In this session, learn how to apply DevOps, microservices, and serverless to innovate faster at scale. Discover how we achieved over sixty million deployments per year, and benefit from the lessons we learned while building modern apps for Amazon. We cover the transition from a monolithic application to event-driven serverless microservices and dive into the reasons why more and more customers choose the serverless operational model. We describe how this works in practice by leveraging AWS Lambda, AWS Step Functions, AWS Fargate, Amazon API Gateway, Amazon SNS, Amazon SQS, and the entire serverless portfolio.

1. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
A culture of rapid innovation with
DevOps, microservices, and serverless
M A D 2 0 1
Chris Munns
Principal developer advocate–Serverless
AWS

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About me
Chris Munns - munns@amazon.com, @chrismunns
• Principal Developer Advocate – Serverless
• New Yorker
Previously:
• AWS Business Development Manager, DevOps, July 2015–Feb. 2017
• AWS Solutions Architect, Nov. 2011–Dec. 2014
• Formerly on operations teams @Etsy and @Meetup
• Little time at a hedge fund, Xerox, and a few other startups
• Rochester Institute of Technology: Applied Networking and Systems Administration
’05
• Internet infrastructure geek

3. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
“We want to be a large company that’s also an invention machine. We want to
combine the extraordinary customer-serving capabilities that are enabled by
size with the speed of movement, nimbleness, and risk-acceptance mentality
normally associated with entrepreneurial startups.”
Jeff Bezos
CEO, Amazon

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ListenIterate
Experiment
Innovation
flywheel
Experiments power the engine of rapid innovation

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Development transformation at Amazon: 2001–2002
Monolithic application
+ teams
2001
Lesson learned: Decompose for agility
2002
Microservices
+ two pizza teams

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Changes to the team structure

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Full ownership
Full accountability
DevOps
Focused innovation
Two-pizza teams

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Deployment at scale
Thousands of
teams
Microservices CI/CD Serverless
> 60 million deployments a year*

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New services and features released per year
0
500
1000
1500
2000
2500
2011 2012 2013 2014 2015 2016 2017 2018

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Changes to the architectural patterns

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When the impact of change is small,
release velocity can increase
Monolith
Does everything
Microservices
Does one thing

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When a small team can make a change,
release velocity can increase
Multiple teams
Loosely connected
One team
Focus and ownership

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Microservice
API
API
Microservice
Microservice
Event
API
Microservice
Event
API
Microservice
Application
Mobile client
Client
Internet of
Things (IoT)
Persistence Persistence

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APIs are the front door of microservices

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APIs are the “hardened contract” between
teams

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Manage APIs with Amazon API Gateway
Mobile apps
Websites
Services
Internet Amazon
CloudFront
Amazon CloudWatch
monitoring
API
Gateway
cache
Any other
AWS service
All publicly
accessible
endpoints
Lambda
functions
Endpoints
in your VPC
Regional API endpoints
AWS Lambda
functions
Endpoints on Amazon
Elastic Compute
Cloud (Amazon EC2)
Your virtual private
cloud (VPC)
Amazon Web Services (AWS)

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Event-driven architectures

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Decouple state from code using
messaging

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Decouple state from code using messaging
Queues
Simple
Fully managed
Any volume
Pub/sub
Simple
Fully managed
Flexible
Amazon Simple
Queue Service
(Amazon SQS)
Amazon Simple
Notification Service
(Amazon SNS)
Messaging
Synchronization
Rapid
Fully managed
Real time
Amazon CloudWatch
Events

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Microservice
Event
Event
Microservice
Microservice
Event
API
Microservice
Event
API
Microservice
Application
Mobile client
Client
IoT
Persistence Persistence
Queue
Topic

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Amazon SNS
“CheckoutEventsTopic”
Event storage and backup pipeline
Event search and analytics pipeline
Event replay pipeline
Checkout event processing pipeline
filtered orders (amount >= $100)
Orders to replay
All
orders
AWS Cloud
Ecommerce
users
Internet
Lambda
“CheckoutFunction”
Amazon SQS
“CheckoutQueue”
Lambda
“CheckoutFunction”
Amazon DynamoDB
“CheckoutTable”
Event-driven architecture

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Data-stream-based architectures

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Stream processing
Ingest
Data streams
Data processing
Real time
Data store
Microservices
Performance at scale
Fast and flexible
Amazon Kinesis
data streams
DynamoDB
Data-stream capture

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Track status of data
and execution
Remove redundant
code
Build workflows to orchestrate everything

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Simpler integration, less code
With serverless
polling
With new
service integration
Start
End
Lambda
functions
Start
End
No
Lambda
functions

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Object storage
Durable and scalable
Comprehensive security
Query-in-place
AWS serverless storage and database options
Non-relational
Performance at scale
Fully managed
Enterprise-ready
Relational
Fully managed
High performance
Cost effective

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Cloud-native architectures are small
pieces, loosely joined

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Changes to the operational model

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AWS operational responsibility models
On premises Cloud
Less More
Compute Virtual machine
Amazon EC2 AWS Elastic Beanstalk LambdaAWS Fargate
Databases MySQL MySQL on Amazon EC2
Amazon RDS MySQL Amazon RDS Aurora Aurora Serverless DynamoDB
Storage Storage
Amazon S3
Messaging Enterprise service
buses (ESBs) Amazon MQ Kinesis Amazon SQS/Amazon SNS
Analytics
Apache Hadoop Hadoop on
Amazon EC2
Amazon EMR Amazon Elasticsearch Service Amazon Athena

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What is serverless?
No infrastructure management Automatic scaling
Pay for value Highly available and secure

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Lambda Fargate
API Gateway
Amazon
SNS
Amazon
SQS
AWS
Step Functions
Compute
Data stores
Integration
Aurora ServerlessAmazon S3 DynamoDB
AWS
AppSync

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Serverless compute engine
for containers
Long-running
Bring existing code
Fully managed orchestration
Fargate
Let’s focus on compute for now
Serverless event-driven
code execution
Short-lived
All language runtimes
Data-source integrations
Lambda

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Comparison of operational responsibility
Lambda
Serverless functions
Fargate
Serverless containers
Amazon ECS/Amazon EKS
Container-management as a service
Amazon EC2
Infrastructure-as-a-service
More opinionated
Less opinionated
AWS manages Customer manages
• Data source integrations
• Physical hardware, software, networking,
and facilities
• Provisioning
• Application code
• Container orchestration, provisioning
• Cluster scaling
• Physical hardware, host OS/kernel,
networking, and facilities
• Application code
• Data source integrations
• Security config and updates, network config,
management tasks
• Container orchestration control plane
• Physical hardware software, networking,
and facilities
• Application code
• Data source integrations
• Work clusters
• Security config and updates, network config,
firewall, management tasks
• Physical hardware software,
networking, and facilities
• Application code
• Data source integrations
• Scaling
• Security config and updates, network config,
management tasks
• Provisioning, managing scaling and
patching of servers

34. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Making development easier with Lambda
Accessible for
all developers
Enable new
application patterns
Greater
productivity
Support for all runtimes
with Lambda Layers and Runtime API
ISO, PCI, HIPAA, SOC, GDPR,
and FedRamp compliances
15-minute functions
Amazon SQS for Lambda
Automatic load balancing for Lambda
Support for Kinesis Data Streams Enhanced Fan-Out
and HTTP/2
Toolkits for popular integrated
development environments (IDEs):
VSCode, IntelliJ, and PyCharm
Simplified deployment
with nested apps

35. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Serverless containers with Fargate
Bring existing code Containers as first-class
primitive
Production ready
No changes required of existing code,
works with existing workflows and
microservices built on Amazon ECS
Time- and event-based scheduling, network
integration, individually metered and billed;
native service discovery
ISO-, PCI-, HIPAA-, SOC-compliant.
Launch tens or tens of thousands of
containers in seconds in
nine global regions
(+ seven in 2018)

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Changes to the delivery of software

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Monolith development lifecycle
MonitorReleaseTestBuild
Developers
Delivery pipelines
Services

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Microservice development lifecycle
Developers Services
MonitorReleaseTestBuild
Delivery pipelines
MonitorReleaseTestBuild
MonitorReleaseTestBuild
MonitorReleaseTestBuild
MonitorReleaseTestBuild
MonitorReleaseTestBuild

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How Amazon
does DevOps
(microservices, two pizza teams)
(governance, templates)

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We released the AWS developer tools for continuous
integration and continuous delivery (CI/CD)
AWS CodeBuild +
third party
AWS CodeCommit AWS CodeBuild AWS CodeDeploy AWS X-Ray
Source Build Test Deploy Monitor
AWS CodePipeline

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X-Ray is built for modern applications
Identify customer
impact
Support for serverlessMap all services and
ephemeral resources
Follow end-to-end
interactions

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Author and debug Lambda applications on AWS using
your favorite IDEs
Python, Node Python Java
Developer
preview
.NET, Node

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Developer previewAWS cloud development kit
CDK application AWS
CloudFormation
template
Stack(s)
Construct Construct
Resources
AWS
CloudFormation
Amazon SQS Lambda Amazon S3
bucket
DynamoDB

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Conclusion

45. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Increase
customer
value
Build better
products
Innovate
more often
Release
features
faster
Focus on
business
logic
Decouple
software
systems
Our goal is to automate and abstract away as much as is possible so customers can focus on
building applications for their business
We are witnessing a paradigm shift

46. Thank you!
S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Chris Munns
munns@amazon.com
@chrismunns