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Serverless	for	Developers
Danilo	Poccia,	Technical	Evangelist
@danilop
Danilo Poccia
W
ith AWS Lambda, you write your code and upload it to
the AWS cloud. AWS Lambda responds to the events
triggered by your application or your users, and auto-
matically manages the underlying computer resources for you.
Back-end tasks like analyzing a new document or processing
requests from a mobile app are easy to implement. Your ap-
plication is divided into small functions, leading naturally to a
reactive architecture and the adoption of microservices.
AWS Lambda in Action is an example-driven tutorial that
teaches you how to build applications that use an event-driven
approach on the back-end. Starting with an overview of AWS
Lambda, the book moves on to show you common examples
and patterns that you can use to call Lambda functions from
a web page or a mobile app. The second part of the book puts
these smaller examples together to build larger applications.
By the end, you’ll be ready to create applications that take
advantage of the high availability, security, performance, and
scalability of AWS.
What’s Inside
● Create a simple API
● Create an event-driven media sharing application
● Secure access to your application in the cloud
● Use functions from different clients like web pages
or mobile apps
● Connect your application with external services
Requires basic knowledge of JavaScript. Some examples are
also provided in Python. No AWS experience is assumed.
Danilo Poccia is a technical evangelist at Amazon Web Services
and a frequent speaker at public events and workshops.
To download their free eBook in PDF, ePub, and Kindle formats, owners
of this book should visit www.manning.com/books/aws-lambda-in-action
$49.99 / Can $57.99 [INCLUDING eBOOK]
AWSLambdaINACTION
SOFTWARE DEVELOPMENT/CLOUD
Danilo
Poccia
M A N N I N G
AWSLambdaINACTION
MANNING
“Clear and concise …
the code samples are as well
structured as the writing.
”—From the Foreword by
James Governor, RedMonk
“A superb guide to an
important aspect of AWS.
”—Ben Leibert, VillageReach
“Step-by-step examples
and clear prose make this
the go-to book for
AWS Lambda!.
”—Dan Kacenjar, Wolters Kluwer
“Like Lambda itself, this
book is easy to follow, concise,
and very functional.
”—Christopher Haupt, New Relic
M A N N I N G
SEE INSERT
Danilo Poccia
FOREWORD BY James Governor
Event-driven serverless applications
Function
<demo>
greetingsOnDemand
</demo>
Function
Function
Client Application
Function
invoke
Client Application
Function
Database
Files
invoke
read/write
Client Application
Function2
Database
Files
Function1
Function3
invoke
event trigger
event trigger
read/write
Business LogicClient Application
Function2
Database
Files
Function1
Function3
invoke
event trigger
event trigger
read/write
Data PersistenceBusiness LogicClient Application
Function2
Database
Files
Function1
Function3
invoke
event trigger
event trigger
read/write
Data PersistenceBusiness Logic
Client
Application
FunctionsFunctionsFunctions RepositoriesRepositoriesRepositoriesAPI read/write
event trigger
Data PersistenceBusiness Logic
Client
Application
FunctionsFunctionsFunctions RepositoriesRepositoriesRepositoriesAPI read/write
event trigger
read/write
Data PersistenceBusiness Logic
Client
Application
FunctionsFunctionsFunctions
API
Gateway
RepositoriesRepositoriesRepositoriesAPI read/write
event trigger
read/write
Request – Input Format
{
"resource": "Resource path",
"path": "Path parameter",
"httpMethod": "Incoming request's method name",
"headers": { Incoming request headers },
"queryStringParameters": { Query string parameters },
"pathParameters": { Path parameters },
"stageVariables": { Applicable stage variables },
"requestContext": { Request context, including authorizer-returned key-value pairs },
"body": "A JSON string of the request payload",
"isBase64Encoded": "A boolean flag to indicate if the applicable request payload is Base64-encode"
}
Response – Output Format
{
"statusCode": httpStatusCode,
"headers": { "headerName": "headerValue", ... },
"body": "...”
}
Lambda
Function
Amazon API
Gateway
<demo>
greetingsAPI
</demo>
How do I start?
No Servers
to Manage
Continuous
Scaling
Subsecond
Metering
AWS Lambda
1 Million requests
per month
400,000 GB-seconds
per month
Free Tier
https://github.com/awslabs/chalice
$ pip install chalice
$ chalice new-project helloworld && cd helloworld
$ cat app.py
from chalice import Chalice
app = Chalice(app_name="helloworld")
@app.route("/")
def index():
return {"hello": "world"}
$ chalice deploy
...
Your application is available at: https://endpoint/dev
$ curl https://endpoint/dev
{"hello": "world"}
<demo>
chalice
</demo>
https://serverless.com
https://github.com/awslabs/aws-serverless-auth-reference-app
Serverless reference app and backend API, showcasing authentication and
authorization patterns using Amazon Cognito, Amazon API Gateway, AWS
Lambda, and AWS IAM
<demo>
aws-serverless-auth-reference-app
</demo>
Building An Infinitely Scalable Online Recording Campaign
For David Guetta & UEFA
Do I need to rebuild everything?
https://github.com/awslabs/aws-serverless-express
This library enables you to utilize AWS Lambda and Amazon API Gateway to
respond to web and API requests using your existing Node.js application
framework
https://github.com/awslabs/aws-serverless-java-container
A Java wrapper to run Jersey, Spark, and other apps inside AWS Lambda
<demo>
aws-serverless-express
</demo>
How to go beyond the timeout?
function processList(itemList, context) {
var item = itemList.shift();
processItem(item, () => {
if (itemList.length === 0) {
console.log('Finished');
} else if (context.getRemainingTimeInMillis() > TIME_THRESHOLD) {
// Process remaning items
processList(itemList, context);
} else {
console.log('Not finished');
// Time is running out,
// invoke self asynchrounously to process remaning items
invokeSelf(itemList, context);
}
});
}
For example…
What about larger apps?
https://github.com/awslabs/serverless-application-model
</>
Serverless Continuous Integration and Deployment
GitHub
Amazon S3
AWS CodeCommit
AWS CodeBuild AWS CodeBuild
third-party tools
AWS CloudFormation
Commit Build Test
Deploy
to Prod
AWS CodePipeline + SAM
<demo>
serverless-application-model
</demo>
AWS Step Functions
Sequential
Steps
Branching Steps
(Choice of Path)
Parallel
Steps
https://states-language.net/spec.html
<demo>
AWS Step Functions
</demo>
Event-Driven Architecture
Name
Email
Create New User
Submit
Check the “Name” syntax is right
(only letters and spaces)
Check the “Email” syntax is right
(something@some.domain)
Create the new user using
provided Name and Email
User Interface Actions
Name
Email
Create New User
Submit
Check the “Name” syntax is right
(only letters and spaces)
Check the “Email” syntax is right
(something@some.domain)
Create the new user using
provided Name and Email
User Interface ActionsObservers
Target Action
Generate thumbnails
Keep another database in sync
Process streaming data
Services FunctionsPlatform
Target Action
Kinesis
Stream
DynamoDB
Table
S3
Bucket
area = length x width
What do you see here?
area = length x width
Procedural Programming
“This is a function!”
area = length x width
Procedural Programming
“This is a function!”
Reactive Programming
“This is data binding!”
To Leverage Even-Driven Architectures,
You May Need to Take a Different Point of View
A B
Event-Driven Design
For Services
”Service A triggers B"
or better
”Service B is caused by A"
A B
C
D
E
F
?
?
What is causing
services E and F?
A B
C
D
E
F
New services (E, F)
are triggered caused by C
A B
C
D
E
F
It can be cyclic
Think of
acknowledgements
Each service
has local visibility
A B
C
D
E
F
What I need to know
(input events)
1
A B
C
D
E
F
What I need to do
(internal logic)
2
A B
C
D
E
F
Who I need to notify
(output events)
3
A B
C
D
E
F
Who I need to notify
(output events)
What I need to know
(input events)
What I need to do
(internal logic)
1
2
3
B
A B
C
D
E
F
Distributed Data Flow
Vs
Centralised Workflow
A B
C
D
E
F
Choreography
Vs
Orchestration
Microservices
Distributed Systems
Monolith
Service
Service
μ
μ
μ
space (distribution, mobility)
time(concurrency,latency)
μ
μ
μ
μ
“Distributed
in Time and Space”
[Jonas Bonér]
“…a diagram of
two microservices
and their shared database”
Data should drive
the boundaries
A
C
I
D
tomic
onsistent
solated
urable
A
C
I
D
tomic
onsistent
solated
urable
A
C
I
D
ssociative
ommutative
dempotent
istributed
ACID 2.0
Prototype
Production
Responsive
ResilientElastic
Message Driven
The Reactive Manifesto
Asynchronous
communication
is not enforced
by serverless architectures
Responsive
ResilientElastic
Message Driven
The Reactive Manifesto
Lambda Everywhere
AWS Greengrass
AWS Snowball Edge
AWS Snowball Edge
AWS Snowmobile
Lambda@Edge
Build Apps With Services,
Not Servers
https://aws.amazon.com/lambda
https://github.com/awslabs/aws-serverless-auth-reference-app
https://github.com/awslabs/aws-serverless-express
https://github.com/awslabs/chalice
https://github.com/awslabs/aws-serverless-java-container
https://serverless.com
https://github.com/awslabs/serverless-application-model
https://states-language.net/spec.html
https://github.com/danilop/AWS_Lambda_in_Action
For Your Reference
Danilo	Poccia
@danilop
Your	feedback	
is	important	to	us!

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