Free WGU Cloud Deployment and Operations Cloud-Deployment-and-Operations Exam Questions

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Spot Instances are the most suitable EC2 instance type for this workload pattern, offering the lowest cost for short, interruptible tasks like 3D rendering, where work can be redistributed if interrupted. This aligns with the company's cost-plus pricing model. The WGU Cloud Deployment and Operations Study Guide (Section 7.3, EC2 Instance Types) states, 'Spot Instances provide significant cost savings (up to 90% off On-Demand) for fault-tolerant, short-term workloads like rendering, where interruptions can be handled by redistributing tasks to other nodes.' On-Demand, Dedicated, and Reserved Instances are more expensive and less flexible for this use case.

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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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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.

A metric filter in Amazon CloudWatch Logs can be used to search for specific terms in log data and create metrics based on the matches. To include log events with the word 'ERROR' and exclude those with the word 'WARNING,' the correct syntax involves using a filter pattern with a positive match for 'ERROR' and a negation for 'WARNING.' The correct pattern is 'ERROR -WARN,' where the minus sign (-) indicates exclusion of log events containing 'WARN.' According to the WGU Cloud Deployment and Operations Study Guide (Section 4.2, CloudWatch Logs), metric filters use a pattern-based syntax where terms are included or excluded using positive matches and the negation operator (-). This ensures that only logs with 'ERROR' and without 'WARN' are processed into the metric.

Amazon CloudWatch alarms can trigger notifications when a metric breaches a defined threshold. The AWS solution designed to send emails based on these alarms is Amazon Simple Notification Service (SNS). SNS supports sending notifications via email, SMS, and other protocols when subscribed endpoints are triggered by CloudWatch alarms. The WGU Cloud Deployment and Operations Study Guide (Section 4.3, Monitoring and Alarms) states that SNS is the primary service for delivering notifications from CloudWatch, allowing users to configure email subscriptions for alarm states. Other options like SQS, Amplify, and Kinesis are not designed for this purpose.

To reduce conversion delays caused by increased demand, the company should configure a CloudWatch alarm to scale the EC2 fleet based on the SQS queue length. This auto-scaling approach dynamically adjusts the number of EC2 instances to handle the workload, especially during peak evening hours and anticipated growth. The WGU Cloud Deployment and Operations Study Guide (Section 3.3, Auto Scaling and SQS) explains, 'Auto Scaling can be triggered by a CloudWatch alarm monitoring SQS queue depth, ensuring the EC2 fleet scales out to process video conversion tasks efficiently as the queue length increases.' Spot instances, dead-letter queues, and instance type upgrades do not directly address dynamic scaling needs.

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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A Billing alarm in Amazon CloudWatch should be used to monitor estimated AWS charges by setting thresholds on cost metrics and triggering notifications when exceeded. This helps manage budgets effectively. The WGU Cloud Deployment and Operations Study Guide (Section 7.4, Cost Monitoring) states, 'Billing alarms in CloudWatch monitor estimated charges against a defined threshold, sending alerts via SNS to prevent cost overruns.' Cognito handles user authentication, Pricing Calculator estimates costs pre-deployment, and Forecast predicts usage, none of which monitor real-time charges.

Amazon EventBridge is the AWS solution that can be used to send events from external sources like Shopify. EventBridge supports integration with third-party applications through its event bus, allowing custom events (e.g., from Shopify via webhooks) to be ingested and routed to AWS services or targets. The WGU Cloud Deployment and Operations Study Guide (Section 4.3, EventBridge) notes that EventBridge is designed for event ingestion from SaaS applications, making it suitable for Shopify integration. CloudTrail, IoT Events, and Service events are not designed for this purpose.

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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.