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Amazon AWS-CERTIFIED-BIG-DATA-SPECIALTY AWS-Certified-Big-Data-Specialty Dumps in PDF

Free Amazon AWS-Certified-Big-Data-Specialty Real Questions (page: 18)

AWS-Certified-Big-Data-Specialty PDF — 492 Questions

A data engineer is running a DWH on a 25-node Redshift cluster of a SaaS service. The data engineer needs to build a dashboard that will be used by customers. Five big customers represent 80% of usage, and there is a long tail of dozens of smaller customers. The data engineer has selected the dashboarding tool.
How should the data engineer make sure that the larger customer workloads do NOT interfere with the smaller customer workloads?

  1. Apply query filters based on customer-id that can NOT be changed by the user and apply distribution keys on customer id
  2. Place the largest customers into a single user group with a dedicated query queue and place the rest of the customer into a different query queue
  3. Push aggregations into an RDS for Aurora instance. Connect the dashboard application to Aurora rather than Redshift for faster queries
  4. Route the largest customers to a dedicated Redshift cluster, Raise the concurrency of the multi- tenant Redshift cluster to accommodate the remaining customers

Answer(s): D



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, issue 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?

  1. 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
  2. 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 Amazon Redshift cluster
  3. 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
  4. 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
  5. 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

Answer(s): C



Using only AWS services. You intend to automatically scale a fileet of stateless of stateless web servers based on CPU and network utilization metrics. Which of the following services are needed? Choose 2 answers

  1. Auto Scaling
  2. Amazon Simple Notification Service
  3. AWS Cloud Formation
  4. CloudWatch
  5. Amazon Simple Workflow Service

Answer(s): A,D



When an EC2 instance that is backed by an s3-based AMI is terminated. What happens to the data on the root volume?

  1. Data is unavailable until the instance is restarted
  2. Data is automatically deleted
  3. Data is automatically saved as an EBS snapshot
  4. Data is automatically saved as an EBS volume

Answer(s): B



A user has created a launch configuration for Auto Scaling where CloudWatch detailed monitoring is disabled. The user wants to now enable detailed monitoring. How can the user achieve this?

  1. Update the Launch config with CLI to set InstanceMonitoringDisabled = false
  2. The user should change the Auto Scaling group from the AWS console to enable detailed monitoring
  3. Update the Launch config with CLI to set InstanceMonitoring.Enabled = true
  4. Create a new Launch Config with detail monitoring enabled and update the Auto Scaling group

Answer(s): D



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