A company plans to use Route 53 instead of an ELB to load balance the incoming request to the web application. The system is deployed to two EC2 instances to which the traffic needs to be distributed. You want to set a specific percentage of traffic to go to each instance.
Which routing policy would you use?

• A.Weighted
• B.Geolocation
• C.Failover
• D.Latency

Correct Answer: A

Weighted routing lets you associate multiple resources with a single domain name (tutorialsdojo.com) or subdomain name (portal.tutorialsdojo.com) and choose how much traffic is routed to each resource. This can be useful for a variety of purposes including load balancing and testing new versions of software.
You can set a specific percentage of how much traffic will be allocated to the resource by specifying the weights.

For example, if you want to send a tiny portion of your traffic to one resource and the rest to another resource, you might specify weights of 1 and 255. The resource with a weight of 1 gets 1/256th of the traffic (1/1+255), and the other resource gets 255/256ths (255/1+255).
You can gradually change the balance by changing the weights. If you want to stop sending traffic to a resource, you can change the weight for that record to 0. Hence, the correct answer is Weighted.
Latency is incorrect because you cannot set a specific percentage of traffic for the 2 EC2 instances with this routing policy. Latency routing policy is primarily used when you have resources in multiple AWS Regions and if you need to automatically route traffic to a specific AWS Region that provides the best latency with less round-trip time.
Failover is incorrect because this type is commonly used if you want to set up an active-passive failover configuration for your web application.
Geolocation is incorrect because this is more suitable for routing traffic based on the location of your users, and not for distributing a specific percentage of traffic to two AWS resources.
Reference:
http://docs.aws.amazon.com/Route53/latest/DeveloperGuide/routing-policy.html Amazon Route 53 Overview:
https://youtu.be/Su308t19ubY
Check out this Amazon Route 53 Cheat Sheet:
https://tutorialsdojo.com/amazon-route-53/

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The media company that you are working for has a video transcoding application running on Amazon EC2. Each EC2 instance polls a queue to find out which video should be transcoded, and then runs a transcoding process. If this process is interrupted, the video will be transcoded by another instance based on the queuing system. This application has a large backlog of videos which need to be transcoded. Your manager would like to reduce this backlog by adding more EC2 instances, however, these instances are only needed until the backlog is reduced.
In this scenario, which type of Amazon EC2 instance is the most cost-effective type to use?

• A.Spot instances
• B.Reserved instances
• C.Dedicated instances
• D.On-demand instances

Correct Answer: A

You require an instance that will be used not as a primary server but as a spare compute resource to augment the transcoding process of your application. These instances should also be terminated once the backlog has been significantly reduced. In addition, the scenario mentions that if the current process is interrupted, the video can be transcoded by another instance based on the queuing system. This means that the application can gracefully handle an unexpected termination of an EC2 instance, like in the event of a Spot instance termination when the Spot price is greater than your set maximum price.
Hence, an Amazon EC2 Spot instance is the best and cost-effective option for this scenario.

Amazon EC2 Spot instances are spare compute capacity in the AWS cloud available to you at steep discounts compared to On-Demand prices. EC2 Spot enables you to optimize your costs on the AWS cloud and scale your application's throughput up to 10X for the same budget. By simply selecting Spot when launching EC2 instances, you can save up-to 90% on On-Demand prices. The only difference between On-Demand instances and Spot Instances is that Spot instances can be interrupted by EC2 with two minutes of notification when the EC2 needs the capacity back.
You can specify whether Amazon EC2 should hibernate, stop, or terminate Spot Instances when they are interrupted. You can choose the interruption behavior that meets your needs.
Take note that there is no "bid price" anymore for Spot EC2 instances since March 2018. You simply have to set your maximum price instead.
Reserved instances and Dedicated instances are incorrect as both do not act as spare compute capacity.
On-demand instances is a valid option but a Spot instance is much cheaper than On-Demand.
References:
https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/spot-interruptions.html
http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/how-spot-instances-work.html
https://aws.amazon.com/blogs/compute/new-amazon-ec2-spot-pricing
Check out this Amazon EC2 Cheat Sheet:
https://tutorialsdojo.com/amazon-elastic-compute-cloud-amazon-ec2/

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A startup needs to use a shared file system for its .NET web application running on an Amazon EC2 Windows instance. The file system must provide a high level of throughput and IOPS that can also be integrated with Microsoft Active Directory.
Which is the MOST suitable service that you should use to achieve this requirement?

• A.AWS Storage Gateway - File Gateway
• B.Amazon Elastic File System
• C.Amazon EBS Provisioned IOPS SSD volumes
• D.Amazon FSx for Windows File Server

Correct Answer: D

Amazon FSx for Windows File Server provides fully managed, highly reliable, and scalable file storage accessible over the industry-standard Service Message Block (SMB) protocol. It is built on Windows Server, delivering a wide range of administrative features such as user quotas, end-user file restore, and Microsoft Active Directory (AD) integration.
Amazon FSx supports the use of Microsoft's Distributed File System (DFS) Namespaces to scale-out performance across multiple file systems in the same namespace up to tens of Gbps and millions of IOPS.

The key phrases in this scenario are "file system" and "Active Directory integration." You need to implement a solution that will meet these requirements. Among the options given, the possible answers are FSx Windows File Server and File Gateway. But you need to consider that the question also states that you need to provide a high level of throughput and IOPS. Amazon FSx Windows File Server can scale-out storage to hundreds of petabytes of data with tens of GB/s of throughput performance and millions of IOPS.
Hence, the correct answer is: Amazon FSx for Windows File Server.
Amazon EBS Provisioned IOPS SSD volumes is incorrect because this is just a block storage volume and not a full-fledged file system. Amazon EBS is primarily used as persistent block storage for EC2 instances.
Amazon Elastic File System is incorrect because it is stated in the scenario that the startup uses an Amazon EC2 Windows instance. Remember that Amazon EFS can only handle Linux workloads.
AWS Storage Gateway - File Gateway is incorrect. Although it can be used as a shared file system for Windows and can also be integrated with Microsoft Active Directory, Amazon FSx still has a higher level of throughput and IOPS compared with AWS Storage Gateway. Amazon FSX is capable of providing hundreds of thousands (or even millions) of IOPS.
References:
https://aws.amazon.com/fsx/windows/faqs/ https://docs.aws.amazon.com/fsx/latest/WindowsGuide/what- is.html Check out this Amazon FSx Cheat Sheet: https://tutorialsdojo.com/amazon-fsx/

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A company plans to host a web application in an Auto Scaling group of Amazon EC2 instances. The application will be used globally by users to upload and store several types of files. Based on user trends, files that are older than 2 years must be stored in a different storage class. The Solutions Architect of the company needs to create a cost-effective and scalable solution to store the old files yet still provide durability and high availability.
Which of the following approach can be used to fulfill this requirement? (Select TWO.)

• A.Use Amazon S3 and create a lifecycle policy that will move the objects to Amazon S3 Standard-IA after 2 years.
• B.Use Amazon EBS volumes to store the files. Configure the Amazon Data Lifecycle Manager (DLM) to schedule snapshots of the volumes after 2 years.
• C.Use a RAID 0 storage configuration that stripes multiple Amazon EBS volumes together to store the files. Configure the Amazon Data Lifecycle Manager (DLM) to schedule snapshots of the volumes after 2 years.
• D.Use Amazon EFS and create a lifecycle policy that will move the objects to Amazon EFS-IA after 2 years.
• E.Use Amazon S3 and create a lifecycle policy that will move the objects to Amazon S3 Glacier after 2 years.

Correct Answer: A,E

Amazon S3 stores data as objects within buckets. An object is a file and any optional metadata that describes the file. To store a file in Amazon S3, you upload it to a bucket. When you upload a file as an object, you can set permissions on the object and any metadata. Buckets are containers for objects. You can have one or more buckets. You can control access for each bucket, deciding who can create, delete, and list objects in it. You can also choose the geographical region where Amazon S3 will store the bucket and its contents and view access logs for the bucket and its objects.

To move a file to a different storage class, you can use Amazon S3 or Amazon EFS. Both services have lifecycle configurations. Take note that Amazon EFS can only transition a file to the IA storage class after 90 days. Since you need to move the files that are older than 2 years to a more cost-effective and scalable solution, you should use the Amazon S3 lifecycle configuration. With S3 lifecycle rules, you can transition files to S3 Standard IA or S3 Glacier. Using S3 Glacier expedited retrieval, you can quickly access your files within 1-5 minutes.
Hence, the correct answers are:
- Use Amazon S3 and create a lifecycle policy that will move the objects to Amazon S3 Glacier after 2 years.
- Use Amazon S3 and create a lifecycle policy that will move the objects to Amazon S3 Standard-IA after 2 years.
The option that says: Use Amazon EFS and create a lifecycle policy that will move the objects to Amazon EFS-IA after 2 years is incorrect because the maximum days for the EFS lifecycle policy is only 90 days. The requirement is to move the files that are older than 2 years or 730 days.
The option that says: Use Amazon EBS volumes to store the files. Configure the Amazon Data Lifecycle Manager (DLM) to schedule snapshots of the volumes after 2 years is incorrect because Amazon EBS costs more and is not as scalable as Amazon S3. It has some limitations when accessed by multiple EC2 instances. There are also huge costs involved in using the multi-attach feature on a Provisioned IOPS EBS volume to allow multiple EC2 instances to access the volume.
The option that says: Use a RAID 0 storage configuration that stripes multiple Amazon EBS volumes together to store the files. Configure the Amazon Data Lifecycle Manager (DLM) to schedule snapshots of the volumes after 2 years is incorrect because RAID (Redundant Array of Independent Disks) is just a data storage virtualization technology that combines multiple storage devices to achieve higher performance or data durability. RAID 0 can stripe multiple volumes together for greater I/O performance than you can achieve with a single volume. On the other hand, RAID 1 can mirror two volumes together to achieve on-instance redundancy.
References:
https://docs.aws.amazon.com/AmazonS3/latest/dev/object-lifecycle-mgmt.html
https://docs.aws.amazon.com/efs/latest/ug/lifecycle-management-efs.html
https://aws.amazon.com/s3/faqs/
Check out this Amazon S3 Cheat Sheet:
https://tutorialsdojo.com/amazon-s3/

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A company is planning to deploy a High Performance Computing (HPC) cluster in its VPC that requires a scalable, high-performance file system. The storage service must be optimized for efficient workload processing, and the data must be accessible via a fast and scalable file system interface. It should also work natively with Amazon S3 that enables you to easily process your S3 data with a high- performance POSIX interface.
Which of the following is the MOST suitable service that you should use for this scenario?

• A.Amazon FSx for Windows File Server
• B.Amazon FSx for Lustre
• C.Amazon Elastic Block Storage (EBS)
• D.Amazon Elastic File System (EFS)

Correct Answer: B

Amazon FSx for Lustre provides a high-performance file system optimized for fast processing of workloads such as machine learning, high performance computing (HPC), video processing, financial modeling, and electronic design automation (EDA). These workloads commonly require data to be presented via a fast and scalable file system interface, and typically have data sets stored on long-term data stores like Amazon S3.
Operating high-performance file systems typically require specialized expertise and administrative overhead, requiring you to provision storage servers and tune complex performance parameters. With Amazon FSx, you can launch and run a file system that provides sub-millisecond access to your data and allows you to read and write data at speeds of up to hundreds of gigabytes per second of throughput and millions of IOPS.
Amazon FSx for Lustre works natively with Amazon S3, making it easy for you to process cloud data sets with high-performance file systems. When linked to an S3 bucket, an FSx for Lustre file system transparently presents S3 objects as files and allows you to write results back to S3. You can also use FSx for Lustre as a standalone high-performance file system to burst your workloads from on-premises to the cloud. By copying on-premises data to an FSx for Lustre file system, you can make that data available for fast processing by compute instances running on AWS. With Amazon FSx, you pay for only the resources you use. There are no minimum commitments, upfront hardware or software costs, or additional fees.

For Windows-based applications, Amazon FSx provides fully managed Windows file servers with features and performance optimized for "lift-and-shift" business-critical application workloads including home directories (user shares), media workflows, and ERP applications. It is accessible from Windows and Linux instances via the SMB protocol. If you have Linux-based applications, Amazon EFS is a cloud- native fully managed file system that provides simple, scalable, elastic file storage accessible from Linux instances via the NFS protocol.
For compute-intensive and fast processing workloads, like high-performance computing (HPC), machine learning, EDA, and media processing, Amazon FSx for Lustre, provides a file system that's optimized for performance, with input and output stored on Amazon S3. Hence, the correct answer is: Amazon FSx for Lustre.
Amazon Elastic File System (EFS) is incorrect because although the EFS service can be used for HPC applications, it doesn't natively work with Amazon S3. It doesn't have the capability to easily process your S3 data with a high-performance POSIX interface, unlike Amazon FSx for Lustre.
Amazon FSx for Windows File Server is incorrect because although this service is a type of Amazon FSx, it does not work natively with Amazon S3. This service is a fully managed native Microsoft Windows file system that is primarily used for your Windows-based applications that require shared file storage to AWS.
Amazon Elastic Block Storage (EBS) is incorrect because this service is not a scalable, high- performance file system.
References:
https://aws.amazon.com/fsx/lustre/ https://aws.amazon.com/getting-started/use-cases/hpc/3/
Check out this Amazon FSx Cheat Sheet: https://tutorialsdojo.com/amazon-fsx/

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