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Hey everyone, welcome back!
Today we’re diving into one of the most important concepts in modern software development — the CI/CD pipeline. If you’ve ever heard teams talk about continuous integration or continuous deployment and wondered what exactly happens behind the scenes, this video will break it down clearly, visually, and step by step.
YouTube Video
So let’s start with the big picture and then walk through each stage in the pipeline.
What is CI/CD?
CI/CD stands for Continuous Integration and Continuous Delivery or Continuous Deployment. It’s a set of practices that help development teams deliver code changes more frequently and reliably.
The idea is simple: when a developer writes code, it should automatically be tested, built, and either delivered to staging or deployed to production — without manual steps slowing things down.
CI/CD automates that flow — making releases faster, safer, and more consistent.
CI/CD Pipeline Workflow
1. Source Code Management (Git)
Everything begins with code.
Developers write their code and push it to a version control system like GitHub, GitLab, or Bitbucket. Think of this as the starting point of the pipeline.
Once the code is committed, it triggers the pipeline automatically. This is usually set up using a webhook that listens for changes in the repository — like when someone pushes a new feature or fixes a bug.
This auto-triggering is a critical part of Continuous Integration.
2. Build Stage
Next comes the Build stage.
This is where the system compiles the code, installs dependencies, and prepares the application into an executable format.
If you’re using Java, this is where Maven or Gradle builds the JAR or WAR file. In Node.js, it might run npm install and bundle everything.
The goal is to make sure the code compiles correctly, and the application can actually run. If the build fails here, the pipeline stops and notifies the developers.
3. Automated Tests
Once the build is successful, the pipeline moves on to automated testing.
This is where unit tests, integration tests, and sometimes even UI tests are run — all without any manual intervention.
If the code passes all the tests, it means it’s stable and doesn’t break existing features.
If any test fails, the pipeline again halts, and the development team is notified to fix the issue before proceeding. This ensures quality and avoids pushing broken code further downstream.
4. Code Analysis and Security Scan
Some pipelines also include static code analysis and security scanning.
These tools analyze the source code to catch bugs, vulnerabilities, or bad practices — even before the application is deployed.
Tools like SonarQube, Checkmarx, or Snyk can flag security issues, outdated libraries, or violations of coding standards.
By catching issues early, teams save time and avoid security breaches down the line.
5. Artifact Repository
Once everything passes, the final build is stored in an artifact repository.
This could be JFrog Artifactory, Nexus, or AWS S3.
Think of it as a library of approved builds. These artifacts are versioned and can be reused across environments — like dev, QA, staging, or production.
This makes it easy to track which build was deployed where and roll back if needed.
6. Deployment to Staging
Next comes Continuous Delivery — where the approved build is automatically deployed to a staging or test environment.
This staging environment is almost identical to production — same configurations, same dependencies.
This allows testers or product managers to manually test the new features in a safe environment, without affecting real users.
Some teams stop here and trigger manual approval for production deployment.
Others go further — and this is where Continuous Deployment comes in.
7. Deployment to Production
In Continuous Deployment, if the staging deployment succeeds, the same artifact is then automatically pushed to production.
That means your users can get the latest updates instantly — without delays or manual processes.
This is often done using deployment strategies like blue-green deployments, canary releases, or rolling updates to reduce downtime and risk.
It’s fast, safe, and incredibly efficient — especially for agile teams who release often.
8. Monitoring and Alerts
The final stage is monitoring.
Once the application is live, monitoring tools like Prometheus, Grafana, Datadog, or New Relic track performance, uptime, errors, and user behavior.
If something goes wrong, alerts are sent out — usually through Slack, email, or an incident dashboard — so the team can respond quickly.
CI/CD doesn’t end at deployment. Observability and feedback close the loop and ensure a healthy system.
Wrap-Up
So to recap — a CI/CD pipeline helps automate the software delivery process, from writing code to releasing it live.
It begins with a Git commit, then moves through build, testing, security scans, artifact creation, staging, and possibly automatic production deployment — all backed by real-time monitoring.
CI/CD gives teams the confidence to deliver high-quality code quickly and reliably.
Keep learning, and keep shipping great software.
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