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NEW QUESTION 51
A company wants to run a gaming application on Amazon EC2 instances that are part of an Auto Scaling group in the AWS Cloud. The application will transmit data by using UDP packets. The company wants to ensure that the application can scale out and in as traffic increases and decreases.
What should a solutions architect do to meet these requirements?
- A. Attach an Application Load Balancer to the Auto Scaling group.
- B. Attach a Network Load Balancer to the Auto Scaling group
- C. Deploy a NAT instance that is configured with port forwarding to the EC2 instances in the Auto Scaling group.
- D. Deploy an Amazon Route 53 record set with a weighted policy to route traffic appropriately
NEW QUESTION 52
A company plans to launch an Amazon EC2 instance in a private subnet for its internal corporate web portal. For security purposes, the EC2 instance must send data to Amazon DynamoDB and Amazon S3 via private endpoints that don’t pass through the public Internet.
Which of the following can meet the above requirements?
- A. Use VPC endpoints to route all access to S3 and DynamoDB via private endpoints.
- B. Use AWS VPN CloudHub to route all access to S3 and DynamoDB via private endpoints.
- C. Use AWS Direct Connect to route all access to S3 and DynamoDB via private endpoints.
- D. Use AWS Transit Gateway to route all access to S3 and DynamoDB via private endpoints.
A VPC endpoint allows you to privately connect your VPC to supported AWS and VPC endpoint services powered by AWS PrivateLink without needing an Internet gateway, NAT computer, VPN connection, or AWS Direct Connect connection. Instances in your VPC do not require public IP addresses to communicate with resources in the service. Traffic between your VPC and the other service does not leave the Amazon network.
In the scenario, you are asked to configure private endpoints to send data to Amazon DynamoDB and Amazon S3 without accessing the public Internet. Among the options given, VPC endpoint is the most suitable service that will allow you to use private IP addresses to access both DynamoDB and S3 without any exposure to the public internet.
Hence, the correct answer is the option that says: Use VPC endpoints to route all access to S3 and DynamoDB via private endpoints.
The option that says: Use AWS Transit Gateway to route all access in S3 and DynamoDB to a public endpoint is incorrect because a Transit Gateway simply connects your VPC and on-premises networks through a central hub. It acts as a cloud router that allows you to integrate multiple networks.
The option that says: Use AWS Direct Connect to route all access to S3 and DynamoDB via private endpoints is incorrect because AWS Direct Connect is primarily used to establish a dedicated network connection from your premises to AWS. The scenario didn’t say that the company is using its on- premises server or has a hybrid cloud architecture.
The option that says: Use AWS VPN CloudHub to route all access in S3 and DynamoDB to a private endpoint is incorrect because AWS VPN CloudHub is mainly used to provide secure communication between remote sites and not for creating a private endpoint to access Amazon S3 and DynamoDB within the Amazon network.
Check out this Amazon VPC Cheat Sheet:
NEW QUESTION 53
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 Elastic Block Storage (EBS)
- B. Amazon FSx for Windows File Server
- C. Amazon Elastic File System (EFS)
- D. Amazon FSx for Lustre
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.
Check out this Amazon FSx Cheat Sheet: https://tutorialsdojo.com/amazon-fsx/
NEW QUESTION 54
A leading media company has recently adopted a hybrid cloud architecture which requires them to migrate their application servers and databases in AWS. One of their applications requires a heterogeneous database migration in which you need to transform your on-premises Oracle database to PostgreSQL in AWS. This entails a schema and code transformation before the proper data migration starts.
Which of the following options is the most suitable approach to migrate the database in AWS?
- A. Use Amazon Neptune to convert the source schema and code to match that of the target database in RDS. Use the AWS Batch to effectively migrate the data from the source database to the target database in a batch process.
- B. First, use the AWS Schema Conversion Tool to convert the source schema and application code to match that of the target database, and then use the AWS Database Migration Service to migrate data from the source database to the target database.
- C. Configure a Launch Template that automatically converts the source schema and code to match that of the target database. Then, use the AWS Database Migration Service to migrate data from the source database to the target database.
- D. Heterogeneous database migration is not supported in AWS. You have to transform your database first to PostgreSQL and then migrate it to RDS.
AWS Database Migration Service helps you migrate databases to AWS quickly and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database. The AWS Database Migration Service can migrate your data to and from most widely used commercial and open-source databases.
AWS Database Migration Service can migrate your data to and from most of the widely used commercial and open source databases. It supports homogeneous migrations such as Oracle to Oracle, as well as heterogeneous migrations between different database platforms, such as Oracle to Amazon Aurora.
Migrations can be from on-premises databases to Amazon RDS or Amazon EC2, databases running on EC2 to RDS, or vice versa, as well as from one RDS database to another RDS database. It can also move data between SQL, NoSQL, and text based targets.
In heterogeneous database migrations the source and target databases engines are different, like in the case of Oracle to Amazon Aurora, Oracle to PostgreSQL, or Microsoft SQL Server to MySQL migrations.
In this case, the schema structure, data types, and database code of source and target databases can be quite different, requiring a schema and code transformation before the data migration starts. That makes heterogeneous migrations a two step process. First use the AWS Schema Conversion Tool to convert the source schema and code to match that of the target database, and then use the AWS Database Migration Service to migrate data from the source database to the target database. All the required data type conversions will automatically be done by the AWS Database Migration Service during the migration. The source database can be located in your own premises outside of AWS, running on an Amazon EC2 instance, or it can be an Amazon RDS database. The target can be a database in Amazon EC2 or Amazon RDS.
The option that says: Configure a Launch Template that automatically converts the source schema and code to match that of the target database. Then, use the AWS Database Migration Service to migrate data from the source database to the target database is incorrect because Launch templates are primarily used in EC2 to enable you to store launch parameters so that you do not have to specify them every time you launch an instance.
The option that says: Use Amazon Neptune to convert the source schema and code to match that of the target database in RDS. Use the AWS Batch to effectively migrate the data from the source database to the target database in a batch process is incorrect because Amazon Neptune is a fully-managed graph database service and not a suitable service to use to convert the source schema. AWS Batch is not a database migration service and hence, it is not suitable to be used in this scenario. You should use the AWS Schema Conversion Tool and AWS Database Migration Service instead.
The option that says: Heterogeneous database migration is not supported in AWS. You have to transform your database first to PostgreSQL and then migrate it to RDS is incorrect because heterogeneous database migration is supported in AWS using the Database Migration Service.
Check out this AWS Database Migration Service Cheat Sheet: https://tutorialsdojo.com/aws-database- migration-service/ AWS Migration Services Overview: https://www.youtube.com/watch?v=yqNBkFMnsL8
NEW QUESTION 55
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