I got the opportunity to put AWS skills related to various services like Amazon Rekognition, AWS Lambda, S3, IAM roles, Cloudwatch, EC2 etc. via interactive team-based learning exercise I was part of a team with four members and it was an extremely fun way to run collaboratively. AWS Loft team introduced us to imaginary company “Unicorn.Rentals” and we were told to transform its sub-optimal application architecture to robust, resilent & scalable architecture.

1. my experience at
AWS Loft, New York
on 15th Oct 2019

2. Background
• I got the opportunity to put AWS skills related to
various services like Amazon Rekognition, AWS
Lambda, S3, IAM roles, Cloudwatch, EC2 etc. via
interactive team-based learning exercise
• I was part of a team with four members and it was
an extremely fun way to run collaboratively.
• AWS Loft team introduced us to imaginary
company “Unicorn.Rentals” and we were told to
transform its sub-optimal application architecture
to robust, resilent & scalable architecture.

3. at stake

4. S3 Learnings
• Hosted “Unicorn.Rentals” static
website on Amazon S3
• Added S3 bucket policy grant
cross-account permissions
https://s3.console.aws.amazon.com/s3/home?region=us-east-2#

5. ALB Learnings
• Used Path-based routing with
Application load balancer
• We routed general requests to
one target group and requests
to “images” to another target
group
• We did this by creating a
listener with rules to forward
“general” or “images”(/img/*)
requests based on the URL path
https://docs.aws.amazon.com/elasticloadbalancing/latest/userguide/what-is-load-
balancing.html?icmpid=docs_elbv2_console

6. Rekognition Learnings
• Facial recognition for locating “Missing CEO” using
Amazon Rekognition (Ironically, “Missing CEO” is
travelling around and updating S3 with his images via
another IAM account”)
• We needed to create “collection”, which is basically a
group of people you want recognition to recognize.
• We created Collection using AWS CLI command
aws rekognition create-collection
--collection-id “collectionname”
https://aws.amazon.com/rekognition/

7. Lambda Learnings
• AWS Loft team provided us with starter code(AWS
Lambda functions) for populating Rekognition
collection and prepopulated S3 bucket containing
training images
• Remember we need to train rekognition for
recognizing “Missing CEO” picture
• And another starter code for iterating through the
faces found in the submitted image (told you
“Missing CEO” is putting images into S3 while moving
around)
https://aws.amazon.com/lambda/

8. SNS Learnings
send_sns(return_message)
• “We’ve found our CEO!!
Hurrah!”
else
• We need to signal back
that our CEO wasn’t in
the picture
https://aws.amazon.com/sns/

9. My Team:
Synergy
(Final Position: 5th)