This presentation covers the basics of Serverless through examples and case studies.

1. Serverless by
Examples and Case
Studies
Srushith R Ganesh Samarthyam
@SrushithR @GSamarthyam
CodeopsTechnologies

2. How will the application
handle server hardware failure?
How can I control
Serversaccess from my servers?
When should I decideto
scale out my servers?
When should I decideto
scale up myservers?
What size servers are
right for my budget?
How much remaining
capacity do my
servers have?
(AAHHHHHHHHH!!)
How will I keep my
server OS
patched?
How many servers
should I budget
for?
Content source: https://www.slideshare.net/AmazonWebServices/aws-reinvent-2016-getting-started-with-serverless-
architectures-cmp211
2

3. What is serverless?
“Serverless architectures refer to applications that
significantly depend on third-party services (knows
as Backend as a Service or "BaaS") or on custom
code that's run in ephemeral containers (Function
as a Service or “FaaS”)”
- Martin Fowler

4. Serverless use cases

5. Real time re-tweeting

6. Python code
fromTwitterFollowBot importTwitterBot
def retweet():
# create an instance of theTwitterFollowBot
# by default, the bot will look for a configuration file called
config.txt in your current
my_bot =TwitterBot()
# autoretweets the 5(count) latest tweets that matches
the hashtag
my_bot.auto_rt("#AppleEvent", count = 5)
return {'message' : 'retweeted successfully‘}
retweet()

7. Apache OpenWhisk
Apache OpenWhisk
is an open source
serverless cloud
platform that
executes functions in
response to events at
any scale.

8. Salient features of OpenWhisk
OpenWhisk
Open
source
Wide
range of
languages
Run
docker
images
Run
locally

9. OpenWhisk:Types of invocation
Types of
invocation
Blocking
Non-blocking

10. Let’s go Serverless! – Updated code
from TwitterFollowBot import TwitterBot
def retweet(dict):
my_bot = TwitterBot()
my_bot.auto_rt("#Serverless", count = 5)
def main(dict):
retweet(dict)
return {'message' : 'retweeted successfully'}

11. Create Update Invoke
OpenWhisk function
invocation process

12. Let’s get our
hands dirty!

13. Let’s automate it!

14. Triggers
Cloudant
Custom
trigger
GitHub
Message
hub
Mobile
push
Periodic
Triggers
Cloudant
Custom
trigger
GitHub
Message
hub
Mobile
push
Periodic
triggers when a REST
endpoint is POSTed
to
triggers when a
github repository
is updated
triggers when
Cludant database is
updated
triggers when a new
message is written to
the queue
triggers based on
time
triggers when a push
notification is sent to
your mobile

15. Periodic trigger

16. Chatbots with Serverless

17. How chat bots work? – BookBot
Architecture
User asks for a java
book
Lex understands the
intent, if understood,
invokes lambda and if
not, asks the user to
re-enter
Processes the code
and returns the title
Logs the data
Book title is returned
back to the user

18. Lambda: Overview
A compute service where
you don’t have to think about:
▪ Servers
▪ Being over/under capacity
▪ Deployments
▪ Scaling and fault tolerance
▪ OS or language updates
▪ Metrics and logging
...but where you can easily:
 Bring your own code... even native
libraries
 Run code in parallel
 Create backends, event handlers,
and data processing systems
 Never pay for idle!
Content source: https://www.slideshare.net/AmazonWebServices/aws-lambda-and-the-serverless-cloud

19. Working with Lambda

20. Lambda limits
Content source: http://docs.aws.amazon.com/lambda/latest/dg/limits.html

21. AWS Lex

22. Text and speech language
understanding
Speech
Recognition
Natural Language
Understanding
Powered by the same Deep Learning technology as Alexa
22
Content source: https://www.slideshare.net/AmazonWebServices/integrate-your-amazon-lex-chatbot-with-any-messaging-service-may-2017-
aws-online-tech-talks

23. 23
Integration channels
AWS Lex
Facebook messenger

24. Let’s bot!