Quickly following the rise of micro­services came the rise of containers to help build and deploy micro­services. But how do you manage them effectively to get the best performance while simultaneously reducing cost? Thankfully, there are many solutions out there that can help you orchestrate large clusters of containers to auto­scale up or down. During this hands ­on talk, we will be using three of the most popular open source solutions ­ Kubernetes, Marathon, and Docker Swarm ­ to orchestrate container clusters in order to demonstrate the pros and cons of using each solution. After leaving the talk, you will be able to pick the solution that best fits your needs.

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Container Orchestration
Mariano Gonzalez
Rob Mills
code: http://bit.ly/container-orchestration-code
slides: http://bit.ly/container-orchestration-slides

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Before we get started
Pre-requisites

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Pre-requisites
• Docker Toolbox (http://bit.ly/docker-toolbox)
– docker
– docker-machine
– docker-compose
• Kubernetes (http://bit.ly/kubernetes-install)
– brew install kubernetes-cli
• Git (optional - to pull the code)
– brew install git
• Code examples (http://bit.ly/container-orchestration-code)
– git clone https://github.com/eschizoid/container-orchestration.git
Install (or have installed)

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Who are these guys?

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Mariano Gonzalez
Mariano is a Chicago-based computer geek originally from Mexico. He loves working with
all types of middleware technologies such as Apache Camel, IBM Integration Bus, Mule
and Spring Integration just to mention a few. He has been using Java for almost 10
years, implementing multiple kinds of applications for different business fields (insurance,
banking, and trade shows). Mariano used to work for Peapod.com before joining Uptake.
He enjoyed sharing his knowledge about Java platforms SE/EE and it's huge ecosystem.
mariano.gonzalez.mx@gamil.com
Rob Mills
Rob is a technology enthusiast and born problem solver originally from Boston. His
experience covers the full stack, including mobile applications, rich single page javascript
UIs, e-Commerce applications, enterprise middleware integration applications, and
document management applications for clients and employers in a number of verticals.
He loves sharing his passion for software engineering in all languages but has a
professional background in mostly Java stacks. Rob currently works for Uptake, a
predictive analytics/big data/IoT company, as a Software Engineering Manager.
me@robgmills.com

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1. Frameworks overview
a. Marathon
b. Kubernetes
1. Workshop
a. Marathon
b. Kubernetes
1. Conclusions
2. QA
Agenda

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Why should I care?

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Why should I care?
Is your
(Dev)Ops team
… always putting out fires?
… building special snowflake servers?
… supporting applications that they
have no idea how they work?
… generally overworked (by volume or
by scope)?

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“The Other end of the spear: the tooth-to-tail ratio (T3R) in modern military operations” by John J. McGrath
http://www-cgsc.army.mil/carl/download/csipubs/mcgrath_op23.pdf
3:1
Support : Infantry
Why should I care?
U.S. Military deployments

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Why should I care?
So what if you
could
… allow your DevOps team to focus on
more sustainable infrastructure
approaches?
… have a clear handoff between
operations and developers?
… allow your developers to reliably ship
new changes with minimal DevOps
support?
… decrease the DevOps workload?

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Ok, now I care.
• More reliable deployments - containers are the same throughout the
pipeline
• Narrower DevOps responsibilities - they deliver the underlying hosts
and the frameworks* and nothing else
• Keep application domain knowledge with the application - engineers
can better see and control how their application runs
• Fewer man-hours required to prototype or test new deployments
The Promise
*please use chef, ansible, puppet, salt, CloudFoundry or the like.

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Let’s start at the beginning
Just to level-set everyone

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The Old Old Way of Application deployments
App
OS Kernel
lib
App App App
lib liblib liblib lib lib lib

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App
OS Kernel
lib lib lib
App
lib lib lib
App
lib lib lib
App
lib lib lib
New Old Way

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Definition
orchestration
(noun)
ˌȯr-kə-ˈstrā-shən
the automated arrangement,
coordination, and management of
complex computer systems, middleware
and services
Chicago Coder Conference June 6-8, 2016

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Framework Background

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Framework Background
“an open-source system for automating
deployment, scaling, and management of
containerized applications”
Chicago Coder Conference June 6-8, 2016

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Framework Background
“production-grade container orchestration
platform”
Chicago Coder Conference June 6-8, 2016

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Kubernetes

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So, to rephrase...
a mixed of best practices and an
opinionated technology stack to provide a
robust, scalable way of managing
containers
Chicago Coder Conference June 6-8, 2016

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Kubernetes
• Pods
• Flat Networking Space
• Labels
• Services
• Replication Controllers
• Docker
Key components
Not going to demonstrate today, but come talk to us about it!

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Kubernetes Way
Pod
Proxykubelet
App2
lib lib lib
App1
lib lib lib
cAdvisor
Pod
kube-proxykubelet
App4
lib lib lib
App3
lib lib lib
cAdvisor
kubectl
API’s (Rest)
Replication Controller
(REST)
Scheduling
actuator
Scheduler
OS Kernel OS Kernel
etcd

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Marathon
+ Mesos

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Marathon
a UI for an infrastructure abstraction to
enable running compute units at scale
Chicago Coder Conference June 6-8, 2016

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Marathon
• Mesos
– Master
– Agent(s) (a.k.a. Slave(s))
• Marathon
• Zookeeper
• Docker*
Key components
*Actually optional, but not for the purposes of this presentation

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OS Kernel
Mesos/Marathon Way
Agent
OS Kernel
Agent
OS Kernel
Agent
Master
marathon-lb
lib lib lib
api
lib lib lib App
cURL
api
lib lib lib

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Workshop

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Marathon / Kubernetes Workshop
1. Setup infrastructure
1. Self healing capabilities (Kubernetes)
1. Scale up down the app
1. Blue-Green (Marathon) / Rolling deployments

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Workshop

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Results
...but really, our opinions

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Advantages
Service discovery and replication baked-in
Feature rich command-line client for remote container-level management (kubectl)
Powerful control over multiple-containers services (Pods and Services)
Rolling deployments
GCE integration
Disadvantages
Can only deploy Docker containers
Blue/Green deployments are roll-your-own
Less mature
Can only use etcd (skydns)
Alerts not supported OOTB (however there are many options: Google Cloud Monitoring, Bosun +
InfluxDB, Reimann + InfluxDB)
Can’t modify the running pods/services/containers using the UI
Kubernetes

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Advantages
Requires fewer pieces to get running
Can continue to run Mesos frameworks like Spark and other processes (not Docker-only)
Easy-to-do Blue/Green deployments
Greater compatibility for service discovery frameworks
Full control the deployments via the UI
Disadvantages
Not as much control over multiple-container services
Documentation sometimes sucks and the configuration or execution isn’t always intuitive
Service discovery doesn’t come OOTB
Not backed by Google
Alerts not supported OOTB (and not many options besides Prometheus)
Mesos+Marathon

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So who is the winner?

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• you only have containerized apps
• you are already using Google Compute Engine
• you want to use the kubernetes label-based service-discovery, load-
balancing, and replication control
• you already have monitoring and alerting frameworks
We recommend going with Kubernetes if...

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• you are using any of the Mesos frameworks like
– Hadoop, Storm or Spark for big data processing
– Chronos for time-based scheduling
• you already have service discovery other than etcd
• you’re using any cloud provider other than Google Compute Engine
We recommend starting with Marathon + Mesos if...

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The End?

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But really, here’s what’s coming
+

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https://mesosphere.com/blog/2015/09/25/kubernetes-and-the-dcos/

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Questions?
code: http://bit.ly/container-orchestration-code
slides: http://bit.ly/container-orchestration-slides