매달, 우리는 1000명 이상의 사람들이 시험 준비를 잘하고 시험을 잘 통과할 수 있도록 도와줍니다.
WGUCloud Deployment and Operations 온라인 연습
최종 업데이트 시간: 2025년12월09일
당신은 온라인 연습 문제를 통해 WGU Cloud Deployment and Operations 시험지식에 대해 자신이 어떻게 알고 있는지 파악한 후 시험 참가 신청 여부를 결정할 수 있다.
시험을 100% 합격하고 시험 준비 시간을 35% 절약하기를 바라며 Cloud Deployment and Operations 덤프 (최신 실제 시험 문제)를 사용 선택하여 현재 최신 67개의 시험 문제와 답을 포함하십시오.
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Comprehensive and Detailed Explanation From Exact Extract:
StackSets are used to change stacks across multiple AWS accounts and regions in a single operation, enabling centralized management of infrastructure deployments. StackSets allow administrators to create, update, or delete stacks consistently across specified accounts and regions. The WGU Cloud Deployment and Operations Study Guide (Section 5.4, StackSets) states, "StackSets provide the capability to manage and update stacks across multiple accounts and regions with a single operation, streamlining multi-region deployments." StackInstance, nested stacks, and stack policies do not support this multi-account, multi-region functionality.
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To set up self-managed permissions for CloudFormation StackSet operations, two roles are required: in the administrator account, create an IAM role named AWSCloudFormationStackSetAdministrationRole to manage StackSet operations, and in each target account, create a service role named AWSCloudFormationStackSetExecutionRole that trusts the administrator account to execute the stacks. The WGU Cloud Deployment and Operations Study Guide (Section 5.4, StackSets) states, "For self-managed permissions, the administrator account requires the AWSCloudFormationStackSetAdministrationRole, while each target account needs the AWSCloudFormationStackSetExecutionRole with a trust relationship to the administrator account for stack deployment." Roles B and D are incorrectly named or misplaced.
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The Mappings section in a CloudFormation template should be used to set values based on region-specific AMI IDs. Mappings allow the template to define a lookup table that associates regions with corresponding AMI IDs, enabling dynamic selection during stack creation across multiple regions. The WGU Cloud Deployment and Operations Study Guide (Section 5.3, CloudFormation Mappings) states, "The Mappings section enables region-specific configurations, such as mapping AMI IDs to regions (e.g., 'us-east-1': 'ami-123456'), ensuring the correct AMI is used based on the deployment region." Outputs, WaitCondition, and Resources do not provide this mapping functionality.
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Comprehensive and Detailed Explanation From Exact Extract:
The CloudFormation template feature should be used to specify the AWS resources to be provisioned. A template is a JSON or YAML file that defines the resources (e.g., EC2 instances, S3 buckets) and their configurations for deployment. The WGU Cloud Deployment and Operations Study Guide (Section 5.3, CloudFormation Templates) states, "The template is the core component of CloudFormation, containing the resource specifications and properties that are provisioned when a stack is created." Change sets, exports, and stack sets serve different purposes (e.g., previewing changes, sharing outputs, managing multiple stacks).
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Comprehensive and Detailed Explanation From Exact Extract:
AWS CloudFormation uses YAML and JSON languages to define infrastructure as code (IaC) templates, specifying resources, parameters, and configurations. These formats are human-readable and support the creation of stacks for provisioning AWS resources. The WGU Cloud Deployment and Operations Study Guide (Section 5.3, CloudFormation) states, "CloudFormation templates can be written in YAML or JSON, both of which are supported for defining infrastructure resources like EC2 instances and S3 buckets." XML and C# are not supported languages for CloudFormation templates.
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The inability to make an AMI public is caused by an encrypted boot volume. AWS does not allow AMIs with encrypted EBS snapshots to be shared publicly due to security constraints; sharing is limited to specific AWS accounts. The WGU Cloud Deployment and Operations Study Guide (Section 6.3, AMI Management) states, "An AMI cannot be made public if its boot volume is encrypted; encryption restricts sharing to authorized accounts only, requiring decryption keys to be managed separately." Legacy BIOS, paravirtual virtualization, and the absence of a bookmark do not impact AMI sharing.
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CloudWatch should be used to identify and shut down idle EC2 instances by monitoring metrics such as CPU utilization or network activity. Custom alarms can be set to trigger an AWS Lambda function or Systems Manager automation to terminate idle instances, optimizing costs. The WGU Cloud Deployment and Operations Study Guide (Section 4.1, CloudWatch Metrics) states, "CloudWatch can monitor EC2 instance metrics like CPUUtilization; an alarm can be configured to invoke a Lambda function to terminate idle instances, ensuring cost efficiency." CloudFront, CloudSearch, and CloudTrail are not designed for this monitoring and automation task.
정답: C
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Comprehensive and Detailed Explanation From Exact Extract:
To reduce latency in region B due to increased demand for media files stored in region A, cross-region replication (CRR) should be used. CRR replicates objects to an S3 bucket in another region (e.g., region B), allowing users to access files from a closer location, thus minimizing latency. The WGU Cloud Deployment and Operations Study Guide (Section 2.2, S3 Replication) states, "Cross-Region Replication in S3 copies objects to a destination bucket in a different region, reducing latency by enabling access to data from the nearest region, such as region B in this case." S3 Batch, S3 Versioning, and Same-Region replication do not address cross-region latency.
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To protect critical data on EBS volumes with a maximum tolerable data loss of one hour, the company should schedule automated volume snapshots using CloudWatch Events. Snapshots capture the state of the volume at a point in time, and regular scheduling (e.g., every hour) ensures data loss is limited to the snapshot interval. The WGU Cloud Deployment and Operations Study Guide (Section 7.3, EBS and Snapshots) states, "Automated EBS snapshots can be scheduled using CloudWatch Events rules to create backups at defined intervals, ensuring an RPO of one hour by capturing volume data regularly." Local storage, Cloud Control backups, and Block Express are not viable solutions for this automated snapshot requirement.
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Recovery Point Objective (RPO) measures the maximum acceptable data loss, while Recovery Time Objective (RTO) measures the maximum acceptable downtime. The company requires an RPO of up to 3 hours (acceptable data loss) and an RTO of 1 hour (service restoration time). The correct option is RPO 4 hours, RTO 1 hour, as it meets the RPO requirement (allowing up to 3 hours of data loss is within 4 hours) and satisfies the RTO of 1 hour. The WGU Cloud Deployment and Operations Study Guide (Section 8.1, Disaster Recovery) states, "RPO defines the maximum data loss tolerance (e.g., 3 hours), and RTO defines the maximum downtime (e.g., 1 hour); a configuration of RPO 4 hours and RTO 1 hour aligns with these thresholds." Other options fail to meet both criteria simultaneously.
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Explanation:
The multivalue routing policy in Amazon Route 53 allows up to 8 healthy records to be returned in response to DNS queries, enabling load balancing across multiple resources. To ensure the maximum allowed number of records is utilized, the administrator should create 8 records. The WGU Cloud Deployment and Operations Study Guide (Section 3.1, Route 53 Routing Policies) specifies, "Multivalue answer routing supports up to 8 healthy resource record sets per response, requiring the creation of 8 records to maximize the policy's capability." Options A, C, and D exceed or fall short of this limit.
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Explanation:
The latency routing policy in Amazon Route 53 should be used to direct customer requests to the website with the shortest round-trip time (RTT). This policy routes traffic to the AWS region with the lowest latency based on the user's location, optimizing performance. The WGU Cloud Deployment and Operations Study Guide (Section 3.1, Route 53 Routing Policies) states, "The latency-based routing policy in Route 53 measures RTT to direct users to the region with the lowest latency, improving user experience across multiple websites." Geolocation, geoproximity, and weighted policies do not prioritize RTT in this manner.
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Explanation:
To meet the requirements, the administrator should use an Amazon RDS Multi-AZ DB instance for multiple Availability Zones and failover support, and an Amazon Aurora DB instance with Aurora Replica for a read-only connection. The RDS Multi-AZ configuration automatically provisions a standby instance in a different AZ for failover, while Aurora Replicas provide read-only instances for scaling read traffic. The WGU Cloud Deployment and Operations Study Guide (Section 7.1, RDS and Aurora) states, "RDS Multi-AZ deploys a standby instance across AZs for failover, and Aurora Replicas are read-only instances that enhance performance by offloading read traffic from the primary instance."
Options A and D are incorrect as multi-master replication and Multi-AZ clusters do not align with the read-only requirement.
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When Amazon Route 53 determines an endpoint is unhealthy based on a failure threshold (e.g., via health checks), it terminates the connection attempt to that endpoint and routes traffic to a healthy alternative, if available. This behavior ensures high availability using routing policies like failover or latency-based routing. The WGU Cloud Deployment and Operations Study Guide (Section 3.1, Route 53 Health Checks) states, "Route 53 stops routing traffic to an unhealthy endpoint by terminating connection attempts once the health check failure threshold is exceeded, redirecting to a healthy resource."
Options A, C, and D are not direct actions taken by Route 53 in this scenario.
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Explanation:
Elastic Load Balancing (ELB) should be used to horizontally scale Amazon EC2 instances by distributing incoming traffic across multiple instances, improving availability and fault tolerance. ELB works in conjunction with Auto Scaling groups to add or remove instances based on demand. The WGU Cloud Deployment and Operations Study Guide (Section 3.2, Elastic Load Balancing) notes, "Elastic Load Balancing distributes traffic across EC2 instances, enabling horizontal scaling as part of an Auto Scaling group to handle increased load efficiently." Elastic IPs, elastic network interfaces, and Elastic Beanstalk do not provide this scaling functionality.