Hey there! Let‘s talk through a super important devops concept that often trips up those just getting started – how to automate your workflows using pipeline as code.
Now I know that title sounded like gibberish if this is your first rodeo, so let‘s break things down piece by piece and see how pipelines provide speed and reliability.
What on Earth is CI/CD…and Why Care?
CI/CD refers to continuous integration and continuous delivery. These joined at the hip practices transformed application development by allowing seamless, automated flows from code to production.
Continuous integration means developers frequently merge code which triggers automated build and test processes. This catches errors early to reduce headaches down the line.
Continuous delivery takes the handoff from CI and automatically pushes the code through staging, testing and approvals to go live in production with a single button press.
This automation allows us to release innovative features faster and more reliably to delight our customers – everyone wins!
So why is this often called infrastructure as code? Because just like we define servers, networks and environments in configuration files (rather than manually clicking around), CI/CD allows codifying release workflows.
Introducing CI/CD Pipelines
The automated process that ships code from laptop to server is called a pipeline.
Pipelines provide the foundation for scaling infrastructure reliably. They are the assembly lines of the modern tech factory!
Here‘s an overview of critical stages in a deployment pipeline:
Instead of manually running through these steps, pipelines enable automation by codifying workflows.
According to Gartner, over 70% of organizations now leverage CI/CD pipelines to accelerate delivery.
Transitioning to Pipeline as Code
Many CI/CD tools like Jenkins expose visual editors to model pipelines through dragging and linking stages.
But there is a better way…
Defining the deployment workflow in text configuration files allows treating it as you would any other code:
- Store it in source control
- Maintain revisions
- Enable collaboration
This pipeline as code approach provides consistency and control instead of reliance on flaky graphical interfaces.
Let‘s look at open source stalwart Jenkins as an example pipeline as code implementation.
Jenkins Pipeline 101
Released in 2011, Jenkins pioneered build automation and now also leads the way on enterprise pipelines via their domain specific language.
Architecturally, Jenkins is basically just a server that allows scripting workflows by stitching together plugins.
With 2000+ plugins available their platform can handle incredibly complex scenarios – but also presents security considerations requiring diligence to patch and harden appropriately.
Let‘s explore Jenkins pipeline syntax and build your intuition for codifying workflows…
Declarative vs Scripted Syntax
The Jenkins DSL provides two flavors:
Declarative – A clean, structured format perfect for getting started:
pipeline {
agent any
stages {
stage(‘Build‘) {
steps {
// do build
}
}
stage(‘Test‘) {
steps {
// test things
}
}
}
} Scripted – A lower level syntax granting complete control via Groovy:
node {
stage(‘Build‘) {
// build app
}
stage(‘Test‘) {
// test all teh things
}
}Scripted syntax allows unlimited customization leveraging the full power of programming – but can get messy fast.
Let‘s look at some real world examples…
Jenkins Pipeline Example Walkthrough
Here is an example pipeline script implementing best practices:
// parameters allow customizing per execution
parameters {
string(name: ‘GIT_BRANCH‘, defaultValue: ‘master‘, description: ‘Git branch to build‘)
}
pipeline {
agent any
options {
buildDiscarder(logRotator(numToKeepStr: ‘20‘)) // keep last 20 builds
timeout(time: 15, unit: ‘MINUTES‘)
}
triggers {
cron(‘H */6 * * *‘) // trigger every 6 hours
}
stages {
// lint code
stage(‘Lint‘) {
steps {
tee(‘logs/lint.log‘) { // capture output
sh ‘make lint‘
}
}
}
// run automation suite
stage(‘Acceptance Tests‘) {
steps {
sh ‘make acceptance‘ // execute tests
}
}
}
post {
always {
junit ‘reports/*.xml‘ // publish test reports
}
changed {
echo ‘Only runs on job status change‘
}
}
} Let‘s break down what‘s happening:
- Parameters allow customization per run
- Triggers can schedule automated executions
- The pipeline section defines workflow stages
- Post conditions handle outcomes
This shows how declarative pipelines allow full control while maintaining readability.
You could model exponentially more complex workflows using Jenkins capabilities – but things would get unwieldy fast. That‘s why…
Pipeline Code Best Practices
When codifying pipelines, adhere to standard coding best practices:
- Modularize code into reusable libraries
- Separate configuration from logic
- Handle errors gracefully
- Make pipelines easy to configure
- Restrict access appropriately
Also test automated pipelines rigorously since they touch production systems.
Following these principles will keep things maintainable as complexity increases.
Now that you have context on Jenkins specifics, let‘s zoom out…
Evaluation: Jenkins vs Other Tools
While feature-packed, Jenkins has downsides some organizations can‘t stomach:
- Complexity & customization difficulty
- Resource heavy Java dependency
- Not inherently multi-tenant
GitHub Actions present an appealing alternative providing native pipelines leveraging easy to read YAML syntax. Tight integration with GitHub provides a streamlined experience.
On the enterprise scale, Azure DevOps shines by blending integrated application lifecycle management with cloud-scale pipelines supported by the Microsoft stack.
TravisCI offers a simplistic SaaS experience popular with open source projects. TeamCity also keeps thing simple while allowing enterprise scale.
My recommendation? Start simple but ensure your solution has room to grow.
Okay, I know we just covered a ton of ground. Let‘s shift gears and go broader.
Expanding CI/CD Horizons
We primarily focused on application integration and delivery pipelines to provide solid footing.
But the power of automation extends far beyond deploying web apps. Nearly any workflow can benefit from codified pipelines.
Pipeline Use Cases
While originally focused on software, pipelines now spread to domains like:
Data ops – Apply CI/CD to machine learning and data analytics systems
Database devops – Keep schemas and procedures under version control
Infrastructure ops – Automatically test and release cloud configurations
Security ops – Scan images and configurations pre-production
The rise of GitOps patterns demonstrate tying robust CI/CD pipelines into infrastructure as code tools provides a killer combination!
Integrating Pipeline & Infra as Code
Treating all infrastructure – applications, data models, cloud configs – as code unlocks scale and consistency.
Kubernetes environments shine when pairing reproducible declarative specifications with progressive delivery pipelines.
Tools like Terraform allow codifying cloud infrastructure elegantly. Connected pipelines enable automatically testing and promoting changes through environments.
Similarly, configuration management tools like Ansible benefit immensely from CI/CD. Testing playsbooks against real infrastructure pre-production allows preventing outages.
Maturing Pipeline Strategy
As complexity increases, integrate these advanced concepts:
- Testing pipelines – Unit test pipeline logic!
- Canary deployments – Reduce risk with partial rollouts
- GitOps – Automation inside and outside pipelines
- Trunk based development – Simplify workflows through collaboration
Invest in continually improving pipeline craftsmanship.
The Future of Software Delivery
We covered a ton of ground explaining how pipelines provide the connective tissue between code, testing and deployment – both for applications and infrastructure.
Automating delivery flows provides tremendous leverage. CI/CD pipeline mastery lets developers focus on building business value rather than headaches.
Cloud native architecture patterns fully embrace modern delivery best practices. Kubernetes environments thrive when paired with robust GitOps workflows.
As code drives more of the world, codifying complex continuous integration, delivery and deployment processes makes hitting the big red easy button possible.
Questions? Hit me up on Twitter anytime and let‘s keep the conversation going!
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