Today’s retail customers want to set the rules on how and when they buy, receive, and return their product. But many retailers are struggling to unify their sales channels using existing legacy e-commerce software stacks. To consistently serve customers across retail channels, retailers must adopt a modern architecture that is elastic, cost effective, and based on loosely coupled application services. In this session, we dive deep into how retailers can leverage serverless architectures using Amazon API Gateway, AWS Lambda, and Amazon DynamoDB. Learn how Amazon Fresh quickly responded to customer feedback on the Totes Pickup feature, developing a cost-effective and scalable self-service serverless application to deliver a 1-click experience for the customer, while providing faster insights back to the business.

1. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS re:INVENT
Rapidly Respond to Demanding Retail
Customers with the Same Serverless
Architecture That Powers Amazon Fresh
G o w r i B a l a s u b r a m a n i a n , S r . S o l u t i o n s A r c h i t e c t , A W S
F e r n a n d o D i n g l e r , S o f t w a r e E n g i n e e r , A m a z o n F r e s h
N o v e m b e r 2 7 , 2 0 1 7
R E T 3 0 4

2. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
What to expect from this session
• Retail industry’s use cases on AWS
• Introduction of serverless architectures
• Overview of AWS Lambda, Amazon API Gateway and Amazon
DynamoDB services
• - Serverless architecture

3. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Retail Workloads on AWS—Key Benefits
Develop applications faster with focus on features that differentiate your business
Scale on demand to handle seasonal peaks or variance (for example, for Black
Friday)
Reduce overall IT costs—CAPEX to OPEX model, further minimize operational cost
via AWS managed services
Reach customers in regions across the globe
Implement agile approach to data and analytics

4. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Made.com provides a website that links home-
furnishings designers directly to consumers.
We broke our sales record
two weeks into the month-
long sale thanks to
disruption-free service from
AWS.
Jonathan Howell
Chief Technology Officer
”
“
Customers
Brooks Brothers is a leading U.S. retailer of
fashion and accessories.
Using AWS ... we can be
more nimble, which opens up
many more possibilities for
our business.
Sahal Laher
Executive Vice President and CEO,
”
“

5. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Retailer's focus areas
E-commerce
• Digital commerce stacks (SAP Hybris, IBM Webshpere Commerce, etc.)
• Omni-channel customer interactions (Mobile backend, web applications)
Big data/analytics
• Single view of the customer driven by omni-channel
• Guided selling/product recommendation
Digital customer experience
• Voice/chat apps—e.g., digital shopping assistant
• Call-center automation—e.g., product returns
• IoT (Internet of Things) for in-store and operations automation

6. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Nordstrom gives personalized style recommendations
in seconds
.
- Keith Homewood
cloud product owner, Nordstrom
”
“ • Nordstrom Recommendation is the online version of
a stylist. It can analyze and deliver personalized
recommendations in seconds
• Going all-in on AWS has resulted in reducing costs
by 2X
• Continuous delivery allows Nordstrom to deliver
multiple production launches a day in a single
application
• Can now create a personalized recommendation in
seconds, in what used to take 15-20 minutes of
processing
Nordstrom
AWS allows us to truly be
customer-focused and to get out
of operational details and
problems.
https://aws.amazon.com/solutions/case-studies/nordstrom/

7. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Virtual servers
in the cloud
(Amazon EC2)
Containers
in the cloud
(Amazon ECS)
Serverless with
the cloud
Evolving to serverless
Growing number of retail customers are using serverless

8. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Cost-effective
and efficient
No infrastructure
to manage
Pay only for what you use
Continuous
scaling
Productivity-focused compute platform to build powerful, dynamic, modular applications
in the cloud
Automatically scales
to the workload
Focus on business logic
Why serverless platform?
1 2 3

9. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Components of serverless architectures
AWS Lambda
Trigger-based Lambda functions
Streaming data
Amazon Kinesis
Amazon DynamoDB Streams
APIs
Amazon API Gateway
Event sources
Amazon CloudWatch
Amazon S3
AWS Config
Amazon SNS
Data Persistence
Amazon DynamoDB
AWS Elasticsearch Service
Amazon S3
Integration Points
Amazon VPC resources
AWS service APIs
Third-party services

10. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Serverless web/mobile applications
Internet
Mobile apps
AWS Lambda
AWS
API Gateway
Amazon
DynamoDB
Web browser

11. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Working with AWS Lambda
Event source Function Services (anything)
Changes in
data state
Requests to
endpoints
Changes in
resource state
Node
Python
Java
C#
… more coming soon

12. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon S3 Amazon
DynamoDB
Amazon
Kinesis
AWS
CloudFormatio
n
AWS
CloudTrail
Amazon
CloudWatch
Amazon SNSAmazon
SES
Amazon
API Gateway
Amazon
Cognito
Amazon
Alexa
Cron events
Data stores Endpoints
Configuration repositories Event/message services
Event sources that trigger AWS Lambda
… and the list will continue to grow!
AWS
CodeCommit
AWS IoT

13. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS Lambda programming model
Bring your own code
• Node.js, Java, Python, C#
• Bring your own libraries
• Environment variables
Simple resource model
• Select power rating from
128 MB to 1.5 GB
• CPU and network allocated
proportionately
Stateless
• Persist data using Amazon
DynamoDB or Amazon S3
• No affinity to
infrastructure (can’t “log in
to the box”)
Monitoring and logging
• Built-in metrics for
requests, errors, latency,
and throttles
• Built-in logs in Amazon
CloudWatch logs

14. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
AWS Lambda deployment options
MonitorProvisionDeployTestBuildCode
Amazon
CloudWatch
AWS CloudFormation
Code
Commit
CodePipeline
CodeBuild
X-ray

15. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
What about the front end….

16. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Benefits of Amazon API Gateway
Create a unified
API front end for
multiple micro
services
DDoS protection
and throttling for
backend systems
Authenticate and
authorize requests

17. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Working with Amazon API Gateway
Publish
Maintain MonitorSecure
Create Configure

18. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
API call flow
Interne
t
Mobile
apps
Websites
Partner
Services
AWS Lambda
functions
API
Gateway
response
cache
Endpoints on
Amazon EC2
Any publicly
accessible
endpoint
Amazon
CloudWatch
Amazon
CloudFront
API
Gateway

19. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Lets talk about data…

20. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Relational vs. NoSQL?
Optimized for storage Optimized for compute
Normalized/relational
Denormalized/hierarchical
(flexible schema)
Case-specific queries Instantiated views
Scale vertically Scale horizontally
Good for OLAP Built for OLTP at scale
SQL NoSQL

21. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Highly available
and durable
Consistently fast at any scale Fully managed
Secure
Integrates with AWS Lambda,
Amazon Redshift, and more
Benefits of Amazon DynamoDB
Cost-effective

22. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Scalability Performance Security Manageability Developer platform
• Millions of
reads/sec from
single DAX cluster
• Unlimited items
and storage
• Managed
Auto Scaling
• Consistent,
single-digit
millisecond latency
• Microsecond
response times
with
DynamoDB
Accelerator
(DAX)
• Monitor with
CloudWatch metrics
and logging with
CloudTrail
• Client-side
encryption library
• Secure, private VPC
endpoints
• Pay-as-you-grow for
capacity and storage
independently
• Track table-level
spending with Tagging
• Purge data
automatically
(Time To Live)
• Event-driven programming
with triggers and Lambda
• Advanced analytics with
Amazon EMR and Amazon
Redshift
• Full-text query support
with Amazon Elasticsearch
Service
DynamoDB features at a glance

23. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
serverless architecture

24. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

25. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

26. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

27. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

28. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Old process
Customer
Customer
service
1. Calls customer service
2. Manually raises a ticket
to the transportation team
Pickup
specialist
3. Schedules a pickup at
customer’s address
4. Driver picks up totes

29. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
A better solution
Customer

30. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
A better solution

31. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Requirements
Time to market Managed infrastructure Cost-effective

32. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Architecture overview
Amazon S3
DynamoDB
API Gateway Lambda
functions

33. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Use cases
Totes
pickup service
1. Verify eligibility
2. Schedule pickup request
3. Reporting
Is customer eligible to
request a totes pickup?
Schedule a totes pickup
at the provided address
Generate periodic reports
for business intelligence

34. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Use cases
Totes
pickup service
1. Verify eligibility
2. Schedule pickup request
3. Reporting
Is customer eligible to
request a totes pickup?
Schedule a totes pickup
at the provided address
Generate periodic reports
for business intelligence

35. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Use case 1—verify eligibility
Fetch the last
customer
order
Is it
delivered?
Has
customer
already
requested a
pickup?
No Yes
Amazon internal systems
Is eligible

36. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Use cases
Totes
pickup service
1. Verify eligibility
2. Schedule pickup request
3. Reporting
Is customer eligible to
request a totes pickup?
Schedule a totes pickup
at the provided address
Generate periodic reports
for business intelligence

37. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Use case 2—schedule pickup request
API
DynamoDBTotes pickup
Transportation
systems
Save request
Schedule pickup
notification
Request
pickup
• Totes count
• Associated delivery address
• Delivery instructions
• Transportation system

38. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Use cases
Totes
pickup service
1. Verify eligibility
2. Schedule pickup request
3. Reporting
Is customer eligible to
request a totes pickup?
Schedule a totes pickup
at the provided address
Generate periodic reports
for business intelligence

39. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Use case 3—reporting
DynamoDB
Amazon
S3 bucket
Scheduled execution
Asynchronous
Generate report
List of requests
in the day
Amazon
SES
1. Query pickup requests
3. Send email
Amazon CloudWatch 2. Save report

40. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Totes pickup—the data layer
DynamoDB
Access patterns
1. Get pickup requests by CustomerId and Address
2. Get all pickup requests by CustomerId
3. Query pickup requests for a given time range
and…
Flexible schema with JSON document

41. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
DynamoDB design
Sample Item

42. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
• Good partition key (uniformity)
• Allows for quick lookup of
pickup requests for a given
customer at a given address
DynamoDB design
• Allows for multiple requests
to be placed for a customer at
a given address, but at
different times

43. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Global secondary indexes
Get all pickup requests
by CustomerId
2
Get pickup requests for a
given time range
1
1
2

44. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
DynamoDB throughput capacity
• 1 Read Capacity Unit (RCU) =
one 4 KB strongly consistent
read or two 4KB eventually
consistent reads
• 1 Write Capacity Unit (WCU) =
One 1 KB write

45. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
How we choose the right capacity
Estimated load/trafficMeasured item sizeIdentified
access patterns
1 2 3
Reads and writes
Average size in KB for
each item in DynamoDB
Totes pickup requests
per second

46. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
For example, write capacity
10 TPS
Totes pickup requests
per second
3 KB
Item size
=
Min: 30 units
Max: 60 units
With Auto Scaling
1 write unit = 1 KB per second
Doing the math
10 x 3 = 30 units per second

47. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
DynamoDB monitoring
Metrics Statistics Sample Alarm
Throttle requests Count Count > 10 in 5 minutes
Consumed read capacity units Sum Sum > 8,000 in 1 minute
Consumed write capacity units Sum Sum > 8,000 in 1 minute
• Monitoring needs to be enabled for table and GSIs separately
• Throttle requests can be monitored at the API level (i.e. Get, Put)

48. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Best practices we followed on DynamoDB
 Chose a partition key that provided an even data distribution
 Used global secondary indexes (GSI) to satisfy all of the data access requirements
 Estimated throughput capacity based on the workload and item size
 Handled sporadic traffic spikes using DynamoDB Auto Scaling
 Used DocumentClient to handle JSON objects and retries on throttle exceptions
 CloudWatch monitoring

49. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Totes pickup—the compute layer
Lambda function Timeout Memory Execution Runtime
tote-pickup-get-recent-requests 10 sec 512 MB Sync Node.js 6.10
tote-pickup-find-eligibility 10 sec 512 MB Sync Node.js 6.10
tote-pickup-email-report 10 sec 512 MB Sync Node.js 6.10
tote-pickup-daily-requests-report 5 min 1,536 MB Async Node.js 6.10
tote-pickup-report-by-region 5 min 1,536 MB Async Node.js 6.10

50. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Totes pickup—Lambda execution model
Amazon
API Gateway
/request
Daily report
CloudWatch
AsynchronousSynchronous

51. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Lambda monitoring
Metrics Statistics Sample Alarm
Errors Count Count > 5 in 10 minutes
Invocation duration Average Average > 750 in 15 minutes
Throttled invocations Count Count > 5 in 10 minutes

52. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Best practices we followed on Lambda
Design
 One function per use case vs. monolithic large Lambda function
 Separated the Lambda handler (entry point) from the core logic
 Used environment variables to pass operational parameters
 Avoided placing Lambdas in VPC if not needed

53. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Best practices we followed on Lambda
Operations
 Set CloudWatch alarms on throttled invocations and errors
 Used dead letter queues to handle errors on async invocations
 Were aware of the concurrency limits; limits apply per account per region
 Leveraged CloudWatch events for scheduled invocations

54. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Totes pickup—the API layer
• Smooth integration with Lambda
• Secure (https)
• Track requests per client with API Keys
• Stages
• Throttling and usage plans

55. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Provisioning & management
CloudFormation to create and update:
IAM roles, DynamoDB tables, Lambda functions, API endpoints, Amazon S3
Buckets

56. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Results
Savings per SDE
per week in
operational work
Development effort
with a small team
Savings per month
in customer service
Hundreds
of hours
3.7 hours
Better customer
experience
3 Months
3.7 hours

57. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
THANK YOU! Please remember to fill
out your surveys

58. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Related sessions
SRV305—What's New in Serverless
ARC406—Replacing 100s of DBs with 1 or: How Amazon’s Order Processing Workflow System
Learned to Stop Worrying and Love its Scale
DAT326—How DynamoDB Powered Amazon's Prime Day 2017
ABD321—Don’t Wait Until Tomorrow: How to Use Streaming Data to Gain Real-time Insights
into Your Business
ARC307—From Monolithic to Microservices: Evolving Architecture Patterns in the Cloud