Question 451
A company that provides wireless services needs a solution to store and analyze log files about user activities. Currently, log files are delivered daily to AmazonLinux on an Amazon EC2 instance. A batch script is run once a day to aggregate data used for analysis by a third-party tool. The data pushed to the third-party tool is used to generate a visualization for end users. The batch script is cumbersome to maintain, and it takes several hours to deliver the ever-increasing data volumes to the third-party tool. The company wants to lower costs, and is open to considering a new tool that minimizes development effort and lowers administrative overhead. The company wants to build a more agile solution that can store and perform the analysis in near-real time, with minimal overhead. The solution needs to be cost effective and scalable to meet the company's end-user base growth.
Which solution meets the company's requirements?
A. Develop a Python script to capture the data from Amazon EC2 in real time and store the data in Amazon S3. Use a copy command to copy data from Amazon S3 to Amazon Redshift. Connect a business intelligence tool running on Amazon EC2 to Amazon Redshift and create the visualizations.
B. Use an Amazon Kinesis agent running on an EC2 instance in an Auto Scaling group to collect and send the data to an Amazon Kinesis Data Firehose delivery stream. The Kinesis Data Firehose delivery stream will deliver the data directly to Amazon ES. Use Kibana to visualize the data.
C. Use an in-memory caching application running on an Amazon EBS-optimized EC2 instance to capture the log data in near real-time. Install an Amazon ES cluster on the same EC2 instance to store the log files as they are delivered to Amazon EC2 in near real-time. Install a Kibana plugin to create the visualizations.
D. Use an Amazon Kinesis agent running on an EC2 instance to collect and send the data to an Amazon Kinesis Data Firehose delivery stream. The Kinesis Data Firehose delivery stream will deliver the data to Amazon S3. Use an AWS Lambda function to deliver the data from Amazon S3 to Amazon ES. Use Kibana to visualize the data.
Question 452
A company wants to move a web application to AWS. The application stores session information locally on each web server, which will make auto scaling difficult.
As part of the migration, the application will be rewritten to decouple the session data from the web servers. The company requires low latency, scalability, and availability.
Which service will meet the requirements for storing the session information in the MOST cost-effective way?
A. Amazon ElastiCache with the Memcached engine
B. Amazon S3
C. Amazon RDS MySQL
D. Amazon ElastiCache with the Redis engine
Question 453
A company has an Amazon EC2 deployment that has the following architecture:
- An application tier that contains 8 m4.xlarge instances
- A Classic Load Balancer
- Amazon S3 as a persistent data storeAfter one of the EC2 instances fails, users report very slow processing of their requests. A Solutions Architect must recommend design changes to maximize system reliability. The solution must minimize costs.
What should the Solutions Architect recommend?
A. Migrate the existing EC2 instances to a serverless deployment using AWS Lambda functions
B. Change the Classic Load Balancer to an Application Load Balancer
C. Replace the application tier with m4.large instances in an Auto Scaling group
D. Replace the application tier with 4 m4.2xlarge instances
Question 454
An on-premises application will be migrated to the cloud. The application consists of a single Elasticsearch virtual machine with data source feeds from local systems that will not be migrated, and a Java web application on Apache Tomcat running on three virtual machines. The Elasticsearch server currently uses 1 TB of storage out of 16 TB available storage, and the web application is updated every 4 months. Multiple users access the web application from the Internet. There is a 10Gbit AWS Direct Connect connection established, and the application can be migrated over a scheduled 48-hour change window.
Which strategy will have the LEAST impact on the Operations staff after the migration?
A. Create an Elasticsearch server on Amazon EC2 right-sized with 2 TB of Amazon EBS and a public AWS Elastic Beanstalk environment for the web application. Pause the data sources, export the Elasticsearch index from on premises, and import into the EC2 Elasticsearch server. Move data source feeds to the new Elasticsearch server and move users to the web application.
B. Create an Amazon ES cluster for Elasticsearch and a public AWS Elastic Beanstalk environment for the web application. Use AWS DMS to replicate Elasticsearch data. When replication has finished, move data source feeds to the new Amazon ES cluster endpoint and move users to the new web application.
C. Use the AWS SMS to replicate the virtual machines into AWS. When the migration is complete, pause the data source feeds and start the migrated Elasticsearch and web application instances. Place the web application instances behind a public Elastic Load Balancer. Move the data source feeds to the new Elasticsearch server and move users to the new web Application Load Balancer.
D. Create an Amazon ES cluster for Elasticsearch and a public AWS Elastic Beanstalk environment for the web application. Pause the data source feeds, export the Elasticsearch index from on premises, and import into the Amazon ES cluster. Move the data source feeds to the new Amazon ES cluster endpoint and move users to the new web application.
Question 455
A company's application is increasingly popular and experiencing latency because of high volume reads on the database server.
The service has the following properties:
- A highly available REST API hosted in one region using Application Load Balancer (ALB) with auto scaling.
- A MySQL database hosted on an Amazon EC2 instance in a single Availability Zone.
The company wants to reduce latency, increase in-region database read performance, and have multi-region disaster recovery capabilities that can perform a live recovery automatically without any data or performance loss (HA/DR).
Which deployment strategy will meet these requirements?
A. Use AWS CloudFormation StackSets to deploy the API layer in two regions. Migrate the database to an Amazon Aurora with MySQL database cluster with multiple read replicas in one region and a read replica in a different region than the source database cluster. Use Amazon Route 53 health checks to trigger a DNS failover to the standby region if the health checks to the primary load balancer fail. In the event of Route 53 failover, promote the cross-region database replica to be the master and build out new read replicas in the standby region.
B. Use Amazon ElastiCache for Redis Multi-AZ with an automatic failover to cache the database read queries. Use AWS OpsWorks to deploy the API layer, cache layer, and existing database layer in two regions. In the event of failure, use Amazon Route 53 health checks on the database to trigger a DNS failover to the standby region if the health checks in the primary region fail. Back up the MySQL database frequently, and in the event of a failure in an active region, copy the backup to the standby region and restore the standby database.
C. Use AWS CloudFormation StackSets to deploy the API layer in two regions. Add the database to an Auto Scaling group. Add a read replica to the database in the second region. Use Amazon Route 53 health checks on the database to trigger a DNS failover to the standby region if the health checks in the primary region fail. Promote the cross-region database replica to be the master and build out new read replicas in the standby region.
D. Use Amazon ElastiCache for Redis Multi-AZ with an automatic failover to cache the database read queries. Use AWS OpsWorks to deploy the API layer, cache layer, and existing database layer in two regions. Use Amazon Route 53 health checks on the ALB to trigger a DNS failover to the standby region if the health checks in the primary region fail. Back up the MySQL database frequently, and in the event of a failure in an active region, copy the backup to the standby region and restore the standby database.
Question 456
A company runs a three-tier application in AWS. Users report that the application performance can vary greatly depending on the time of day and functionality being accessed.
The application includes the following components:
- Eight t2.large front-end web servers that serve static content and proxy dynamic content from the application tier.
- Four t2.large application servers.
- One db.m4.large Amazon RDS MySQL Multi-AZ DB instance.
Operations has determined that the web and application tiers are network constrained.
Which of the following is a cost effective way to improve application performance? (Choose two.)
A. Replace web and app tiers with t2.xlarge instances
B. Use AWS Auto Scaling and m4.large instances for the web and application tiers
C. Convert the MySQL RDS instance to a self-managed MySQL cluster on Amazon EC2
D. Create an Amazon CloudFront distribution to cache content
E. Increase the size of the Amazon RDS instance to db.m4.xlarge
Question 457
An online retailer needs to regularly process large product catalogs, which are handled in batches. These are sent out to be processed by people using theAmazon Mechanical Turk service, but the retailer has asked its Solutions Architect to design a workflow orchestration system that allows it to handle multiple concurrent Mechanical Turk operations, deal with the result assessment process, and reprocess failures.
Which of the following options gives the retailer the ability to interrogate the state of every workflow with the LEAST amount of implementation effort?
A. Trigger Amazon CloudWatch alarms based upon message visibility in multiple Amazon SQS queues (one queue per workflow stage) and send messages via Amazon SNS to trigger AWS Lambda functions to process the next step. Use Amazon ES and Kibana to visualize Lambda processing logs to see the workflow states.
B. Hold workflow information in an Amazon RDS instance with AWS Lambda functions polling RDS for status changes. Worker Lambda functions then process the next workflow steps. Amazon QuickSight will visualize workflow states directly out of Amazon RDS.
C. Build the workflow in AWS Step Functions, using it to orchestrate multiple concurrent workflows. The status of each workflow can be visualized in the AWS Management Console, and historical data can be written to Amazon S3 and visualized using Amazon QuickSight.
D. Use Amazon SWF to create a workflow that handles a single batch of catalog records with multiple worker tasks to extract the data, transform it, and send it through Mechanical Turk. Use Amazon ES and Kibana to visualize AWS Lambda processing logs to see the workflow states.
Question 458
An organization has two Amazon EC2 instances:
- The first is running an ordering application and an inventory application.
The second is running a queuing system.
During certain times of the year, several thousand orders are placed per second. Some orders were lost when the queuing system was down. Also, the organization's inventory application has the incorrect quantity of products because some orders were processed twice.
What should be done to ensure that the applications can handle the increasing number of orders?
A. Put the ordering and inventory applications into their own AWS Lambda functions. Have the ordering application write the messages into an Amazon SQS FIFO queue.
B. Put the ordering and inventory applications into their own Amazon ECS containers, and create an Auto Scaling group for each application. Then, deploy the message queuing server in multiple Availability Zones.
C. Put the ordering and inventory applications into their own Amazon EC2 instances, and create an Auto Scaling group for each application. Use Amazon SQS standard queues for the incoming orders, and implement idempotency in the inventory application.
D. Put the ordering and inventory applications into their own Amazon EC2 instances. Write the incoming orders to an Amazon Kinesis data stream. Configure AWS Lambda to poll the stream and update the inventory application.
Question 459
A company is migrating its on-premises build artifact server to an AWS solution. The current system consists of an Apache HTTP server that serves artifacts to clients on the local network, restricted by the perimeter firewall. The artifact consumers are largely build automation scripts that download artifacts via anonymousHTTP, which the company will be unable to modify within its migration timetable.
The company decides to move the solution to Amazon S3 static website hosting. The artifact consumers will be migrated to Amazon EC2 instances located within both public and private subnets in a virtual private cloud (VPC).
Which solution will permit the artifact consumers to download artifacts without modifying the existing automation scripts?
A. Create a NAT gateway within a public subnet of the VPC. Add a default route pointing to the NAT gateway into the route table associated with the subnets containing consumers. Configure the bucket policy to allow the s3:ListBucket and s3:GetObject actions using the condition IpAddress and the condition key aws:SourceIp matching the elastic IP address of the NAT gateway.
B. Create a VPC endpoint and add it to the route table associated with subnets containing consumers. Configure the bucket policy to allow s3:ListBucket and s3:GetObject actions using the condition StringEquals and the condition key aws:sourceVpce matching the identification of the VPC endpoint.
C. Create an IAM role and instance profile for Amazon EC2 and attach it to the instances that consume build artifacts. Configure the bucket policy to allow the s3:ListBucket and s3:GetObjects actions for the principal matching the IAM role created.
D. Create a VPC endpoint and add it to the route table associated with subnets containing consumers. Configure the bucket policy to allow s3:ListBucket and s3:GetObject actions using the condition IpAddress and the condition key aws:SourceIp matching the VPC CIDR block.
Question 460
A group of research institutions and hospitals are in a partnership to study 2 PBs of genomic data. The institute that owns the data stores it in an Amazon S3 bucket and updates it regularly. The institute would like to give all of the organizations in the partnership read access to the data. All members of the partnership are extremely cost-conscious, and the institute that owns the account with the S3 bucket is concerned about covering the costs for requests and data transfers from Amazon S3.
Which solution allows for secure datasharing without causing the institute that owns the bucket to assume all the costs for S3 requests and data transfers?
A. Ensure that all organizations in the partnership have AWS accounts. In the account with the S3 bucket, create a cross-account role for each account in the partnership that allows read access to the data. Have the organizations assume and use that read role when accessing the data.
B. Ensure that all organizations in the partnership have AWS accounts. Create a bucket policy on the bucket that owns the data. The policy should allow the accounts in the partnership read access to the bucket. Enable Requester Pays on the bucket. Have the organizations use their AWS credentials when accessing the data.
C. Ensure that all organizations in the partnership have AWS accounts. Configure buckets in each of the accounts with a bucket policy that allows the institute that owns the data the ability to write to the bucket. Periodically sync the data from the institute's account to the other organizations. Have the organizations use their AWS credentials when accessing the data using their accounts.
D. Ensure that all organizations in the partnership have AWS accounts. In the account with the S3 bucket, create a cross-account role for each account in the partnership that allows read access to the data. Enable Requester Pays on the bucket. Have the organizations assume and use that read role when accessing the data.