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Containers @ Netflix
How they add to a proven cloud architecture
https://www.flickr.com/photos/hinnosaar/2655128664
Datacenters
Java monolithic app
Oracle database
AWS cloud
Java microservices
Cassandra
Netflix Open
Source Software
http://netflix.github.io
Containers @ Netflix
How they add to a proven cloud architecture
batch applications
Multi-tenant (cgroups/Mesos)
historically used for batch
Linux cgroups
What do batch users want?
● Simple shared resources, run till done, job files
● NOT
○ EC2 Instance sizes, autoscaling, AMI OS’s
● WHY
○ Offloads resource management ops, Simpler
Titus
Batch
Job Management
Resource Management & Optimization
Container Execution
Integration
Workflow, Data Analysis, Adhoc
Upstream Systems
Netflix Batch Job Examples
● Algorithm Model Training (with GPU’s)
Netflix Batch Job Examples
● Media Encoding
● Digital Watermarking
1 1
Netflix Batch Job Examples
Open Connect
CDN Reporting
Adhoc
Reporting
Lessons Learned from Batch
● Docker helped generalize use cases
Lessons Learned from Batch
● Docker helped generalize use cases
● Advanced scheduling required
Lessons Learned from Batch
● Docker helped generalize use cases
● Advanced scheduling required
● Initially ignored failures (with retries)
● Docker helped generalize use cases
● Advanced scheduling required
● Initially ignored failures (with retries)
● Time sensitive batch came later
Lessons Learned from Batch
Current Container Usage - Batch
● 100 containers / hour
● Peaks of 1000’s per hour
● Large spikes of CI testing and Digital Watermarking
A random day’s worth of containers
service applications
Why Services in containers?
Theory Reality
“Why is Apache and Tomcat running on
my NodeJS server”
“Why is Apache and Tomcat running on
my NodeJS server”
Problem:
BaseAMI optimized for Java, not
easily customizable
“Why do I need java, gradle, ospackage
after my non-Java build?”
“Why do I need java, gradle, ospackage
after my non-Java build?”
Problem:
Reuse of Java-centric AMI tooling
“I want an instance with a single core to
run my lightweight server”
“I want an instance with a single core to
run my lightweight server”
Problem:
Small instances are not reliable
Enter Docker
● Have a new language?
● Have a build tool you like?
● Want to resource isolate easily?
Come one, come all
Services are just long running batch?
Services
Job Management
Resource Management & Optimization
Container Execution
Integration
Service Apps
Batch
Services more complex
● Services resize constantly and run forever
○ Autoscaling
○ Hard to upgrade underlying hosts
Services more complex
● Services resize constantly and run forever
○ Autoscaling
○ Hard to upgrade underlying hosts
● Have more state
○ Ready for traffic vs. just started/stopped
○ Even harder to upgrade
Services more complex
● Services resize constantly and run forever
○ Autoscaling
○ Hard to upgrade underlying hosts
● Have more state
○ Ready for traffic vs. just started/stopped
○ Even harder to upgrade
● Existing well defined dev, deploy, runtime & ops tools
Real networking is hard
Multi-tenant
Need IP per container - in VPC
Using security groups
Using IAM roles
Considering network resource isolation
Solutions
● VPC Networking driver
○ Supports ENI’s - full IP functionality
○ Scheduled security groups
○ Support traffic control (isolation)
● EC2 Metadata proxy
○ Adds container “node” identity
○ Delivers IAM roles
Reuse existing infrastructure services
VMVM
EC2
AWSAutoScaler
VMs
App
Cloud Platform
(metrics, IPC, health)
VPC
Netflix Cloud Infrastructure (VM’s + Containers)
Atlas Eureka Edda
Enable them for containers
VMVM
EC2
AWSAutoScaler
VMs
App
Cloud Platform
(metrics, IPC, health)
VPC
Netflix Cloud Infrastructure (VM’s + Containers)
VMVM
Atlas
TitusJobControl
Containers
App
Cloud Platform
(metrics, IPC, health)
Eureka Edda
VMVM
Batch
Containers
Spinnaker
Deploy based
on new images
tags
Basic resource
requirements
IAM Roles & Sec
Groups per
container
Deploy
Strategies
Same as VM’s
Easily see
health &
discovery
Current Container Usage - Service
● Still small - 100’s of containers
● NodeJS Device UI Scripts Apps
● Stream Processing Jobs - Flink
● Various Internal Dashboards
developer experience
● Consistent Mac setup
● Consistent workflows
● Netflix integration
The Docker experience
NEWT (Netflix Workflow Toolkit)
dev machine bootstrap
project scaffolding
setup dev pipelines
run locally
build history
start pipeline
beyond java
beyond java
Node.js support
before Newt:
● Install Java
● Install Nebula (Netflix Gradle)
● Add a build.gradle
● Run gradlew wrapper
● Add deb instr to build.gradle
● Install Vagrant + VBox
● Test deb locally
● Create Stash repo
● Create Jenkins job
● Create Spinnaker pipelines
● git push
after Newt:
● Install Newt
● newt init --app-type nodejs
● git push
Nebula ospackage is
hidden inside a local
Docker container
managed by Newt
https://en.wikipedia.org/wiki/Data_visualization#/media/File:Social_Network_Analysis_Visualization.png
dependencies @ scale
Project Niagara
100,000 builds a day, peak
where are we going?
Future of containers @ Netflix
● More scale!
● Guaranteed capacity (service)
● Fair scheduling (batch)
● Local integration test env (devex)
● Next generation CI (devex)
● Internal RI spot market of trough
Questions?

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