Exam AWS Certified Solutions Architect - Associate SAA-C03 topic 1 question 113 discussion

A. Use AWS DataSync to move the data. Create a custom transformation job by using AWS Glue. - No BW available for DataSync, so "asap" will be weeks/months (?) B. Order an AWS Snowcone device to move the data. Deploy the transformation application to the device. - Snowcone will just store 14TB (SSD configuration). **C**. Order an AWS Snowball Edge Storage Optimized device. Copy the data to the device. Create a custom transformation job by using AWS Glue. - SnowBall can store 80TB (ok), takes around 1 week to move the device (faster than A), and AWS Glue allows to do ETL jobs. This is the answer. D. Order an AWS Snowball Edge Storage Optimized device that includes Amazon EC2 compute. Copy the data to the device. Create a new EC2 instance on AWS to run the transformation application. - Same as C, but the ETL job requires the deployment/configuration/maintenance of an EC2 instance, while Glue is serverless. This means D has more operational overhead than C.

Why C? This answer misses the part between SnowBall and AWS Glue. D at least provides a full-step solution that copies data in snowball device, and installs the custom application in device's EC2 to do the transformation job.

Ans D - but I suspect it should be Ans C because, as stated by 123jhlo (1yr 11mth ago), D is not serverless: "**C**. Order an AWS Snowball Edge Storage Optimized device. Copy the data to the device. Create a custom transformation job by using AWS Glue. - SnowBall can store 80TB (ok), takes around 1 week to move the device (faster than A), and AWS Glue allows to do ETL jobs." D. Order an AWS Snowball Edge Storage Optimized device that includes Amazon EC2 compute. Copy the data to the device. Create a new EC2 instance on AWS to run the transformation application. - Same as C, but the ETL job requires the deployment/configuration/maintenance of an EC2 instance, while Glue is serverless. This means D has more operational overhead than C."

A and D are wrong. D is the correct answer. Why not C: AWS Snowball Edge is a physical device designed for transferring large amounts of data to and from AWS. It includes some compute capabilities, such as running AWS Lambda functions, AWS IoT Greengrass, and EC2 instances, but it does not support AWS Glue. AWS Glue is a fully managed ETL (Extract, Transform, Load) service that runs within the AWS Cloud. It is designed to work with data stored in AWS services like Amazon S3, Amazon RDS, and Amazon Redshift, among others. AWS Glue is not available on edge devices like Snowball Edge.

gotta be C surely..... LEAST operational overhead. EC2 = operational overhead. AWS Glue = managed service with transformation capabilities.

The q states that the custom job must remain, so glue is out. Seems like D is the only option as DataSync needs bandwidth.

Using an EC2 instance instead of a managed service like AWS Glue will include more operational overhead for the organization.

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The answer is D because of the following key points 1. A custom application in the company’s data center runs a weekly data transformation job. Which means that the company already has an application that runs the transformation. 2. A solutions architect must transfer the data and must configure the transformation job to continue to run in the AWS Cloud. This shows that the only responsibility of the architect is to transfer the data and configure the existing application to run on the EC2 the architect is going to deploy.

A: Cannot be done because no bandwidth B: Snowcone is probably to small D: Doable by EC2 is overhead for transformation when Glue is an option C: Is correct as Snowball Edge Storage Optimised device is good for storage and Glue can transform once the data is available

C best suit for: ETL jobs with LEAST operational overhead. For my understanding, we need here to avoir operation or maintenance burden of the solution

we use snowball to copy 50 PB "The company plans to pause the application until the data transfer is complete " and least over head " hence C would be reinventing the weel

which is faster? - setup a glue cluster and adapt it to do the same analytical stuff as the original app - simpley run the same app in an EC2 instance?

How are we going to run the custom application using glue? that means more time to adapt the process instead of just running the app in ec2

Not A. AWS DataSync requires an internet connection & the question states no available bandwidth Not B. SnowCone only has a max of 14 TB with an SSD, and the data is 50 TB Not C. Snowball Edge doesn't support Glue Supported services: https://docs.aws.amazon.com/snowball/latest/developer-guide/whatisedge.html So the answer must be D, as Snowball Edge Storage Optimized does support EC2 & can store 80 TB for the version that support compute resources

Snowball Edge has storage and compute capabilities, can be used to support workload in offline locations. Technically option D will work but with the overhead of EC2, negating the requirement for LEAST ops.

The Snowball Edge Storage Optimized device allows transferring a large amount of data without using network bandwidth. Once the data is copied to the Snowball, AWS Glue can be used to create a custom ETL job to transform the data, avoiding the need to reconfigure the existing on-premises application. This meets the requirements to transfer the data with minimal operational overhead and configure the data transformation job to run in AWS