Breakout Session delivered at the AWS Summit in Milan 2017

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Michele Alessandrini, Sr. Solutions Architect
Milan - June 8, 2017
Microservices and Docker
Containers in Production
Tools & Best Practices

2. What to Expect from the Session
• Why containers?
• Amazon ECS
• Task Placement Engine
• Event Stream
• Blox

3. Why containers?

4. What are containers?
OS virtualization
Process isolation
Images
AutomationServer
Guest OS
Bins/Libs Bins/Libs
App2App1

5. Container advantages
Portable
Flexible
Fast
Efficient
Server
Guest OS
Bins/Libs Bins/Libs
App2App1

6. Microservices Architecture

7. What Are Microservices?
“is a software architecture style in which complex
applications are composed of small, independent
processes communicating with each other using
language-agnostic APIs. These services are small, highly
decoupled and focus on doing a small task, facilitating a
modular approach to system-building.” - Wikipedia
https://en.wikipedia.org/wiki/Microservices

8. Order UI User UI
Shipping
UI
Order
Service
User
Service
Shipping
Service
Data
Access
Monolithic Architecture

9. Monolithic Architecture – Scaling

10. Order UI User UI
Shipping
UI
Order
Service
User
Service
Shipping
Service
Microservices Architecture

11. Order UI User UI UI
Order
Service
Service
Shipping
Service
Order UI
Order UI
User UI UIShipping
UI
Order
ServiceOrder
Service
Service
Service
Service
Service
User
Service
Shipping
Service
Microservices Architecture – Scaling

12. Characteristics of Microservice Architectures
Do one
thing wellIndependent
Decentralized
Black box
Polyglot
You build it, you run it

13. Containers are natural for microservices
Simple to model
Any app, any language
Image is the version
Test and deploy same artifact
Stateless servers decrease change risk

14. Server
Guest OS
Bins/Libs
Bins/Lib
s
App2App1
Going from this…

15. Server
Guest OS
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Guest OS
.. to this - is hard!

16. Amazon ECS

17. What is Amazon ECS?
Scalable Container
Management
Flexible Container
Placement
AWS Platform
Integration
Extensible by Design

18. Amazon ECS – Task Example
EC2 INSTANCES
LOAD
BALANCER
Internet
ECS
AGENT
TASK
Container
TASK
Container
ECS
AGENT
TASK
Container
TASK
Container
AGENT COMMUNICATION
SERVICE
Amazon
ECS
API
CLUSTER MANAGEMENT
ENGINE
KEY/VALUE STORE
ECS
AGENT
TASK
Container
TASK
Container
LOAD
BALANCER

19. Amazon ECS - Cluster
EC2 INSTANCES
LOAD
BALANCER
Internet
ECS
AGENT
TASK
Container
TASK
Container
ECS
AGENT
TASK
Container
TASK
Container
AGENT COMMUNICATION
SERVICE
Amazon
ECS
API
CLUSTER MANAGEMENT
ENGINE
KEY/VALUE STORE
ECS
AGENT
TASK
Container
TASK
Container
LOAD
BALANCER

20. Amazon ECS - Task
EC2 INSTANCES
LOAD
BALANCER
Internet
ECS
AGENT
TASK
Container
TASK
Container
ECS
AGENT
TASK
Container
TASK
Container
AGENT COMMUNICATION
SERVICE
Amazon
ECS
API
CLUSTER MANAGEMENT
ENGINE
KEY/VALUE STORE
ECS
AGENT
TASK
Container
TASK
Container
LOAD
BALANCER

22. Amazon ECS - Service
EC2 INSTANCES
LOAD
BALANCER
Internet
ECS
AGENT
TASK
Container
TASK
Container
ECS
AGENT
TASK
Container
TASK
Container
AGENT COMMUNICATION
SERVICE
Amazon
ECS
API
CLUSTER MANAGEMENT
ENGINE
KEY/VALUE STORE
ECS
AGENT
TASK
Container
TASK
Container
LOAD
BALANCER

23. Amazon ECS – Service - Example

24. Amazon ECS: Under the Hood
ALB ALB
AZ 1 AZ 2
user / scheduler
Scheduler
Cluster State Service
Placement Engine
Event Stream

25. Task Placement Engine

26. New Placement Constraints & Attributes
Name Example
AMI ID attribute:ecs.ami-id == ami-eca289fb
Availability Zone attribute:ecs.availability-zone == us-east-1a
Instance Type attribute:ecs.instance-type == t2.small
Distinct Instances type=“distinctInstance”
Custom attribute:stack == prod

27. Anatomy of Task Placement
Cluster Constraints
Custom Constraints
Placement Strategies
Apply Filter
Satisfy CPU, memory, and port requirements
Filter for location, instance-type, AMI, or custom
attribute constraints
Identify instances that meet spread or binpack
placement strategy
Select final container instances for placement

28. Supported Placement Strategies
Binpacking Spread Affinity Distinct Instance

29. Placement Strategy Chaining
Spread tasks across Zones
and Binpack within each Zone

30. New Cluster Query Language

31. Filtering: Match on Instance Family or Type

32. Filtering: Match on Availability Zone

33. Filtering: Match on Multiple Expressions

34. Filtering: Match on Custom Attributes

35. Task Placement Examples

36. g2.2xlarge t2.small t2.micro t2.medium
t2.medium t2.small g2.2xlarge
t2.small
t2.small t2.medium
us-east-1aus-east-1d
Placement: Targeting Instance Type & Zone

37. g2.2xlarge t2.small t2.micro t2.medium
t2.medium t2.small g2.2xlarge t2.small
us-east-1aus-east-1d
g2.2xlarge t2.medium
t2.micro t2.small
us-east-1c
Placement: Spread across Zone and Binpack

38. g2.2xlarge t2.small t2.micro t2.medium
t2.medium t2.small g2.2xlarge t2.small
us-east-1aus-east-1d
g2.2xlarge t2.medium
t2.micro t2.small
us-east-1c
Placement: Affinity and Anti-Affinity

39. Running a Service

40. t2.medium t2.small t2.small
us-east-1aus-east-1d
t2.medium t2.micro t2.small
us-east-1c
Placement: Multiple Services on a Cluster

41. t2.medium g2.2xlarge t2.micro t2.small
t2.small t2.small g2.2xlarge t2.small
t2.small t2.small
g2.2xlarge t2.small
Placement: Services – Distinct Instances

42. Event Stream

43. Consuming Real-time Events

44. Three Steps to Getting Started with Events
Step 1: Create CWE Rule Step 2: Create SNS Topic Step 3: Put Events to SNS

45. Consuming Events for Service Discovery
app1-tst  10.1.0.11
db1-tst  10.1.0.14
app2  10.1.0.16
db2  10.1.0.18
my-app  10.1.0.20
websrv1 10.1.0.1
websrv2 10.1.0.2
websrv3 10.1.0.4
app-dev1 10.1.0.9
app-dev2 10.1.0.5
app-dev3 10.1.0.8
db-dev 10.1.0.19

46. Cesare Navarotto
Chief Operating Officer
Monrif Net S.r.l.
cesare.navarotto@monrif.net

48. The old architecture (2014 - Q2 2016)
100Mbit/s
100Mbit/s
Internet

49. Problems & limitations of the old setup

50. Solution: head in the cloud, feet on the ground!

52. Paas vs IaaS? Why not both at the same time?
+ -
PaaS
● easy and fast to build and
deploy apps
● reliable and scaleable
● cost
● privacy
● risk of vendor lock-in
● lack of customization
IaaS
● full flexibility
● savings potential
● reliable and scaleable
● complex to setup, requires
significant upfront R&D

53. PaaS inside AWS? Convox is the answer!

54. Scaling apps and creating services with Convox

55. Our new infrastructure

56. Our new microservices architecture

57. Some results: fast and stable

58. Just to get an idea of costs vs volumes...

59. The main advantages of the new platform
• operations workload minimized
• easy and safe to deploy new features (rollback in a click) without service
interruptions
• scalable at will
• headless CMS allows for “extreme” frontend development with no impact on
the newsroom
• centralized API for interacting with our content

60. What next? Serverless? Big data? AI?
• Video on Demand on AWS using AWS Step Functions, Amazon Elastic
Transcoder, and AWS Lambda
• Paywall is coming (maybe)… Let’s predict customer churn with Amazon
Machine Learning
• Push notifications service based on readers’ interests using Amazon
DynamoDB and AWS Lambda

62. Introducing Blox

63. What is Blox?
Choice
Control
Developer Experience

64. Building with Blox
scheduler cluster state service

65. Swagger Spec: Cluster State Service

66. Swagger Spec: Daemon Scheduler

67. Contributing to Blox
• Blox is licensed under Apache 2.0
• Open an issue or pull request
• Watch our roadmap on GitHub
• Check out our Gitter channel

68. Thank You