SlideShare a Scribd company logo
Docker as super
binary
Infradel Team
Is Docker new to
you?
It is a container, I know, but then...
Motivations
Motivations - What we had
python 2.7
modules
openssl
xmlsec1
manually install produces
artefact
pipeline
manually config
on CI server
agent1
agent2
agent3
devticketops
devsudo
git
server app A
server app B
server app C
Toolset Approach
● minimize the need to touch
or change the CI agent
● allow self-service build
environments
Toolset
Goals:
● the build environment that
runs on developer machine
runs everywhere
● can build any version of
anything
● standardized
environment to bring
speed and quality to
the development
process
What we have done
Motivations - What we had
python 2.7
modules
openssl
xmlsec1
manually install produces
artefact
pipeline
manually config
on CI server
agent1
agent2
agent3
devticketops
devsudo
git
server app A
server app B
server app C
What we envisioned
builds toolset
container
produces
artefact
pipeline
manually config
on CI server
agent1
agent2
agent3
git
servers app A
servers app B
servers app C
commit Dockerfile
on git repo
python 2.7
modules
openssl
xmlsec1
What we have done
builds toolset
container
produces
artefact
pipeline
manually config
on CI server
agent1
agent2
agent3
git
servers app A
servers app B
servers app C
commit Dockerfile
on git repo
Examples
CloudFormation container
● python
● py-pip
● bash
● awscli
● boto3
Ansible container
● python(2.7)
● py-pip
● openssl
● ca-certificates
● bash
● git
● openssh
● bash
● awscli
● ansible
● boto3
Examples - super binary containers
Examples - pipeline implementation
Examples - pipeline implementation
● costs minimized by sharing
one CI agent instance
between several teams
● not a blocker to others
anymore
Toolset
Pros:
● very small administration
overhead on the CI agent
● not limited by the linux
distro the CI agent runs on
● easy to keep local dev
and prod identical
● makes troubleshooting way
more complex
Toolset
Cons:
● learning curve (new
mindset, new tools, etc.)
● now you have to use
containers for all CI jobs
● performance issues
on the agent instance
affects all the teams
● pay attention to the order
of the instructions inside
your dockerfile
Toolset
Lessons learned:
● use small bash scripts for
your docker build and run
commands
● use small bash scripts to
handle environment
variables
● keep docker up to
date
● docker compose?
Toolset
Next steps:
● secrets management
(credstash?)
● better environment
variable management
Questions?
Contact us:
twitter.com/acacs
twitter.com/datherra
twitter.com/thoughtworks_pt
THANK YOU

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Docker for tooling

  • 2. Is Docker new to you? It is a container, I know, but then...
  • 4. Motivations - What we had python 2.7 modules openssl xmlsec1 manually install produces artefact pipeline manually config on CI server agent1 agent2 agent3 devticketops devsudo git server app A server app B server app C
  • 6. ● minimize the need to touch or change the CI agent ● allow self-service build environments Toolset Goals: ● the build environment that runs on developer machine runs everywhere ● can build any version of anything ● standardized environment to bring speed and quality to the development process
  • 8. Motivations - What we had python 2.7 modules openssl xmlsec1 manually install produces artefact pipeline manually config on CI server agent1 agent2 agent3 devticketops devsudo git server app A server app B server app C
  • 9. What we envisioned builds toolset container produces artefact pipeline manually config on CI server agent1 agent2 agent3 git servers app A servers app B servers app C commit Dockerfile on git repo python 2.7 modules openssl xmlsec1
  • 10. What we have done builds toolset container produces artefact pipeline manually config on CI server agent1 agent2 agent3 git servers app A servers app B servers app C commit Dockerfile on git repo
  • 12. CloudFormation container ● python ● py-pip ● bash ● awscli ● boto3 Ansible container ● python(2.7) ● py-pip ● openssl ● ca-certificates ● bash ● git ● openssh ● bash ● awscli ● ansible ● boto3 Examples - super binary containers
  • 13. Examples - pipeline implementation
  • 14. Examples - pipeline implementation
  • 15. ● costs minimized by sharing one CI agent instance between several teams ● not a blocker to others anymore Toolset Pros: ● very small administration overhead on the CI agent ● not limited by the linux distro the CI agent runs on ● easy to keep local dev and prod identical
  • 16. ● makes troubleshooting way more complex Toolset Cons: ● learning curve (new mindset, new tools, etc.) ● now you have to use containers for all CI jobs ● performance issues on the agent instance affects all the teams
  • 17. ● pay attention to the order of the instructions inside your dockerfile Toolset Lessons learned: ● use small bash scripts for your docker build and run commands ● use small bash scripts to handle environment variables ● keep docker up to date
  • 18. ● docker compose? Toolset Next steps: ● secrets management (credstash?) ● better environment variable management