The document discusses the state of serverless computing on AWS. It begins by explaining what serverless computing is and how it has evolved from physical servers to virtual servers in data centers to virtual servers in the cloud. It then discusses some of the key benefits of serverless computing such as no server management, automatic scaling, and pay per use. The document outlines some common use cases for serverless applications including web apps, backends, media processing, and big data workloads. It also provides examples of large customers using AWS Lambda at scale. Finally, it discusses some of the building blocks that enable serverless applications on AWS such as Lambda, API Gateway, DynamoDB, and others.

1. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Dr. Tim Wagner, General Manager,
AWS Lambda and Amazon API Gateway
April 18, 2017
State of Serverless Computing
AWS Summit San Francisco

2. Agenda

3. What is
serverless?
Build and run applications
without thinking about servers

4. Let’s take a look at the evolution of computing
Physical servers
in data centers
Virtual servers
in data centers
Virtual servers
in the cloud

5. Each progressive step was better
Physical servers
data centers
Virtual servers
data centers
• Higher utilization
• Faster provisioning speed
• Improved uptime
• Disaster recovery
• Hardware independence
• Trade CAPEX for OPEX
• More scale
• Elastic resources
• Faster speed and agility
• Reduced maintenance
• Better availability and fault
tolerance
Virtual servers
in the cloud

6. But there are still limitations
Physical servers
data centers
Virtual servers
data centers
• Trade CAPEX for OPEX
• More scale
• Elastic resources
• Faster speed and agility
• Reduced maintenance
• Better availability and fault
tolerance
• Still need to administer
virtual servers
• Still need to manage
capacity and utilization
• Still need to size
workloads
• Still need to manage
availability, fault tolerance
• Still expensive to run
intermittent jobs
Virtual servers
in the cloud

7. Evolving
to serverless
SERVERLESS
Virtual servers
in the cloud
Physical servers
in data centers
Virtual servers
in data centers

8. No server is easier to manage than no server
All of these responsibilities
go away
Provisioning and utilization
Availability and fault tolerance
Scaling
Operations and management

9. Serverless is a form of event-driven computing
Event-driven computing
Function as a Service
Serverless

10. EVENT DRIVEN CONTINUOUS SCALING PAY BY USAGE
Deliver on demand, never pay for idle

11. Building blocks for serverless
AWS Lambda Amazon DynamoDB
Amazon SNS
Amazon API Gateway
Amazon SQS
Amazon Kinesis
Amazon S3
Orchestration and State Management
API Proxy Messaging and Queues Analytics
Monitoring and Debugging
Compute Storage Database
AWS X-RayAWS Step Functions
Edge Compute
AWS Greengrass
Lambda@Edge

12. Serverless changes how you deliver
Speeds up
time to market
Dedicated time
to innovation
Increases developer
productivity
Eliminates operational
complexity

13. Serverless today

14. Chatbots
• Powering
chatbot logic
• Alexa Skills for
Amazon Echo
Common use cases
Web
applications
• Static
websites
• Dynamic
web apps
• Packages for
Flask and
Express
Backends
• Apps &
services
• Mobile
• IoT
</></>
Media & Log
Processing
• Real-time data
• Streaming
data
Big Data
• MapReduce
• Batch

15. Big Data
• MapReduce
• Batch
Big data
Map Phase Reduce PhaseInputs Results

16. Serverless Map/Reduce with Lambda
https://github.com/awslabs/lambda-refarch-mapreduce

17. PyWren: a massive data framework for Lambda
• Open source MapReduce
framework using Lambda
• 25 TFLOPS performance
• 60 GB/sec read and 50
GB/sec write to S3
https://github.com/pywren/pywren
http://pywren.io/
http://ericjonas.com/

18. Academics agree: serverless + big data = <3
(Source: arXiv)

19. NEW
Now run denser workloads with Lambda
Default concurrency
=
600 concurrent functions600

20. Customers innovating with serverless

21. Enterprises are achieving massive scale with Lambda
• Thomson Reuters processes 4,000 requests per second
• FINRA processes half a trillion validations of stock trades daily
• Hearst reduced the time to ingest and process data for its
analytics pipeline by 97%
• Vevo can handle spikes of 80x normal traffic
• Expedia triggers 1.2 billion Lambda requests each month

22. © 2017 Autodesk
Alan Williams
Enterprise Architect
AWS SF Summit 2017
Tailor - Managing AWS accounts
at scale, serverlessly
@alanwill alanwill

23. https://archiveofourown.org/works/1974981
Once Upon A Time…

24. Human Error Labor intensive
Inconsistency
Provisioning Request
Turnaround
(1-2 weeks)
Global Configuration
Changes

25. http://www.eharmony.com.au/dating-advice/dating/what-if#.WJFRCkXysnU

26.  …we could provision accounts in minutes vs weeks?
 …we could make global changes to all accounts with a
single API call?
 …we could manage all accounts like a single account?
 …we lost all care for whether we have 100 or 10000+
accounts?

27. Tailor
Tailor-made + serverless AWS
Account management at scale

28.  Low Ops
 No OS patching
 No configuration management
 Minimal capacity planning
 Code focus
 Economical
 Managed
 Seamless integration
 Just works
Why Lambda & API Gateway?
SSH

29. Current Capabilities

30. Provisioning
• Lambda + API Gateway + Organizations
Standards
Enforcement
• Lambda + API Gateway
Querying
• API Gateway + Lambda + DynamoDB
Auditing
• Config Rules + Lambda + DynamoDB

31. https://www.collegetransitions.com/top-architecture-colleges/
Architecture

33. https://99robots.com/wordpress-security-log/
Security

34.  All actions logged & auditable
 IAM session name
 CloudTrail
 Root MFA enabled
 Isolated AWS account
Security Features

35. https://admissions.byu.edu/how-much-does-it-cost
Economics

36. Pre-Tailor (Manual) Post-Tailor
(Automated)
Average # of new
accounts per month
2 20
Provisioning Time 10 hours 10 minutes
Tailor Infrastructure N/A $125/m
Cost per account >$500 <$6
ROI

37.  ~$125 per month
 $30 - Cloudwatch/DynamoDB/Config/RDS
 $75 – Lambda
How much does it cost to run?

38.  5-10 accounts per week
 100s of accounts under management
 Serving ~100 project teams / ~500 engineers / 4 business units
 10 minutes provisioning time
 Peak 400 Lambda invocations per sec from Kinesis Streams
 1 month engineering & development time
Stats

39.  Increased time to value
 Reduction in human errors
 Increased security posture
 Reduction in provisioning time
 Scalable
 Reusable
Benefits

40. http://www.gastro.org/about/initiatives/aga-roadmap-to-the-future-of-gi-practice
ArchitectureRoadmap

41.  VPC Peering Approvals
 Tailor Bot
 Serverless – SAM migration
 Open Source
Very soon…

42. Autodesk and the Autodesk logo are registered trademarks or trademarks of Autodesk, Inc., and/or its subsidiaries and/or affiliates in the USA and/or other countries. All other brand names, product names, or trademarks belong to their respective holders.
Autodesk reserves the right to alter product and services offerings, and specifications and pricing at any time without notice, and is not responsible for typographical or graphical errors that may appear in this document.
© 2017 Autodesk. All rights reserved.

43. Serverless is a core component of modern apps

44. AWS serverless platform

45. Capabilities of a
serverless platform

46. Cloud logic layer

47. NEW
Cloud logic layer
New Lambda runtimes
• Node.js v6.10 announced in March
• Python 3.6 now available

48. NEW
Cloud logic layer
Tagging for Lambda
• Add metadata to Lambda functions using tags
• Track and allocate costs per function

49. Cloud logic layer
Other recent features…
• Iterator age metric for Amazon Kinesis records
• View Lambda function policies from the Console

50. NEW
Cloud logic layer
HIPAA compliance
• Amazon API Gateway is now HIPAA
compliant

51. NEW
Cloud logic layer
API request validation
• Amazon API Gateway supports request
validation
• Check for required request parameters in a
request’s URI, query string, and headers
• Verify adherence to the request model of
methods
• Detailed error logs stored in Amazon
CloudWatch Logs

52. NEW
Cloud logic layer
API Gateway + ACM
• API Gateway is now integrated with
AWS Certificate Manager
• Deploy and configure SSL/TLS certificates for
custom API Gateway domains in minutes

53. Responsive data sources

54. Lambda event sources – AWS services
Amazon API Gateway
Amazon S3
Amazon DynamoDB
Amazon Aurora
Amazon Simple Notification Service
Amazon Simple Email Service
Amazon Cognito
AWS Snowball Edge
Amazon CloudWatch
Amazon Kinesis Streams
Amazon Kinesis Firehose
AWS CodeCommit
AWS CloudFormation
AWS Config
Amazon Lex

55. Integrations library

56. Integrations library
Amazon API Gateway listings in
the AWS Marketplace

57. Reliability and performance

58. Reliability and performance
Dead Letter Queues
• Automatically capture events after
exhausting retries
• Build even more reliable event processing
applications
• Target Amazon SQS queues or Amazon
SNS topics
• Available in all regions

59. Application modeling framework
Monolithic
application
Microservices

60. But what happens
when you have an
entire app made up
of many functions?
Composing serverless applications

61. Meet SAM

62. AWS Serverless Application Model (SAM)
Standard model for
representing serverless
applications on AWS
Functions, APIs, event
sources, and data stores
Simplifies deployment and
management for serverless
applications

63. AWS Serverless Application Model (SAM)
• Natively supported by AWS
CloudFormation
• Export any function as a SAM
template
• Package and deploy SAM
templates using AWS CLI
• Open spec under Apache 2.0
for community extensions

64. NEW
AWS Serverless Application Model (SAM)
New features
• Support for inline Swagger
• Intrinsic functions

65. CI/CD for serverless applications
</>
AWS CodePipeline + SAM
GitHub
Amazon S3
AWS CodeCommit
AWS CodeBuild AWS CodeBuild
Third-party tools
AWS CloudFormation
Commit Build Test
Deploy
to Prod

66. Developer ecosystem — AWS
How do you debug distributed applications
made of multiple functions or services?
How do you gain insights into how your
functions are performing or behaving?

67. AWS X-Ray
• Analyze and debug distributed
apps in production
• Visualize service call graph of
your app
• Identify performance
bottlenecks and errors
• Pinpoint service-specific issues
• Identify impact of issues on
users of the app
• Trace function executions
(preview)

68. How X-Ray works
Trace Requests Record Traces View Service Map Analyze Issues

69. X-Ray example

70. X-Ray example

71. X-Ray example

72. X-Ray example

73. X-Ray example

74. X-Ray example

75. X-Ray example

76. Developer tools
Write
code
Deploy to
customer
Build
and test
Receive
feedback

77. Developer ecosystem — commercial
MonitoringDeployment Service Delivery
Program
IntegrationsCode Libraries

78. Developer ecosystem — open source
Chalice
Framework
Serverless Java
Container

79. Orchestration and state management

80. NEW
AWS Step Functions update
New features
Integration with API Gateway
Error-handling for Lambda functions
Send CloudWatch Events to Step Functions

81. AWS Greengrass (in preview)
• Extends Lambda functions to devices
• Low latency, near-real time

82. AWS Snowball Edge
• Petabyte-scale hybrid device with
onboard compute and storage
• Deploy AWS Lambda code to
Snowball Edge

83. NEW
Global scale
Lambda available in
most major regions in
the AWS global
infrastructure
Now available in
London and Mumbai
regions!

84. Lambda@Edge (in preview)
Lambda@Edge is available
in all Amazon CloudFront
edge locations
• Low-latency
request/response
customization
• Supports viewer and
origin events

85. Amazon CloudFront triggers for Lambda@Edge
functions
Origin
server
End user CloudFront
cache
Viewer response Origin response
Viewer request Origin request

86. Lambda@Edge use cases
Content
customization
Visitor
validation
A/B testing

87. Serverless is a
fundamental
component of
modern
applications

88. Learn more about serverless
Tuesday, April 18
10:15 AM - 11:15 AM Building Serverless Web Applications (SMC302)
11:30 AM - 12:30 PM Real-time Data Processing Using AWS Lambda (SMC303)
12:45 PM - 1:45 PM Serverless Orchestration with AWS Step Functions (SMC304)
2:00 PM - 3:00 PM Building CI/CD Pipelines for Serverless Applications (SMC305)
2:00 PM - 3:00 PM Serverless big data architectures (BDA303)
Wednesday, April 19
12:00 PM - 2:00 PM Wild Rydes Takes Off – The Dawn of a New Unicorn (WKS407)
12:00 PM - 2:00 PM Build an Alexa Skill using AWS Lambda (WKS403A)

89. Conclusion
Lambda is a fundamental
component of modern
application architectures
It has a place in everything
from data processing to
simple web apps