, and update the route tables for the management VPC to allow traffic to go over the peering connection.
  B. In the CloudFormation template: 1. Invoke a custom resource to generate unique VPC CIDR ranges for the VPC and subnets. 2. Create a peering connection to the management VPC. 3. Update route tables to allow traffic to the management VPC.
  C. In the CloudFormation template: 1. Use the Fn::Cidr function to allocate an unused CIDR range for the VPC and subnets. 2. Create a peering connection to the management VPC. 3. Update route tables to allow traffic to the management VPC.
  D. Modify the CloudFormation template to include a mappings object that includes a list of /16 CIDR ranges for each account where the stack will be deployed.
  E. Use CloudFormation StackSets to deploy the VPC and associated resources to multiple AWS accounts using a custom resource to allocate unique CIDR ranges. Create peering connections from each VPC to the central management VPC and accept those connections in the management VPC.
  A. Create an AWS Lambda function that is invoked by an Amazon CloudWatch Events rule when a CreateVpcPeeringConnection API call is made. The Lambda function should check the source of the peering request, accepts the request, and update the route tables for the management VPC to allow traffic to go over the peering connection.
  B. In the CloudFormation template: 1. Invoke a custom resource to generate unique VPC CIDR ranges for the VPC and subnets. 2. Create a peering connection to the management VPC. 3. Update route tables to allow traffic to the management VPC.