QUESTION: 85

An online photo album app has a key design feature to support multiple screens (e.g. desktop, mobile phone, and tablet) with high quality displays. Multiple versions of the image must be saved in different resolutions and layouts.
The image processing Java program takes an average of five seconds per upload, depending on the image size and format. Each image upload captures the following image metadata: user, album, photo label, upload timestamp
The app should support the following requirements:
• Hundreds of user image uploads per second
• Maximum image metadata size of 10 MB
• Maximum image metadata size of 1 KB
• Image displayed in optimized resolution in all supported screens no later than one minute after image upload
Which strategy should be used to meet these requirements?

Write images and metadata to Amazon Kinesis, Use a Kinesis Client Library (KCL) application to run the image processing and save the image output to Amazon S3 and metadata to the app repository DB
Write image and metadata RDS with BLOB data type. Use AWS Data Pipeline to run the image processing and save the image output to Amazon S3 and metadata to the app repository DB
Upload image with metadata to Amazon S3 use Lambda function to run the image processing and save the image output to Amazon S3 and metadata to the app repository DB
Write image and metadata to Amazon kinesis. Use Amazon Elastic MapReduce (EMR) with Spark Streaming to run image processing and save image output to Amazon

Answer(s): D

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QUESTION: 86

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?

Apply query filters based on customer-id that can NOT be changed by the user and apply distribution keys on customer id
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
Push aggregations into an RDS for Aurora instance. Connect the dashboard application to Aurora rather than Redshift for faster queries
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

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QUESTION: 87

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?

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
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
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
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
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

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QUESTION: 88

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

Auto Scaling
Amazon Simple Notification Service
AWS Cloud Formation
CloudWatch
Amazon Simple Workflow Service

Answer(s): A,D

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