With AWS Lambda, you can easily build scalable microservices for mobile, web, and IoT applications or respond to events from other AWS services without managing infrastructure. In this session, you’ll see demonstrations and hear more about newly launched features. We’ll show you how to use Lambda to build web, mobile, or IoT backends and voice-enabled apps, and we’ll show you how to extend both AWS and third party services by triggering Lambda functions. We’ll also provide productivity and performance tips for getting the most out of your Lambda functions and show how cloud native architectures use Lambda to eliminate “cold servers” and excess capacity without sacrificing scalability or responsiveness.

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Level 200 (Introductory)
Leo Zhadanovsky
Principal Solutions Architect, AWS
February 24th, 2017
Getting Started with
AWS Lambda and the Serverless Cloud

2. AWS compute offerings
VM Task Function
Service EC2 ECS Lambda
H/W OS Runtime
Unit of scale
Level of
abstraction

3. AWS compute offerings
I want to
configure
machines,
storage,
networking,
and my OS
I want to run
servers,
configure
applications,
and control
scaling
Run my
code when
it’s needed
Service EC2 ECS Lambda
How do I
choose?

4. Agenda
• Why AWS Lambda
• How it works
• Use cases
• Sample architecture
• Best practices

5. Why AWS Lambda

6. Servers
How will the application
handle server hardware failure?
How can I control
access from my servers?
When should I decide to
scale out my servers?
When should I decide to
scale up my servers?
What size servers are
right for my budget?
How much remaining
capacity do my servers have?
(AAHHHHHHHHH!!)

7. Operations and management Scaling
Provisioning and utilization Availability and fault tolerance
Owning servers means dealing with ...

8. Serverless compute: AWS Lambda
COMPUTE
SERVICE
EVENT-
DRIVEN
Run arbitrary
code without
managing
servers
Code only runs
when it needs to
run

9. AWS Lambda: Run code in response to events
Lambda functions: Stateless, trigger-based code execution
Triggered by events:
• Direct sync and async API calls
• AWS service integrations
• Third-party triggers
• Many more …
Makes it easy to:
• Perform data-driven auditing, analysis, and notification
• Build back-end services that perform at scale

10. Cost-effective and
efficient
No infrastructure
to manage
Pay only for what you use
Bring your
own code
Productivity-focused compute platform to build powerful, dynamic, modular
applications in the cloud
Run code in standard
languages
Focus on business logic
Benefits of AWS Lambda
1 2 3

11. How it works

12. Using AWS Lambda
Bring your own code
• Node.js, Java, Python
• Bring your own libraries
(even native ones)
Simple resource model
• Select power rating from
128 MB to 1.5 GB
• CPU and network
allocated proportionately
Flexible use
• Synchronous or
asynchronous
• Integrated with other
AWS services
Flexible authorization
• Securely grant access to
resources and VPCs
• Fine-grained control for
invoking your functions

13. Using AWS Lambda
Authoring functions
• WYSIWYG editor or
upload packaged .zip
• Third-party plugins
(Eclipse, Visual Studio)
Monitoring and logging
• Metrics for requests,
errors, and throttles
• Built-in logs to Amazon
CloudWatch Logs
Programming model
• Use processes, threads,
/tmp, sockets normally
• AWS SDK built in
(Python and Node.js)
Stateless
• Persist data using
external storage
• No affinity or access to
underlying infrastructure

14. Application components for serverless apps
EVENT SOURCE FUNCTION SERVICES (ANYTHING)
Changes in
data state
Requests to
endpoints
Changes in
resource state
Node
Python
Java
… more coming soon

15. Amazon
S3
Amazon
DynamoDB
Amazon
Kinesis
AWS
CloudFormation
AWS
CloudTrail
Amazon
CloudWatch
Amazon
SNS
Amazon
SES
Amazon
API Gateway
Amazon
Cognito
AWS
IoT
Amazon
Alexa
Cron events
DATA STORES ENDPOINTS
REPOSITORIES EVENT/MESSAGE SERVICES
Event sources that integrate with AWS Lambda
… and the list will continue to grow!

16. Use cases

17. Analytics
• Operational management
• Live dashboards
Data workflows
• Content management
• ETL workflows
Multiple application types
Interactive back ends
• Bots
• Webhooks
Autonomous IT
• Policy engines
• Infrastructure management

18. Everybody knows this 3-tier web app diagram
https://d0.awsstatic.com/whitepapers/AWS_Serverless_Multi-Tier_Architectures.pdf

19. Here is what that translates to in real life
http://media.amazonwebservices.com/architecturecenter/AWS_ac_ra_web_01.pdf

20. Updated real-world “serverless” architecture
https://s3.amazonaws.com/awslambda-reference-architectures/web-app/lambda-refarch-webapp.pdf

21. Example: Real-time file processing
https://github.com/awslabs/lambda-refarch-fileprocessing

22. Example: Stream processing
https://github.com/awslabs/lambda-refarch-streamprocessing

23. What to expect from the session
15-20 minutes of processing  now in seconds
2x order of magnitude for cost savings
https://www.youtube.com/watch?v=TXmkj2a0fRE
Nordstrom Recommendations

24. Serverless IoT with AWS Lambda @ iRobot

25. AWS
Lambda
Amazon
CloudFront
Amazon
S3
Amazon
DynamoDB
Amazon
Redshift
Amazon
Route 53 Amazon VPC
Amazon
CloudWatch
AWS
CloudFormation
AWS
CloudTrail
AWS
Config AWS IAMAWS KMSAWS WAF
Amazon Cognito Amazon
SNS
Amazon API
Gateway
Amazon
SQS
Amazon
Elasticsearch Service
Amazon
Kinesis
Amazon
QuickSight
AWS IoT
How iRobot leverages AWS

26. Serverless → distributed by nature
Component graph
becomes call graph
Distributed systems
thinking is required from
the start
Event-based architecture

27. API Gateway
App requests
over HTTPS
CRUD
operations

28. IoT
MQTT
CRUD
operations

29. IoT
MQTT
MQTT
Presigned
URL
Staging
bucket

30. SQS/CloudWatch Events
CloudWatch event
every 5 minutes
Lambda runs
for 5 minutesSQS queue

31. Best practices

32. AWS Lambda best practices
 Limit your function/code size
 Node – remember execution is asynchronous
 500 MB /tmp directory provided to each function
 Don’t assume function will reuse underlying infrastructure
 But take advantage of it when it does occur
 You own the logs
 Include details from service-provided context
 Create custom metrics
 Operations-centric vs. business-centric

33. Best practice: Use versions and aliases
Versions = immutable copies of code + properties
Aliases = mutable pointers to versions
 Rollbacks
 Staged
promotions
 “Lock” behavior
for client

34. The function networking environment
 Default - a default network environment within VPC is provided for you
 Access to the Internet always permitted to your function
 No access to VPC-deployed assets
 Customer VPC - Your function executes within the context of your own VPC
 Privately communicate with other resources within your VPC
 Familiar configuration and behavior with:
 Subnets
 Elastic network interfaces (ENIs)
 EC2 security groups
 VPC route tables
 NAT gateway

35. Additional best practices
 Externalize authorization to IAM roles whenever possible
 Least privilege and separate IAM roles
 Externalize configuration
 DynamoDB is great for this
 Make sure your downstream setup “keeps up” with Lambda scaling
 Limit concurrency when talking to relational databases
 Be aware of service throttling
 Engage AWS Support to increase your limits
 Contact AWS Support before known large scaling events

36. Takeaways
• Many applications can go serverless
• Data processing, back ends, triggers, web hooks
• Lambda functions are opinionated
• State, invocation modes, and deployments
• The ecosystem continues to grow
• Tooling, languages, and application capabilities

37. Next steps
1. Go to console.aws.amazon.com/lambda and create your first
Lambda function. (The first 1M requests are on us!)
2. Stay up to date with AWS Lambda on the Compute blog and check
out aws.amazon.com/lambda for scenarios and customer stories.
3. Send us your questions, comments, and feedback on the AWS
Lambda Forums.
Bonus points: Enter the AWS Serverless Chatbot Competition
https://aws.amazon.com/blogs/aws/enter-the-aws-serverless-chatbot-
competition/

38. Remember to complete
your evaluations!