Following simple patterns of good application design can allow you to scale your application for your customers easily. This presentation dives into the 12 factor application design and demo how this applies to containers and deployments on Amazon ECS and Fargate. We'll take a look at tooling that can be used to simplify your workflow and help you adopt the principles of the 12 factor application.

1. © 2018, Amazon Web Serv ices, Inc. or its Af f iliates. All rights reserv ed.
AWS Builders’ Day London
MAD4 - Breaking the Monolith: road to
containerizing/serverless your app
Paul Armstrong - Principal Solutions Architect

2. Breaking Down the Monolith

3. The monolith
“…asingle-tiered software application inwhichtheuser interface
and data access code arecombined into asingle program from a
single platform. Amonolithic application isself-contained, and
independent from other computing applications.”
-Wikipedia

4. Monolith = ”traditional applications”
• Pros:
• At first…
• Simple
• No over-engineering
• In-process latencies
• Single code base
• Resource efficient at small
scale
• Cons:
• Modularity is hard to enforce
as app grows
• Can only scale up!
• All or nothing deployment
• Long release cycles
• Slow to react to customer
demand

5. Monolith development lifecycle
Build Test Release
Developers
Monolith
Delivery Process

6. How or why should I migrate
my monolith?

7. Common migration strategies
There is no one size fits all approach to migrating your
applications

8. Methodical migration process
Evaluat
e
Plan Design Migrate Optimize
• Discovery
• Migration
patterns
• Well
Architected
• Tool
selection
• Test
planning
• Cutover
• Migration
workloads
• Migration
tools
• Validation &
cutover
• Operation
• Optimizati
on
• Migration
Readiness
Assessment
• On-boarding
• Planning and
SOW
• Portfolio
discovery
• Requirements
collection
• Landing Zone
• People -
skills and
organization
• Business
case, TCO
Visualize the cloud adoption effort from planning to operating on AWS

9. Portfolio discovery
Goals:
• Determine resource allocation in the AWS environment
• Develop a prioritized backlog of applications to feed migration
• Assess project migration costs and run costs
Evaluat
e
Discove
r &
Plan
Design Migrate Optimize

10. Questions & challenges on the migration journey
• Where to start?
• What to break out?
• Dependencies?
• Works as expected?
• Users happy?
• Does it scale?
• Does it perform?
• How to automate?
• Works as expected?
• Users happy?
• How to optimize?
Does it perform?
• How to automate?
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From
On-Premises Monolith
Via
Containerized Services
To
Functions & Cloud Service

11. Containers as part of my
migration strategy?

12. Accelerate
Development
Easier
Adoption
Faster
Iteration
Unified
Experience
Container Platforms
Container Benefits

13. Where do I start?

14. Discovery – Portfolio Data Gathering
• Storage
• Type
• Capacity
• Utilization
• . . .
• Server
• Physical/virtu
al
• OS version
• CPU, RAM, Disk
• type,
utilization
• . . .
• Network
• Device type
• Firewall rule
• Network
connection
• . . .
• Application
• Owners,
criticality
• Characteris
tics
• Stack
• Infrastruct
ure
• . . .

15. Analysis … What Should We Look For?
• Completeness and usability
• If additional discoveryis needed,determine the actions needed to complete discovery.
• Apps, Servers,
Connections
• No. of apps and
servers
• Application and
server dependencies
• Performance
metrics
• Allocate and
right-size
target resources
• Service naming,
tagging
• Identify patterns
• Group servers and
applications

16. Asset
Inventories
CMBD
Tribal
Knowledge
SLA/OLA
App
Configuration
Data
Performance
Information
Architecture
Outcomes
Applications
Infrastructure
Performance
Portfolio Discovery & Analysis
Outcomes
Resource Model
Application backlog
Cost Model
AWS Application
Discovery Service
Disconnected and
Incomplete Data
Gathering Data and
Organizing
“Discovery & Planning”

17. Getting toknow themonolith architecture
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Service
Endpoints
Service Flow
Depending
Services

18. Learnings Through Discovery
/review
/finish
/config
/payment
Backend
Service X
DB A
Q 1
Endpoints +
Throughput
Dependencies&
Call Patterns
Flow & CPU
Consumption

19. Next: Where to break the monolith?
/review
/finish
/config
/payment
Backend
Service X
DB A
Q 1
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Entry Points? Entry Points?

20. Refactoring – break the monolith
Tightly coupled! Shall we really distribute/extract?
ExampleCorpBackendW ebser...
com.Dynatrace.exampleCorp ...

21. The 12 factor application

22. The 12 factor application
I. Codebase
One codebasetrackedin revision control,many
deploys
II. Dependencies
Explicitly declareand isolate dependencies
III. Config
Store config in the environment
IV. Backing services
Treatbacking services asattached resources
V. Build, release,run
Strictly separate build and run stages
VI. Processes
Executethe app as one or more stateless
processes
VII. Port binding
Exportservices via portbinding
VIII. Concurrency
Scale out via the processmodel
IX. Disposability
Maximize robustnesswith fast startup and graceful
shutdown
X. Dev/prod parity
Keep development,staging,and productionas
similar as possible
XI. Logs
Treatlogs as eventstreams
XII. Admin processes
Run admin/managementtasks as one-offprocesses

23. Amazon ECS and Fargate

24. RUNNING A SINGLE CONTAINER

25. EC2 Instance
TaskTask
Task Task
EC2 Instance
TaskTask
Task Task
EC2 Instance
TaskTask
Task Task
EC2 Instance
TaskTask
Task Task
EC2 Instance
TaskTask
Task Task
RUNNING CONTAINERS

26. RUNNING CONTAINERS AT SCALE WITH ECS
Availability Zone #1 Availability Zone #2 Availability Zone #3
Scheduling and Orchestration
ClusterManager Placement Engine

27. ECS
AMI
Docker
agent
ECS
agent
ECSTaskECSTask
ECSTaskECSTask
EC2 Instance

28. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
ECS
AMI
Docker
agent
ECS
agent
EC2 Instance
ECS
AMI
Docker
agent
ECS
agent
EC2 Instance
ECS
AMI
Docker
agent
ECS
agent
EC2 Instance
Scheduling and Orchestration
ClusterManager Placement Engine

29. “Just launch 10 copies of
my container distributed
across three availability
zones and connect them to
this load balancer”
X 10

30. I. CodebaseOne codebase tracked in revision control, many deploys

31. Deployed VersionCode Version Control

32. Staging / QA
Production
Dev #1
Dev #2

33. II. DependenciesExplicitly declare and isolate dependencies

34. Dependencies
Binaries
Code
Application
Bundle

35. Dependency Declaration: Node.js
npm install
yarn install
package.json

36. Dependency Declaration: Python
pip install
requirements.txt

37. Dependencies
Dependencies
Binaries
Code

38. Dependency Declaration & Isolation: Docker
docker build
Dockerfile

39. Development
Production
docker run

40. III. ConfigStore config in the environment

41. Development
Configuratio
n
Production
Configuration
Development
Production

42. Development
Production
Same container deployed to both environments.
Configuration is part of the environment on the host.

43. At runtime the container gets config from the
environment.

44. Application code pulls from the
environment
Environment is customized when docker runs a container

45. IV. Backing servicesTreat backing services as attached resources

46. Amazon
S3
PostgreSQLapp1
Host
app2 3rd party
service
Treat local services just like
remote third party ones

47. PostgreSQ
L
app1
app2
Load
balancer
Use CNAMES for maximum
flexibility and easy reconfiguration
postgres.mycompany.c
om
app2.mycompany.co
m

48. Easily create and maintain custom maps of your applications
Before
Version 2
After
Version 2

49. V. Build, release, runStrictly separate build and run stages

50. Dependencies
Binaries
Code
Build

51. Release
Config ReleaseBuild Artifact
+ =
Tagged image stored in ECR

52. Amazon Elastic Container Service
Confi
g

53. Run
Task
Definition
Release v1
Task Definition
Release v2

54. VI. ProcessesExecute the app as one or more stateless processes

55. Stateful container stores state in local disk
or local memory. Workload ends up tied to a
specific host that has state data.
eu-west-1b
Container 1
Disk
eu-west-1ceu-west-1a

56. Stateful data
Use services:
• Amazon RDS
• Amazon DynamoDB
• Amazon ElasticCache
• Amazon ElasticSearch
• Amazon S3
• ……

57. VII. Port bindingExport services via port binding

58. Port 32456
Port 32457
Port 32458

59. Port
32768
Port
33487
Port
32192
Port
32794
Port
32781
Match:
/api/users*
Match:
/api/auth*

60. VIII. ConcurrencyScale out via the process model

61. © 2018, Amazon Web Services, Inc. or its Affiliates. All
rights reserved.
RUNNING CONTAINERS AT SCALE W ITH
ECS
Availability Zone
#1
Availability Zone
#2
Availability Zone
#3
Scheduling and Orchestration
Cluster Manager Placement Engine

62. Scaling
Instance
Container 1
Instance Instance Instance Instance Instance
+
Container 1
Container 1
Container 1
Container 1
Container 1

63. IX. DisposabilityMaximize robustness with fast startup and graceful shutdown

64. Responsive Graceful
Shutdown
Fast Launch

65. Fast Launch
Minimize the startup time of processes:
• Scale up faster in response to spikes
• Ability to move processes to another host as needed
• Replace crashed processes faster

66. Responsive, Graceful Shutdown
Should respond to SIGTERM by shutting down gracefully

67. X. Dev/prod parityKeep development, staging, and production as similar as possible

68. Staging / QA
Production
Dev #1
Dev #2

69. Local Application Remote
Staging / QA
Production
Dev #1
Dev #2

70. XI. LogsTreat logs as event streams

71. Containerized code writes to
stdout
Docker connects container’s stdout to a log driver

72. CLOUDWATCH LOGS CONFIGURATION
• Use the awslogs driver to
send stdout from your
application to Cloudwatch
logs
• Create a log group in
Cloudwatch
• Configure the log driver
in your task definition
• Remember to add
permissions via the Task
Execution Role
{
"family": " scorekeep",
...
"containerDefinitions ": [
{
"name":“scorekeep-frontend",
...
"logConfiguration": {
"logDriver": "awslogs",
"options": {
"awslogs-group": "scorekeep",
"awslogs-region": “us-east-1",
"awslogs-stream-prefix": "scorekeep/frontend“}}
},
{
"name":“scorekeep-api",
...
"logConfiguration": {
"logDriver": "awslogs",
"options": {
"awslogs-group": "scorekeep",
"awslogs-region": “us-east-1",
"awslogs-stream-prefix": "scorekeep/api"}}
}
]}
Task Definition

73. CLOUDWATCH LOGS
Logs Tab in
the Task
Detail Page
View logs in the ECS or Cloudwatch Console

74. XII. Admin processesRun admin/management tasks as one-off processes

75. Admin / management processes are
inevitable:
• Migrate database
• Repair some broken data
• Once a week move database
records older than X to cold
storage
• Every day email a report to
this person

76. Tools for containers

77. Building Blocks for Containerized 12 Factor
apps
AWS Elastic
Beanstalk
Amazon
SQS
Compute
AWSX-Ray
DeveloperTools
AWS
CodeBuild
AWS
CodePipeline
AWS
Cloud9
AWS
Fargate
Amazon
ECS
Application Integration
Amazon
SNS
Amazon MQ
Logging & Monitoring
Amazon
CloudWatch
AWS
CloudTrail
Amazon
DynamoDB
AmazonS3
Storage & Database
Amazon ElastiCache Amazon RDSAmazon
ECR
Amazon
EKS
AmazonAPI
Gateway
Networking & API Proxy
Elastic Load
Balancing
Amazon
Route 53
AWSStep
Functions

78. Thank you!