This document provides best practices and recommendations for startups and developers building applications on AWS. It discusses principles like failing fast and cheap, building minimum viable products, focusing on core features, leveraging AWS services, loose coupling of services, auto-scaling, continuous delivery, and measuring everything to enable rapid iteration and innovation. The overall message is that AWS lowers the cost of failure, allowing companies to experiment more often and increase innovation.

1. AWS Cloud Kata for Start-Ups and Developers
Jakarta
Startup Best Practices on AWS
Markku Lepistö
Principal Technology Evangelist
@markkulepisto

2. IDEA !
For the next -

5. Fail Fast
Fail Cheap
Fail Forward

6. Scale Success

7. Validate Idea

8. Minimum Viable Product (MVP)
! Release quickly
! Limited core features
! Iterate in production
! Decisions based on data
“Production is truly the only place
you can validate your code”
- Michael Nygard, author of ‘Release it!

9. Application Architecture
for MVP’s Core Features

10. Tightly Coupled, Monolithic (monster)

11. Decomposed to Services

12. Decomposed to Services

13. Decomposed to Services

14. Define Your MVP’s Building Blocks

15. Define Your MVP’s Building Blocks
Compute
Object Store
Load Balancer
SQL Database
Identity & Access
Data Warehouse
Application Lifecycle
CDN
Recommendation Engine
Social Login SSO
BI Analytics
Web Server
Reverse Proxy
My Second Cool FeatureMy Cool Feature

16. Focus

17. Focus on Your Core Differentiator

18. Offload Undifferentiating Ones to Services
Amazon EC2
Amazon S3
Elastic Load Balancing
Amazon RDS
AWS IAM
Amazon RedShift
AWS OpsWorks
Amazon CloudFront
EasyRec
HybridAuth
JasperSoft
Puma
Nginx
My Second Cool FeatureMy Cool Feature

19. Amazon Web Services

20. Regions, Zones and Edge Locations

21. Platform
Services
Databases
Caching
Relational
No SQL
Analytics
Hadoop
Real-time
Data
Workflows
Data
Warehouse
App Services
Queuing
Orchestration
App Streaming
Transcoding
Email
Search
Deployment & Management
Containers
Dev/ops Tools
Resource Templates
Usage Tracking
Monitoring and Logs
Mobile Services
Identity
Sync
Mobile Analytics
Notifications
Foundation
Services
Compute
(VMs, Auto-scaling
and Load Balancing)
Storage
(Object, Block
and Archive)
Security &
Access Control
Networking
Infrastructure Regions CDN and Points of PresenceAvailability Zones
Enterprise
Applications
Virtual Desktops Collaboration and Sharing

22. Discover SW Components – AWS marketplace

23. Discover SW Components – GitHub

24. Discover SW Components – NetflixOSS

25. Services are Black Boxes Exposed via APIs
My Cool Feature
Iterate, even re-
write internal
implementation
API is stable, with
few changes,
potentially
versioning
API
e.g JSON / REST
over HTTP

26. Loose Coupling Enables Scale-out and Resiliency
Use Message Queues

27. Loose Coupling Enables Scale-out and Resiliency
Use Message Queues
Simple Queue
Service (SQS)

28. Loose Coupling Enables Scale-out and Resiliency
Use Idempotent Interfaces

29. Loose Coupling Enables Scale-out and Resiliency
Use Circuit Breakers

30. Loose Coupling Enables Scale-out and Resiliency
Use Circuit Breakers
Temporarily bypass
unresponsive
service. Switch to
degraded mode
transactions

31. Auto Scale, Load Balance, Monitor, HA Assure
Each Service Separately

32. Statelessness Enables Scale-out
Separate State and Data from Compute Instances
Load Balanced, Auto Scaling
pool of EC2 Workers
Scalable Services for
State and Data
ElastiCacheDynamoDBS3

33. Amazon DynamoDB
Zero Admin NoSQL Service
Unlimited Storage
Provisioned Throughput
<10ms response time
Durable on SSD

34. Cloud-SOA
Service
Oriented
Architecture
! Cloud-native New Applications
! SOA principles leveraging Cloud
services
! Architect for
• Automation
• Scale
• Cost
• Availability
• Data
! Applications are
• Always-on
• Self-healing
• Anti-fragile

35. Implemented by Two-Pizza Teams
! Small, autonomous teams
! Full responsibility for Service X
! Decoupled launch schedules
! No handovers
! Trust

36. Putting It All Together into a Solution

37. Putting It All Together into a Solution

38. Putting It All Together into a Solution

39. Putting It All Together into a Solution

41. =
Programmable Platform

42. If you can program it
You can automate it

43. AWS SDKs

44. Java SDK
…!
res = ec2.runInstances new RunInstancesRequest([!
!imageId: "ami-00754474", !
!keyName: ”MyKeyPair", !
!instanceType: ”m3.medium", !
!securityGroups: [”MySecurityGroup"],!
!minCount: 1,!
!maxCount: 1,!
!userData:!
!"AWSWeb.war".bytes.encodeBase64().toString()!
!])!
…!
!

45. Unified Command Line Interface
~ $ aws ec2 run-instances
--image-id ami-554ac83c
--min-count 1
--max-count 1
--key-name MyKeyPair
--security-groups MySecurityGroup

46. « Cloud Instance is an
implementation of a
known, good state »
Dr Rich Wolski, UCSB

47. AMIAMIAMI
YOUR CODE
CORE SERVICES
3rd PARTY
LIBRARIES
OPERATING
SYSTEM
YOUR CODE
CORE SERVICES
3rd PARTY
LIBRARIES
OPERATING
SYSTEM
YOUR CODE
CORE SERVICES
3rd PARTY
LIBRARIES
OPERATING
SYSTEM
Pre-baked Image Base OS Image + Orchestration

48. 3rd Party Configuration Mgmt & Orchestration Tools

49. AWS$OpsWorks$ AWS$
CloudForma2on$
AWS$Elas2c$
Beanstalk$
DevOps$framework$for$
applica2on$lifecycle$
management$and$
automa2on$
Templates$to$deploy$&$
update$infrastructure$
as$code$
Automated!resource$
management$–$web$
apps$made$easy$
DIY$/$$
On$Demand$
DIY,$on$demand$
resources:$EC2,$S3,$
custom$AMI’s,$etc.$
ControlConvenience
AWS Services for Application Lifecycle Management

51. EC2 Container Service New
for
Managing Docker at Scale

52. CloudForma+on!
Template!

53. Application Versions + Infrastructure Versions
Applica+on!
Your!Code!
Infrastructure!
To!Run!and!Support!Your!Code!

54. Deliver Continuously

55. test
Continuous Integration
code buildplan
Agile Development
Source http://www.collab.net
deploy operate
collaboration
value
DevOps
release
Continuous Delivery

56. 11.6s
Average time
between
deployments
(weekday)
1,079
Max number of
deployments in a
single hour
(or approx every
3 seconds)
30,000
Max number of
instances
simultaneously
receiving a
deployment
Speed of deployments at amazon.com
May 2011 snapshot

57. OODA Loop – Key Cycle for Agile Businesses

58. Go Global – in Minutes
! Launch in a test market
! A/B Testing
! Collect all logs
! Analytics ! Insights ! Iterate
! or Pivot
Once you hit the sweet spot –
! Replicate to all regions

60. Measure!outliers!&!
ends!of!distribu+on!
Measure & Log Everything
Amazon!CloudWatch!

61. COLLECT | STORE | ANALYZE | SHARE
Import Export
Glacier
S3 EC2
RedshiftDynamoDB
EMR
Data Pipeline
S3Direct Connect
Leverage AWS Big Data Services
CloudFront
Kinesis

62. Keep Iterating

63. Keep Innovating

64. « Want to increase innovation?
Lower the cost of failure »
Joi Ito
MIT MediaLabs

65. AWS Lowers the Cost of Failure
Experiment
Often
Fail quickly at
a low cost
More
Innovation
Experiment
Infrequently
Failure is
expensive
Less
Innovation
“ON-PREMISE”

66. AWS Cloud Kata for Start-Ups and Developers
台北
6月25日