Microservices is a software architectural method where you decompose complex applications into smaller, independent services. Containers are great for running small decoupled services, but how do you coordinate running microservices in production at scale and what AWS services do you use? In this session, we will explore the reasoning and concepts behind microservices and how containers simplify building microservices based applications. We will also demonstrate how you can easily launch microservices on Amazon EC2 Container Service and how you can use ELB and Route 53 to easily do service discovery between microservices.

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Matt McClean, AWS Solutions Architect
Igor Serko, Lead Operations Engineer, Lyst
2016-07-07
Deep Dive on Microservices and Amazon ECS

2. What to Expect from this Session
Microservices: What are They?
Challenges of Microservices
Microservices on Amazon ECS
Customer story: Lyst

3. What are Microservices?

4. 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

5. Monolithic vs. SOA vs. Microservices
SOA
Coarse-grained
Microservices
Fine-grained
Monolithic
Single unit

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

7. Monolithic Architecture – Scaling

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

9. Order UI User UI UI
Order
Service
Service
Shipping
Service
Order UI
Order UI
User UI UI
Shipping
UI
Order
ServiceOrder
Service
Service
Service
Service
Service
User
Service
Shipping
Service
Microservices Architecture – Scaling

10. Characteristics of Microservices Architectures
Do one
thing well
Independent
Decentralized
Black box
Polyglot
You build it, you run it

11. Containers are Natural for Services
Simple to model
Any app, any language
Image is the version
Test & deploy same artifact
Stateless servers decrease change risk

12. What are Microservices Challenges?
Resource and state management
Monitoring
Service discovery
Deployment

13. What are Microservices Challenges?
Resource and state management
Monitoring
Service discovery
Deployment

14. Server
Guest OS
Bins/Libs Bins/Libs
App2App1
Managing One Host is Straightforward

15. Managing a Fleet is Hard
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
Server
Guest OS
AZ 1 AZ 2
AZ 3

16. Amazon EC2 Container Service

17. Easily Manage Clusters for Any Scale
Nothing to run
Complete state
Control and monitoring
Scale

18. Scalable

19. Flexible Container Placement
Applications
Batch jobs
Multiple schedulers

20. Designed for use with other AWS services
Elastic Load Balancing
Amazon Elastic Block Store
Amazon Elastic File System
Amazon Virtual Private Cloud
AWS Identity and Access Management
AWS CloudTrail

21. Clusters
Regional
Resource pool
Grouping of container instances
Start empty, dynamically scalable

22. Tasks
Unit of work
Grouping of related containers
Run on container instances

23. Services
Good for long-running applications
Load balance traffic across containers
Automatically recover unhealthy containers
Discover services

24. What are Microservices Challenges?
Resource and state management
Monitoring
Service discovery
Deployment

25. Monitoring with Amazon CloudWatch
Metric data sent to CloudWatch in 1-minute periods and
recorded for a period of two weeks
Available metrics: CPUReservation, MemoryReservation,
CPUUtilization, MemoryUtilization
Available dimensions: ClusterName, ServiceName

26. Monitoring with Amazon CloudWatch

27. Monitoring with Amazon CloudWatch
Use the CloudWatch monitoring scripts to monitor additional
metrics: e.g., disk space
# Edit crontab
> crontab -e
# Add command to report disk space utilization to CloudWatch every five minutes
*/5 * * * * <path_to>/mon-put-instance-data.pl --disk-space-util --disk-space-used --disk-space-avail --disk-path=/ --from-cron

28. Monitoring Amazon ECS with Datadog

29. Monitoring Amazon ECS with Sysdig Cloud

30. What are Microservices Challenges?
Resource and state management
Monitoring
Service discovery
Deployment

31. Service Discovery with ECS Services & Route 53
Route 53 private hosted zone
Set search path on hosts with DHCP option sets
Define ECS services with ELB
Create CNAMEs for each ELB

32. Service Discovery with ECS Services & Route 53
Task
Task TaskTask
ECS
service
Application
router, e.g.
NGINX
Internal ELB with
CNAME, e.g.
api.example.com
Route 53 private
zone, e.g.
example.com

33. Service Discovery with Weaveworks
Overlay network between hosts
DNS interface for cross-host container communication
Gossip protocol to share grouped updates

34. Service Discovery with Weaveworks

35. Service Discovery with Consul
• Distributed Key Value store
• Simple interface - DNS or HTTP
• Health Checks
• Dynamic Configuration Management

36. Service Discovery with Consul
ECSCluster
consul-server
ECS Instance
consul-agent
registrator
ECS Instance
Back end 1
Back end 2
consul-agent
registrator
ECS Instance
Front end
ECSCluster

37. What are Microservices Challenges?
Resource and state management
Monitoring
Service discovery
Deployment

38. Scheduling Containers on ECS
Batch jobs
ECS task scheduler
Run tasks once
Batch jobs
RunTask (random)
StartTask (placed)
Long-running apps
ECS service scheduler
Health management
Scale-up and scale-down
Zone-aware
Grouped containers

39. Scheduling Containers: Long-running App
Optionally run your service behind a load balancer.
ELB currently supports a fixed relationship between the
load balancer port and the container instance port.
If a task fails the ELB health check, the task is killed and
restarted (until service reaches desired capacity).

40. Scheduling Containers: Long-running App
Update service’s task definition (rolling update)
Specify a deployment configuration for your service:
• minimumHealthyPercent: lower limit (as a percentage of
the service's desiredCount) of the number of running
tasks that must remain running in a service during a
deployment.
• maximumPercent: upper limit (as a percentage of the
service's desiredCount) of the number of running tasks
that can be running in a service during a deployment.

41. Scheduling Containers: Long-running app
Deploy using the least space: minimumHealthyPercent =
50%, maximumPercent = 100%

42. Scheduling Containers: Long-running App
Deploy quickly without reducing service capacity:
minimumHealthyPercent = 100%, maximumPercent =
200%

43. Scheduling Containers: Long-running App
Blue-Green Deployments
• Define two ECS services
• Each service is associated w/ ELB
• Both ELBs in Route 53 record set
with weighted routing policy, 100%
Primary, 0% Secondary
• Deploy to blue or green service and
switch weights
TaskTask
Route 53
record set
with
weighted
routing
policy
0%
100%

44. Microservices Development Lifecycle
developers delivery pipelinemicroservices
build pipeline
build pipeline
build pipeline
build pipeline
build pipeline
build pipeline
build pipeline
build pipeline
build pipeline
build pipeline
build pipeline
build pipeline
build pipeline
build pipeline
build pipeline

45. Deployment pipeline for Amazon ECS
https://stelligent.com/2016/06/10/automate-amazon-ec2-container-service-provisioning-and-orchestration-using-
cloudformation-and-aws-codepipeline/

46. ECS CI/CD Partners

47. Microservices at Lyst
Igor Serko
Lead Operations Engineer
Lyst Ltd

48. What is Lyst?
Fashion startup
London and New York
Established in 2010
AWS
Python / Django framework

49. Why Microservices?
Monolith codebase problems
Dependency on ops team
Team growth
Self-sufficient developers

50. Docker and the 12
factor application
Less stress on platform team
Consistent environments
Moved to Docker early on
Used 12 factor principles
Library dependencies

51. Splitting the monolith
New projects as microservices
Deployment is an issue

52. What do we want?
Developers deploy by themselves
Least amount of infrastructure management
Plug and Play

53. AWS ECS
Released end of 2014
Runs Docker containers
Have to use APIs
Node scaling using EC2 Auto Scaling
ECS Task scaling using Cloudwatch metrics

54. Empire
Actively developed by Remind
Lightweight
Simple to use
Developer controlled scaling
Provides log streaming
Built on top of AWS ECS

55. Applications
12 Factor application
Service definition using Procfile
CI builds and pushes Docker images

56. Production
30 applications
Developers deploying their apps
Service Discovery using ELB
Developers responsible for app health
Faster development cycle
Desired Features

57. Thank you!

58. Please remember to rate this
session under My Agenda on
awssummit.london
@iserko @matthewmcclean