A Practical CI/CD Pipeline for Modern Web Applications

Automate your build, test and deployment processes so web teams can deliver faster.

Introduction

In order to deliver features fast, modern web teams need to implement efficient CI/CD pipelines. These help automate the process of taking code from your commits to your production environment. As a result allowing you to get updates in front of your users quicker and with more safety. This guide covers the basics of what CI/CD is, why it matters and how to set up a pipeline that fits your teams needs. We’ll explain the main stages, how they work and what tools you can use. This is aimed at developers, product managers and engineering leads so no in depth DevOps knowledge is required. We have kept everything simple to make it easy to follow and implement. At the end of this guide you’ll understand how to confidently push your code from your laptop to production fast!

Why have an effective CI/CD Pipeline?

In order to provide a competitive application, having a practical CI/CD pipeline will allow your team to push updates with confidence knowing they’re working correctly. Without automation many teams experience long deployment times, undetected errors and stressful deployments. This means your business isn’t growing as quickly as it could be.

Having an reliable pipeline will help your remote and distributed teams. Everyone can view the build status, test results and deployment history in one place. Businesses who invest into CI/CD often find they deploy new features faster, get back up after issues faster and save time on repetitive manual tasks.

Faster feature delivery

Increased confidence when deploying to production
Improved visibility between distributed teams
Reduced cost of fixing issues
Tighter development and operations alignment.
Speed up your release cycle

By using automated pipelines you can make frequent deployments of small changes. Smaller changes are easier to test and rollback.

Reduce human error
Many processes require manual actions such as copying files or running database migrations. By automating these processes you reduce any errors that could occur from human error.

Supporting remote and distributed teams

Having one pipeline ensures that everyone on the team has access to the same information. Different time zones will not cause any issues with merging, reviewing and deploying your code.

For example, an e-commerce team were able to reduce their time to release from 2 weeks down to 2 days by implementing automated testing and deployment into their Git repository.

Previously if your team did not have CI/CD they might have spent the whole of Friday deploying an update and then also had issues to fix over the weekend. But using CI/CD they can now deploy several times per day.

Key points to remember
CI/CD helps you deliver your code faster.
Automation helps to reduce errors when deploying.
Shared pipelines help increase collaboration.

How CI/CD Pipelines Work

CI/CD pipelines are an automated way of processing your code from commit to deployment. Understanding the pipeline will get you started on creating a practical pipeline for your modern web apps.

When a developer commits code, the pipeline will begin to run. The pipeline will build your application, test your code and prepare to deploy it. Each step acts as a gatekeeper ensuring that only quality code makes it past. If each pipeline step passes your code will be deployed into a staging environment and finally to production. If any step fails your pipeline will halt and send notifications to your team so that you can fix the issue before broken code reaches the user.
This means you can trust that all updates will have a reliable process.

Commit – Pipeline triggered after committing code.
Build – Application built and packaged.
Test – Unit, integration and end-to-end testing.
Deploy – Code is deployed once passed.
Monitor – Performance monitored.

Code Commit & Build

We start with a commit to GitHub/GitLab or other Git provider. Our build tool will download our code, install dependencies and produce a deployment package (such as a Docker image or static bundle).

Automated Testing

Automated testing will be performed during this process. This can find bugs, security issues and performance problems. If any of the tests fail we stop the pipeline and notify the team.

Deployment

Once the code has been approved it is deployed to our staging environment. This will be identical to our production environment. Once the code has passed all final checks we deploy using the same pipeline. We often use deployment strategies such as blue-green or canary.

Example
A team have pushed their React app into GitHub. GitHub Actions will then be used to build their app, run their Jest tests and deploy their build folder to Vercel for their Staging Preview.

Linear pipelines will run one stage at a time. This can be simple however they can be slow. Parallel pipelines will allow you to run your independent stages (such as linting & unit tests) at the same time. Saving you time without compromising on quality.

Summary Key Points
Pipelines help developers to go through the process of building, testing and deploying their code.
Each pipeline stage acts like a quality gate.
If any stages fail then deployment will not happen to keep users safe.

How to Create a CI/CD Pipeline

Getting started with creating a CI/CD pipeline for modern web applications is really straightforward. Start with a basic pipeline and build up.

Pick an appropriate CI/CD platform for your code and tech stack. Write a config file to outline your pipeline. Include your environment variables and secrets to securely connect to cloud services.

Before using it for all of your projects try running it for a basic application. This will help to highlight any issues with your configuration. As your team grows you can then add more features to your pipeline. Such as security tests, performance tests and automatic rollbacks.

Pick a CI/CD platform that suits your repository.
Write a pipeline file (YAML or config).
Add in any necessary environment variables and secrets.
Run a test pipeline on a test project.
Over time add in security and performance tests.

Picking the Right CI/CD for your stack

Some popular choices include GitHub Actions, GitLab CI, Jenkins, Azure DevOps and AWS CodePipeline. Pick a tool that works well with your repository and cloud provider.

Create your first pipeline file

A pipeline file outlines what triggers your pipeline, what jobs are done and what steps. For example you can set your pipeline to trigger on every push to your main branch. Then outline the jobs such as build, test and deploy.

Secrets & environment variables

Never include API keys or database passwords in your pipeline file. Instead use secrets from your CI provider. These are encrypted.

For example a React team might create a .github/workflows/deploy.yml file for installing dependencies, running npm test and deploying to Firebase Hosting for pushes to their main branch.

Self-hosted solutions such as Jenkins will give you more control however you will have to deal with server maintenance. Whereas cloud native solutions such as GitHub Actions are easier to implement and scale. This makes them a good choice for many small/medium web teams.

Summary
Start simple in a sample project.
Pick a service that works with your repo and stack.
Keep secrets safe.

Benefits of a Real CI/CD pipeline
Teams that implement CI/CD into their modern web applications will have some real benefits. These will increase as your pipeline grows.

You’ll be able to deploy faster meaning new features and bug fixes will be available quicker. You’ll have less bugs in production thanks to automated tests. When issues do occur you’ll be able to quickly rollback thanks to automation. You’ll now have documentation by having logs. You’ll know precisely what happened and when it was deployed along with who approved it.

All these benefits means investing in CI/CD is a great choice for any team.

Faster deployment of Features
Better code quality with automated testing
Less downtime with quick rollback
Clear audit logs
More time spent developing features.

Time To Market

By having smaller and more frequent releases you get your features into the hands of users quicker. This means that you’re able to react to customer feedback quickly.

Higher Quality Code

As all pull requests will run automated tests bugs will be found before any code is merged. We can add static analysis and security checks into our pipeline to increase quality.

Quick Rollbacks

If we have issues with a deployment we can roll back to the last stable version within minutes. This means that any bad releases won’t affect users too much.

An example of this is when a media company reduced their average bug escape rates by 40% by introducing automated regression tests into their CI/CD pipeline.

Instead of waiting weeks for manual testing and a large deployment using a continuous delivery approach means we deploy smaller updates every day. This reduces risks and enables us to easily identify issues.

Key Points

Fast deployment and increased quality.
Automated testing to find bugs.
Quick rollback to help reduce any problems in production.

Common Problems and Solutions

The best CI/CD pipelines will have some issues. However, when building your own CI/CD pipeline that works for your team, you should be prepared for possible issues.

Some test cases may be flaky and cause incorrect failures. This can cause issues with the time spent on the project. Security concerns can also arise as there could be secrets left exposed. Finally, as the team grows, the pipeline may start to become slow and hard to manage. Most issues can be easily resolved by improving the way tests are written, managing secrets and creating a modular pipeline.
By solving these issues you can save time.

Flaky tests leading to unreliable results.
Hardcoded secrets leading to security issues.
Slow pipeline due to large codebase.
Complicated configurations not understandable by new team members.
Not monitoring the pipeline for failures.

Flaky tests

A test that doesn't always pass can be fixed by isolating dependencies, using retries and removing non deterministic logic.

Secure secrets

Storing API keys within your code can be risky. It is best practice to store your secrets in an encrypted store provided by your CI platform. This means you can inject the value and not have it shown in your logs or within version control.

Pipeline scalability

As your team grows, having a large monolithic pipeline can slow down your pipeline. By creating smaller modular jobs and caching dependencies you can improve your performance.

An example of this can be seen below. The team had a flaky test in their frontend so they mocked the API response rather than hitting a real server.

By fixing the issues within your pipeline manually you are taking time away from your developers working on new features. Using automation you can retry flaky tests or roll back bad deployments to keep your pipeline running.

Summary
Flaky tests should be fixed or isolated. Secrets must remain encrypted. Having a modular pipeline will help keep your pipeline running quickly as your team grows.

Examples & Tooling Comparison

It can really help teams to see some examples of CI/CD workflows being used for their web applications. This section will provide some example pipelines and outline how they compare to each other.

A React and Node.js application might use GitHub Actions to install dependencies, run unit tests, build the front end and then deploy to a cloud host. Whereas a Python Django application may use GitLab CI to run migrations, run pytest tests and deploy to a Kubernetes cluster.

Ultimately it will depend on what tooling you are using in your repository, your cloud provider and the size of your team. Below are some examples showing different stacks using similar pipeline concepts.

These examples show common patterns within real world scenarios and can be customised for your project.

GitHub Actions (JavaScript/TypeScript)
GitLab CI (DevOps focused, self-hosted GitLab)
Jenkins (Highly customizable)
Azure DevOps (Microsoft focused)
AWS CodePipeline (AWS native)

Example Pipeline for React and Node.js

A GitHub Actions workflow can be created which will run on every push. It will install NPM dependencies, run npm test, build the react application and deploy the static files to Vercel or Netlify.

Example Pipeline for Python Django

A GitLab CI job can be created which will checkout the code, install Python dependencies, run migrations on a test database, run pytest and deploy the container to a Kubernetes cluster.

Comparison Of Popular CI/CD Tools

All of these tools allow for automated builds and deployments to happen, however they differ in how they are set up, priced and how flexible they are.
An example of a pipeline could be:

name: Deploy React App
on:
push:
branches: [main]
jobs:

build-and-deploy:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- run: npm ci
- run: npm test
- run: npm run build
- uses: peaceiris/actions-gh-pages@v3

GitHub Actions is an easy tool to get started with as your code will be stored on GitHub. GitLab CI has the benefit of having some inbuilt DevOps features. Jenkins is very flexible but you will need to manage your own servers. Azure DevOps and AWS CodePipeline are great if your team are already working within those ecosystems.
Key Takeaways
Examples of pipelines
Based on your stack and infrastructure, you can choose your tool
Start with a simple pipeline and add more complicated features as needed

Future Trends In CI/CD For Web Applications

There are always new trends in CI/CD which modern web teams should be aware of. These can create more intelligent, secure and easy to manage pipelines.
AI is becoming more common for creating tests, reviewing code and predicting failures. GitOps is also becoming popular for deploying Kubernetes workloads. GitOps makes Git the source of truth for your infrastructure. Finally security is becoming more prevalent in pipelines with DevSecOps.
These trends all show that pipelines are becoming more automated and will find more issues. Teams who adopt these practices early can give themselves a competitive edge.
Keeping up to date with these trends will help you plan for future improvements.
AI assisted testing and code reviews
GitOps
DevSecOps
Serverless runners
Observability and analytics

AI Assisted Testing

AI tools can help to suggest tests, provide explanations for why tests failed and even suggest small code changes. This reduces manual work for testing and code reviews.

GitOps

GitOps uses Git repos to store your deployment configuration. Automated agents will then create the infrastructure based on the desired state of the repo.

DevSecOps

Automated scanning is carried out for vulnerabilities, dependencies and secrets. Any issues will block deployment.
Example
A team used an AI coding assistant to create unit tests for a new API endpoint.
Comparison
Traditional CI/CD tools will help automate your builds and deployments. AI enhanced CI/CD tools will help with intelligent suggestions and anomaly detection. This will help you fix any issues quicker.
Key Takeaways
AI can help reduce manual testing and code reviews
GitOps allows you to think of infrastructure as code and store it in Git
DevSecOps means security is built into your pipeline

Best Practices For Maintaining A Healthy Pipeline

Your CI/CD pipeline should be regularly maintained to keep it quick, reliable and helpful.
Make sure your pipelines are quick by caching your dependencies, and running tests in parallel. Every stage should be well documented so new team members can understand the pipeline. You should also track pipeline metrics.
If your pipeline breaks it should be treated as a high priority issue. You won’t be able to deploy anything until your pipeline is fixed.
By following these best practices you can ensure your pipeline will help your web application.
Cache dependencies
Run tests in parallel
Document your pipeline and what to do on call
Track metrics
Fix any broken pipelines immediately

Quick And Modular

Reduce the time your pipelines take to run. Split large jobs into smaller steps, cache Node modules or Python packages and run unrelated tests.

Document Everything

Store your pipeline configuration in Git with your application. Provide comments and a README explaining how the pipeline works, who owns it and what to do if it breaks.

Track Metrics And Get Alerts

Use dashboards to track how long your builds take to run and how often they fail. Set up alerts so you know the correct person is informed when the pipeline breaks.
Example
A team reduced their pipeline runtime by caching dependencies and splitting their test suites into parallel jobs. Their pipeline now takes 8 minutes to run, down from 20 minutes.
Comparison
A poorly maintained pipeline will be slow, unreliable and ignored by developers. A well maintained pipeline will be quick, reliable and used everyday to confidently ship code.
Key Takeaways
Quick and modular pipelines encourage frequent code changes
Documenting and storing in Git will help keep your pipeline maintainable
Tracking metrics will stop small issues from turning into big outages

Conclusion

Having a practical CI/CD pipeline for your modern web application will really change how your team delivers software. You will be able to automate testing, building and deployment with confidence.
You now have a clear plan for understanding CI/CD, selecting tools, implementing stages and maintaining your pipeline. Start small and learn from your pipeline runs. As your team become more confident with automation you can scale your pipeline up. The aim isn’t to have a perfect pipeline from day one but have a repeatable process that will help your team deliver better web applications quicker with less headaches and happy users.
Automate your code to production
Select the right tools for your stack
Test early, deploy often and rollback quickly
Document and track your pipeline

Start small and continually improve

Publishing Information

Suggested Tags (Max 4) for DEV.to

ci-cd #devops #webdevelopment #automation

Suggested Meta Description
A practical guide to creating a CI/CD pipeline for your modern web application. We will look at the core stages, tools to use, common issues and best practices for maintaining your pipeline.

Links
No invented links. The article talks about general CI/CD ideas and commonly known tools.
Claims

The example runtimes, reduction in bugs escaping and increased productivity from the team are example scenarios. You should check these stats against your own tools.