Building Highly Scalable Retail Order Management Systems with Serverless

1. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Bastien Leblanc
Solutions Architect, Amazon Web Services
Charlie Wilkinson
Head of Architecture, River Island
Building Highly Scalable
Retail Order Management Systems
with Serverless

2. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
What to expect from this session?
Serverless introduction & typical use cases
Current architecture challenges
Architecture Principles for Order Management
Feedbacks and future thoughts
Q&A

3. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Serverless

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Serverless Means …
No servers to provision
or manage
Scales with usage
Never pay for idle Built-in availability and
fault tolerance

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Serverless Applications
Services (anything)
Changes in
data state
Requests to
endpoints
Events on a
stream
Event source AWS Lambda function
Node.js
Python
Java
C#
Go

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Serverless Orchestration: AWS Step Functions
Productivity, Agility, Resilience

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Amazon DynamoDB: Managed NoSQL in the Cloud
Fast, Consistent Performance
Highly Scalable
Flexible
Fine-grained Access Control
Fully Managed

8. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Serverless Application Use Cases
E-commerce
• Static
websites
• Complex web
apps
• Packages for
Flask and
Express
Data
processing
• Real time
• MapReduce
• Batch
• Machine
learning
inference
Chatbots /
Alexa
• Powering
chatbot logic
• Powering
voice-enabled
apps
• Alexa
Skills Kit
Backend
Systems
• Apps and
services
(Order,
Supply Chain)
• Mobile
• IoT
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AI/ML
• Powering
Visual
Analytics
platform

9. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

10. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
History lesson:
Hairball architecture
WMS
OMS
Core
Merchandising
Website
New orders
Dispatch result
New orders
Payment provider
Authorisation
Payment capture

11. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Batch processing: Because 3am callouts are fun!
• Peaky CPU usage
• One dodgy input kills the batch
• One dead batch blocks the rest
• One broken step kills the chain
• Data is not timely

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Architectural Principles

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Surface business
events
Easy, timely access
to master data
A
G
I
L
I
T
Y
Guiding objectives

14. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Key architectural principles
Breakdown the
existing monolith
Decouple our core
systems
Reduce dependency
on batch jobs
Expose our business
events
Make our data easily
accessible
Operational
simplicity

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Case Study: Improving the way we
process our orders

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Microservices order pipeline

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Asynchronous: Order validation microservice

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Synchronous: Order payment microservice

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Make our data easily accessible - Data lake

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Monitoring

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Q&A

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THANK YOU !