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Question 661

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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?

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.
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.
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.
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.
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.
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.
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.
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.
Suggested answer: C

Explanation:

Reference:

https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/standard-queues.html

asked 16/09/2024
Quintin van Rooyen
44 questions

Question 662

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While debugging a backend application for an IoT system that supports globally distributed devices, a Solutions Architect notices that stale data is occasionally being sent to user devices. Devices often share data, and stale data does not cause issues in most cases. However, device operations are disrupted when a device reads the stale data after an update.

The global system has multiple identical application stacks deployed in different AWS Regions. If a user device travels out of its home geographic region, it will always connect to the geographically closest AWS Region to write or read data.

The same data is available in all supported AWS Regions using an Amazon DynamoDB global table.

What change should be made to avoid causing disruptions in device operations?

Update the backend to use strongly consistent reads. Update the devices to always write to and read from their home AWS Region.
Update the backend to use strongly consistent reads. Update the devices to always write to and read from their home AWS Region.
Enable strong consistency globally on a DynamoDB global table. Update the backend to use strongly consistent reads.
Enable strong consistency globally on a DynamoDB global table. Update the backend to use strongly consistent reads.
Switch the backend data store to Amazon Aurora MySQL with cross-region replicas. Update the backend to always write to the master endpoint.
Switch the backend data store to Amazon Aurora MySQL with cross-region replicas. Update the backend to always write to the master endpoint.
Select one AWS Region as a master and perform all writes in that AWS Region only. Update the backend to use strongly consistent reads.
Select one AWS Region as a master and perform all writes in that AWS Region only. Update the backend to use strongly consistent reads.
Suggested answer: A
asked 16/09/2024
Lea Kohl
46 questions

Question 663

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You are migrating a legacy client-server application to AWS. The application responds to a specific DNS domain (e.g. www.example.com) and has a 2-tier architecture, with multiple application servers and a database server. Remote clients use TCP to connect to the application servers. The application servers need to know the IP address of the clients in order to function properly and are currently taking that information from the TCP socket. A Multi-AZ RDS MySQL instance will be used for the database. During the migration you can change the application code, but you have to file a change request. How would you implement the architecture on AWS in order to maximize scalability and high availability?

File a change request to implement Alias Resource support in the application. Use Route 53 Alias Resource Record to distribute load on two application servers in different Azs.
File a change request to implement Alias Resource support in the application. Use Route 53 Alias Resource Record to distribute load on two application servers in different Azs.
File a change request to implement Latency Based Routing support in the application. Use Route 53 with Latency Based Routing enabled to distribute load on two application servers in different Azs.
File a change request to implement Latency Based Routing support in the application. Use Route 53 with Latency Based Routing enabled to distribute load on two application servers in different Azs.
File a change request to implement Cross-Zone support in the application. Use an ELB with a TCP Listener and Cross- Zone Load Balancing enabled, two application servers in different AZs.
File a change request to implement Cross-Zone support in the application. Use an ELB with a TCP Listener and Cross- Zone Load Balancing enabled, two application servers in different AZs.
File a change request to implement Proxy Protocol support in the application. Use an ELB with a TCP Listener and Proxy Protocol enabled to distribute load on two application servers in different Azs.
File a change request to implement Proxy Protocol support in the application. Use an ELB with a TCP Listener and Proxy Protocol enabled to distribute load on two application servers in different Azs.
Suggested answer: D

Explanation:

Reference:

https://aws.amazon.com/blogs/aws/elastic-load-balancing-adds-support-for-proxy-protocol/

asked 16/09/2024
David Aghaegbuna
41 questions

Question 664

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A 3-tier e-commerce web application is current deployed on-premises and will be migrated to AWS for greater scalability and elasticity. The web server currently shares read-only data using a network distributed file system. The app server tier uses a clustering mechanism for discovery and shared session state that depends on IP multicast. The database tier uses sharedstorage clustering to provide database fall over capability, and uses several read slaves for scaling. Data on all servers and the distributed file system directory is backed up weekly to off-site tapes.

Which AWS storage and database architecture meets the requirements of the application?

Web servers: store read-only data in S3, and copy from S3 to root volume at boot time. App servers: share state using a combination of DynamoDB and IP unicast. Database: use RDS with multi-AZ deployment and one or more read replicas.Backup: web servers, app servers, and database backed up weekly to Glacier using snapshots.
Web servers: store read-only data in S3, and copy from S3 to root volume at boot time. App servers: share state using a combination of DynamoDB and IP unicast. Database: use RDS with multi-AZ deployment and one or more read replicas.Backup: web servers, app servers, and database backed up weekly to Glacier using snapshots.
Web servers: store read-only data in an EC2 NFS server; mount to each web server at boot time. App servers: share state using a combination of DynamoDB and IP multicast. Database: use RDS with multi-AZ deployment and one or more Read Replicas. Backup: web and app servers backed up weekly via AMIs, database backed up via DB snapshots.
Web servers: store read-only data in an EC2 NFS server; mount to each web server at boot time. App servers: share state using a combination of DynamoDB and IP multicast. Database: use RDS with multi-AZ deployment and one or more Read Replicas. Backup: web and app servers backed up weekly via AMIs, database backed up via DB snapshots.
Web servers: store read-only data in S3, and copy from S3 to root volume at boot time. App servers: share state using a combination of DynamoDB and IP unicast. Database: use RDS with multi-AZ deployment and one or more Read Replicas.Backup: web and app servers backed up weekly via AMIs, database backed up via DB snapshots.
Web servers: store read-only data in S3, and copy from S3 to root volume at boot time. App servers: share state using a combination of DynamoDB and IP unicast. Database: use RDS with multi-AZ deployment and one or more Read Replicas.Backup: web and app servers backed up weekly via AMIs, database backed up via DB snapshots.
Web servers: store read-only data in S3, and copy from S3 to root volume at boot time. App servers: share state using a combination of DynamoDB and IP unicast. Database: use RDS with multi-AZ deployment. Backup: web and app servers backed up weekly via AMIs, database backed up via DB snapshots.
Web servers: store read-only data in S3, and copy from S3 to root volume at boot time. App servers: share state using a combination of DynamoDB and IP unicast. Database: use RDS with multi-AZ deployment. Backup: web and app servers backed up weekly via AMIs, database backed up via DB snapshots.
Suggested answer: C

Explanation:

Amazon RDS Multi-AZ deployments provide enhanced availability and durability for Database (DB) Instances, making them a natural fit for production database workloads. When you provision a Multi-AZ DB Instance, Amazon RDS automatically creates a primary DB Instance and synchronously replicates the data to a standby instance in a different Availability Zone (AZ). Each AZ runs on its own physically distinct, independent infrastructure, and is engineered to be highly reliable. In case of an infrastructure failure (for example, instance hardware failure, storage failure, or network disruption), Amazon RDS performs an automatic failover to the standby, so that you can resume database operations as soon as the failover is complete. Since the endpoint for your DB Instance remains the same after a failover, your application can resume database operation without the need for manual administrative intervention. Benefits Enhanced Durability Multi-AZ deployments for the MySQL, Oracle, and PostgreSQL engines utilize synchronous physical replication to keep data on the standby up-to-date with the primary. Multi-AZ deployments for the SQL Server engine use synchronous logical replication to achieve the same result, employing SQL Server-native Mirroring technology. Both approaches safeguard your data in the event of a DB Instance failure or loss of an Availability Zone. If a storage volume on your primary fails in a Multi-AZ deployment, Amazon RDS automatically initiates a failover to the upto- date standby. Compare this to a Single-AZ deployment: in case of a Single-AZ database failure, a user-initiated point-intime- restore operation will be required. This operation can take several hours to complete, and any data updates that occurred after the latest restorable time (typically within the last five minutes) will not be available. Amazon Aurora employs a highly durable, SSD-backed virtualized storage layer purpose-built for database workloads. Amazon Aurora automatically replicates your volume six ways, across three Availability Zones. Amazon Aurora storage is fault-tolerant, transparently handling the loss of up to two copies of data without affecting database write availability and up to three copies without affecting read availability. Amazon Aurora storage is also self-healing. Data blocks and disks are continuously scanned for errors and replaced automatically. Increased Availability

You also benefit from enhanced database availability when running Multi-AZ deployments. If an Availability Zone failure or DB Instance failure occurs, your availability impact is limited to the time automatic failover takes to complete:

typically under one minute for Amazon Aurora and one to two minutes for other database engines (see the RDS FAQ for details). The availability benefits of Multi-AZ deployments also extend to planned maintenance and backups. In the case of system upgrades like OS patching or DB Instance scaling, these operations are applied first on the standby, prior to the automatic failover. As a result, your availability impact is, again, only the time required for automatic failover to complete. Unlike Single-AZ deployments, I/O activity is not suspended on your primary during backup for Multi-AZ deployments for the MySQL, Oracle, and PostgreSQL engines, because the backup is taken from the standby. However, note that you may still experience elevated latencies for a few minutes during backups for Multi-AZ deployments.

On instance failure in Amazon Aurora deployments, Amazon RDS uses RDS Multi-AZ technology to automate failover to one of up to 15 Amazon Aurora Replicas you have created in any of three Availability Zones. If no Amazon Aurora Replicas have been provisioned, in the case of a failure, Amazon RDS will attempt to create a new Amazon Aurora DB instance for you automatically. No Administrative Intervention

DB Instance failover is fully automatic and requires no administrative intervention. Amazon RDS monitors the health of your primary and standbys, and initiates a failover automatically in response to a variety of failure conditions. Failover conditions

Amazon RDS detects and automatically recovers from the most common failure scenarios for Multi-AZ deployments so that you can resume database operations as quickly as possible without administrative intervention. Amazon RDS automatically performs a failover in the event of any of the following:

Loss of availability in primary Availability Zone

Loss of network connectivity to primary

Compute unit failure on primary

Storage failure on primary

Note: When operations such as DB Instance scaling or system upgrades like OS patching are initiated for Multi-AZ deployments, for enhanced availability, they are applied first on the standby prior to an automatic failover. As a result, your availability impact is limited only to the time required for automatic failover to complete. Note that Amazon RDS Multi-AZ deployments do not failover automatically in response to database operations such as long running queries, deadlocks or database corruption errors.

asked 16/09/2024
Aung Zin
41 questions

Question 665

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A mobile gaming application publishes data continuously to Amazon Kinesis Data Streams. An AWS Lambda function processes records from the data stream and writes to an Amazon DynamoDB table. The DynamoDB table has an auto scaling policy enabled with the target utilization set to 70%.

For several minutes at the start and end of each day, there is a spike in traffic that often exceeds five times the normal load. The company notices the GetRecords.IteratorAgeMilliseconds metric of the Kinesis data stream temporarily spikes to over a minute for several minutes. The AWS Lambda function writes ProvisionedThroughputExceededException messages to Amazon CloudWatch Logs during these times, and some records are redirected to the dead letter queue. No exceptions are thrown by the Kinesis producer on the gaming application. What change should the company make to resolve this issue?

Use Application Auto Scaling to set a scaling schedule to scale out write capacity on the DynamoDB table during predictable load spikes.
Use Application Auto Scaling to set a scaling schedule to scale out write capacity on the DynamoDB table during predictable load spikes.
Use Amazon CloudWatch Events to monitor the dead letter queue and invoke a Lambda function to automatically retry failed records.
Use Amazon CloudWatch Events to monitor the dead letter queue and invoke a Lambda function to automatically retry failed records.
Reduce the DynamoDB table auto scaling policy's target utilization to 20% to more quickly respond to load spikes.
Reduce the DynamoDB table auto scaling policy's target utilization to 20% to more quickly respond to load spikes.
Increase the number of shards in the Kinesis data stream to increase throughput capacity.
Increase the number of shards in the Kinesis data stream to increase throughput capacity.
Suggested answer: D
asked 16/09/2024
PRADESH MATHEW
41 questions

Question 666

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Your company previously configured a heavily used, dynamically routed VPN connection between your on-premises data center and AWS. You recently provisioned a DirectConnect connection and would like to start using the new connection.

After configuring DirectConnect settings in the AWS Console, which of the following options win provide the most seamless transition for your users?

Delete your existing VPN connection to avoid routing loops configure your DirectConnect router with the appropriate settings and verity network traffic is leveraging DirectConnect.
Delete your existing VPN connection to avoid routing loops configure your DirectConnect router with the appropriate settings and verity network traffic is leveraging DirectConnect.
Configure your DirectConnect router with a higher BGP priority man your VPN router, verify network traffic is leveraging Directconnect and then delete your existing VPN connection.
Configure your DirectConnect router with a higher BGP priority man your VPN router, verify network traffic is leveraging Directconnect and then delete your existing VPN connection.
Update your VPC route tables to point to the DirectConnect connection configure your DirectConnect router with the appropriate settings verify network traffic is leveraging DirectConnect and then delete the VPN connection.
Update your VPC route tables to point to the DirectConnect connection configure your DirectConnect router with the appropriate settings verify network traffic is leveraging DirectConnect and then delete the VPN connection.
Configure your DirectConnect router, update your VPC route tables to point to the DirectConnect connection, configure your VPN connection with a higher BGP priority, and verify network traffic is leveraging the DirectConnect connection.
Configure your DirectConnect router, update your VPC route tables to point to the DirectConnect connection, configure your VPN connection with a higher BGP priority, and verify network traffic is leveraging the DirectConnect connection.
Can I use AWS Direct Connect and a VPN Connection to the same VPC simultaneously?Yes. However, only in fail-over scenarios. The Direct Connect path will always be preferred, when established, regardless of AS path prepending. Reference: https://aws.amazon.com/directconnect/faqs/
Can I use AWS Direct Connect and a VPN Connection to the same VPC simultaneously?Yes. However, only in fail-over scenarios. The Direct Connect path will always be preferred, when established, regardless of AS path prepending. Reference: https://aws.amazon.com/directconnect/faqs/
Suggested answer: C

Explanation:

Q. Can I use AWS Direct Connect and a VPN Connection to the same VPC simultaneously?

Yes. However, only in fail-over scenarios. The Direct Connect path will always be preferred, when established, regardless of AS path prepending. Reference: https://aws.amazon.com/directconnect/faqs/

asked 16/09/2024
Tommy Svendsen
37 questions

Question 667

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A retail company processes point-of-sale data on application servers in its data center and writes outputs to an Amazon DynamoDB table. The data center is connected to the company’s VPC with an AWS Direct Connect (DX) connection, and the application servers require a consistent network connection at speeds greater than 2 Gbps.

The company decides that the DynamoDB table needs to be highly available and fault tolerant. The company policy states that the data should be available across two regions. What changes should the company make to meet these requirements?

Establish a second DX connection for redundancy. Use DynamoDB global tables to replicate data to a second Region. Modify the application to fail over to the second Region.
Establish a second DX connection for redundancy. Use DynamoDB global tables to replicate data to a second Region. Modify the application to fail over to the second Region.
Use an AWS managed VPN as a backup to DX. Create an identical DynamoDB table in a second Region. Modify the application to replicate data to both Regions.
Use an AWS managed VPN as a backup to DX. Create an identical DynamoDB table in a second Region. Modify the application to replicate data to both Regions.
Establish a second DX connection for redundancy. Create an identical DynamoDB table in a second Region. Enable DynamoDB auto scaling to manage throughput capacity. Modify the application to write to the second Region.
Establish a second DX connection for redundancy. Create an identical DynamoDB table in a second Region. Enable DynamoDB auto scaling to manage throughput capacity. Modify the application to write to the second Region.
Use AWS managed VPN as a backup to DX. Create an identical DynamoDB table in a second Region. Enable DynamoDB streams to capture changes to the table. Use AWS Lambda to replicate changes to the second Region.
Use AWS managed VPN as a backup to DX. Create an identical DynamoDB table in a second Region. Enable DynamoDB streams to capture changes to the table. Use AWS Lambda to replicate changes to the second Region.
Suggested answer: A
asked 16/09/2024
marius trif
47 questions

Question 668

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A user is trying to understand the detailed CloudWatch monitoring concept. Which of the below mentioned services does not provide detailed monitoring with CloudWatch?

AWS RDS
AWS RDS
AWS ELB
AWS ELB
AWS Route53
AWS Route53
AWS EMR
AWS EMR
Suggested answer: D

Explanation:

CloudWatch is used to monitor AWS as well as the custom services. It provides either basic or detailed monitoring for the supported AWS products. In basic monitoring, a service sends data points to CloudWatch every five minutes, while in detailed monitoring a service sends data points to CloudWatch every minute. Services, such as RDS, EC2, Auto Scaling, ELB, and Route 53 can provide the monitoring data every minute.

Reference: http://docs.aws.amazon.com/AmazonCloudWatch/latest/DeveloperGuide/supported_services.html

asked 16/09/2024
Ismaiel Al-Mufleh
47 questions

Question 669

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A company runs a legacy system on a single m4.2xlarge Amazon EC2 instance with Amazon EBS storage. The EC2 instance runs both the web server and a self-managed Oracle database. A snapshot is made of the EBS volume every 12 hours, and an AMI was created from the fully configured EC2 instance.

A recent event that terminated the EC2 instance led to several hours of downtime. The application was successfully launched from the AMI, but the age of the EBS snapshot and the repair of the database resulted in the loss of 8 hours of data. The system was also down for 4 hours while the Systems Operators manually performed these processes. What architectural changes will minimize downtime and reduce the chance of lost data?

Create an Amazon CloudWatch alarm to automatically recover the instance. Create a script that will check and repair the database upon reboot. Subscribe the Operations team to the Amazon SNS message generated by the CloudWatch alarm.
Create an Amazon CloudWatch alarm to automatically recover the instance. Create a script that will check and repair the database upon reboot. Subscribe the Operations team to the Amazon SNS message generated by the CloudWatch alarm.
Run the application on m4.xlarge EC2 instances behind an Elastic Load Balancer/Application Load Balancer. Run the EC2 instances in an Auto Scaling group across multiple Availability Zones with a minimum instance count of two. Migrate the database to an Amazon RDS Oracle Multi-AZ DB instance.
Run the application on m4.xlarge EC2 instances behind an Elastic Load Balancer/Application Load Balancer. Run the EC2 instances in an Auto Scaling group across multiple Availability Zones with a minimum instance count of two. Migrate the database to an Amazon RDS Oracle Multi-AZ DB instance.
Run the application on m4.2xlarge EC2 instances behind an Elastic Load Balancer/Application Load Balancer. Run the EC2 instances in an Auto Scaling group across multiple Availability Zones with a minimum instance count of one. Migrate the database to an Amazon RDS Oracle Multi-AZ DB instance.
Run the application on m4.2xlarge EC2 instances behind an Elastic Load Balancer/Application Load Balancer. Run the EC2 instances in an Auto Scaling group across multiple Availability Zones with a minimum instance count of one. Migrate the database to an Amazon RDS Oracle Multi-AZ DB instance.
Increase the web server instance count to two m4.xlarge instances and use Amazon Route 53 round-robin load balancing to spread the load. Enable Route 53 health checks on the web servers. Migrate the database to an Amazon RDS Oracle Multi-AZ DB instance.
Increase the web server instance count to two m4.xlarge instances and use Amazon Route 53 round-robin load balancing to spread the load. Enable Route 53 health checks on the web servers. Migrate the database to an Amazon RDS Oracle Multi-AZ DB instance.
Suggested answer: B

Explanation:

Reference: https://docs.aws.amazon.com/Route53/latest/DeveloperGuide/routing-policy.html

asked 16/09/2024
Blake Heffelfinger
37 questions

Question 670

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Someone has recommended a new client to you and you know he is into online gaming and you are almost certain he will want to set up an online gaming site which will require a database service that provides fast and predictable performance with seamless scalability.

Which of the following AWS databases would be best suited to an online gaming site?

Amazon SimpleDB
Amazon SimpleDB
Amazon DynamoDB
Amazon DynamoDB
Amazon Redshift
Amazon Redshift
Amazon ElastiCache
Amazon ElastiCache
Suggested answer: B

Explanation:

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. You can use Amazon DynamoDB to create a database table that can store and retrieve any amount of data, and serve any level of request traffic. Amazon DynamoDB automatically spreads the data and traffic for the table over a sufficient number of servers to handle the request capacity specified by the customer and the amount of data stored, while maintaining consistent and fast performance.

Reference: http://aws.amazon.com/documentation/dynamodb/

asked 16/09/2024
Paul Aronen
45 questions
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