This document provides an overview of running microservices on Amazon ECS. It begins by defining microservices and describing the challenges of managing them at scale. It then introduces Amazon ECS as a way to easily manage containers across a fleet of servers. Key features of ECS discussed include scalable and flexible container placement, integration with other AWS services for tasks like load balancing, and clustering containers together for management. The document also covers how to address microservices challenges with ECS, such as using services for discovery and deployment, CloudWatch for monitoring, and third party tools for additional functions. Continuous delivery options with Jenkins and Shippable are presented as well.

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Pierre Steckmeyer, Solutions Architect
April 28th, 2016
Running Microservices on
Amazon ECS

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

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 UIShipping
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. What are Microservices challenges?
Resource and State Management
Data Management
Monitoring
Service Discovery
Deployment

12. What are Microservices challenges?
Resource and State Management
Data Management
Monitoring
Service Discovery
Deployment

13. Amazon EC2 Container Service

14. 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

15. Server
Guest OS
Bins/Libs Bins/Libs
App2App1
Managing one host is straightforward

16. 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

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 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
Data 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 Amazon 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
Data 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
DNS interface for cross-host container communication
Gossip protocol to share grouped updates
Overlay network between hosts

34. Service Discovery with Weaveworks

35. Service Discovery and Configuration
Management with Consul
Three main components:
• Consul agent - Runs on each node, responsible for checking the
health of the services and of the node itself.
• One or more Consul servers - Store and replicate data, leader
elected using the Raft consensus algorithm
• Registrator agent - Automatically register/deregisters services
based on published ports and metadata from the container
environment variables defined in the ECS task definition

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

37. What are Microservices challenges?
Resource and State Management
Data 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
AZ 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. microservicesdevelopers delivery pipeline
Microservices development lifecycle
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. Continuous Delivery to ECS with Jenkins
4. Push image to
Docker registry
2. Build image
from sources 3. Run test on image
1. Code push
triggers build
5. Update Service
6. Pull image
4. Push image to
Docker registry

46. Continuous Delivery to ECS with Jenkins
Easy Deployment
Developers – Merge into master, done!
Jenkins Build Steps
Trigger via Webhooks, Monitoring, Lambda
Build Docker image via Build and Publish plugin
Push Docker image into Registry
Register Updated Job with ECS API

47. ECS CI/CD Partners

48. Continuous Delivery to ECS with Shippable

49. Demo

50. Demo
TaskTask
Task

51. Thank you!