Based on a tutorial by TechWorld with Nana
If you’ve ever experienced the anxiety of manual deployments, merge conflicts at the worst possible moments, or that sinking feeling when production breaks on a Friday evening, you’re not alone.
I’m breaking down this excellent tutorial from TechWorld with Nana that transforms the nightmare of manual deployment processes into a beautifully streamlined CI/CD pipeline. This isn’t just theory – it’s a practical roadmap from chaos to automation that every development team needs.
Quick Navigation
The Manual Deployment Nightmare
Let’s start with a scenario that’ll make experienced developers cringe. You and your team have finished the first version of your application, and it’s time to deploy.
Here’s what typically happens in manual deployment workflows:
The Manual Process Problems:
- Merge conflicts – Multiple developers pushing changes simultaneously
- Broken main branch – Issues discovered only after merging
- Code freezes – No one can merge until deployment is complete
- Manual testing marathons – Intensive testing sessions before each release
- Human deployment errors – Manual server connections and configuration changes
- Time constraints – Never deploy on Friday evenings (or any evening)
The common thread in all these problems? Human involvement at every critical step. Humans are time-constrained and error-prone, creating bottlenecks throughout the entire deployment process.
My Take:
I’ve seen teams lose entire weekends to deployment issues that could’ve been caught earlier with proper automation. The stress alone costs more than the time investment to build proper CI/CD pipelines.
Continuous Integration: Testing Early and Often
The first major improvement is solving the “bunch of issues every time we merge” problem. Instead of waiting until merge time to discover conflicts and bugs, we shift testing left in our workflow.
CI Core Principles:
- Test individual branches before merging to main
- Run tests on every commit to isolate issues quickly
- Commit smaller changes more frequently instead of large, infrequent pushes
- Integrate code changes often in small, manageable sizes
This approach catches issues faster and earlier in the development workflow. Instead of complex, entangled problems that pile up at release time, you get simpler, isolated issues that developers can fix immediately.
The impact is immediate: no more frustrated developers dealing with other people’s breaking changes, fewer merge conflicts, and significantly less stress piling up before releases.
My Take:
The shift from “integration hell” to smooth, frequent integration is like night and day. Teams that adopt proper CI practices often wonder how they ever worked without it.
Build Automation: Removing Human Bottlenecks
Once we’ve solved the testing-before-merge problem, the next bottleneck is deployment itself. No more code freezes, no more senior engineers manually checking out code and SSH-ing into servers.
The magic word here is automation. When all tests pass on the main branch, your build automation tool takes over:
Automated Build Process:
- Build the app into a Docker image with proper version tagging
- Push the new artifact to your Docker registry
- Connect to your development environment (server or Kubernetes cluster)
- Deploy the newly built container automatically
- Apply any configuration changes or new Kubernetes manifests
# Example Jenkins pipeline step
- name: Build and Deploy
script: |
docker build -t myapp:${BUILD_NUMBER} .
docker push myregistry/myapp:${BUILD_NUMBER}
kubectl set image deployment/myapp myapp=myregistry/myapp:${BUILD_NUMBER}
kubectl rollout status deployment/myapp
Tools like Jenkins, GitLab CI, or GitHub Actions handle all the logic that used to require manual intervention. Yes, there’s initial setup involved, but as Nana points out, building these pipelines from scratch typically takes just 2-3 days when you know what you’re doing.
My Take:
The ROI on automation is incredible. A few days of setup work eliminates hours of manual deployment time every single release cycle. Do the math – it pays for itself almost immediately.
Continuous Delivery: Automated Testing Pipeline
Deploying to dev is just the beginning. We still need to eliminate those intensive manual testing sessions that teams do right before releases.
Instead of waiting for release time to do thorough end-to-end testing, we test every time code changes get merged to main. But here’s the key: we don’t do any of this manually.
Automated Testing Types:
- End-to-end tests – Full application workflow testing
- Integration tests – Database and service connectivity validation
- Security tests – Dynamic application security testing (DAST)
- Performance tests – Load and stress testing
- Compliance tests – Regulatory and policy validation
These tests run against the actual deployed application in a running environment, validating not just code functionality but also configuration, infrastructure, and integrations.
The workflow progresses through stages: dev environment → staging/test environment, with validation at each stage. This staged approach is called continuous delivery (CD), giving us the complete CI/CD acronym.
My Take:
Writing comprehensive automated tests requires upfront investment, but consider this: those tests run multiple times per week, saving hours of manual testing across months and years. The math strongly favors automation.
Continuous Deployment: All the Way to Production
At this point, your code has been extensively tested through multiple environments. Why stop at staging? Let’s take the automation all the way to production.
After staging validation, you might run additional performance tests, compliance checks, and security validation. Often there’s a manual approval step – not because the deployment is manual, but because business stakeholders want final sign-off.
Production Deployment Options:
- Manual gate – Single click approval to deploy
- Fully automated – Deploy immediately after all tests pass
- Scheduled deployments – Deploy at predetermined times
Even with a manual confirmation step, the actual deployment logic remains automated. A non-technical decision maker can click “deploy” and the CI/CD pipeline executes all the production deployment steps automatically.
This progression from continuous delivery to continuous deployment represents the full automation of your release pipeline from code commit to production.
Advanced Deployment Strategies
Even with extensive testing, there’s always a small chance something could slip through to production. Advanced deployment strategies minimize this risk even further.
Canary Deployment
Roll out new features progressively to reduce risk:
Canary Process:
- 1-5% of users get the new version initially
- Monitor for issues for a set period (e.g., 1 hour)
- Gradually increase to 10%, then 20%, etc.
- Full rollout only after confirming stability
Blue-Green Deployment
Maintain two identical production environments for instant fallback:
Blue-Green Setup:
- Blue environment runs current production version
- Green environment runs new version being deployed
- Traffic switching happens instantly between environments
- Immediate rollback if issues are detected
Both strategies require monitoring setup to detect issues automatically, but they provide incredible peace of mind for production deployments.
My Take:
The confidence boost from proper deployment strategies can’t be overstated. When you know you can rollback instantly or limit blast radius, you naturally deploy more frequently – which is exactly what high-performing teams do.
Why CI/CD Is Worth the Investment
This transformation from manual chaos to automated efficiency represents the core of DevOps. It’s not just about tools – it’s about eliminating manual workload and accelerating the entire development process.
CI/CD Benefits:
- Eliminates human errors in deployment processes
- Removes bottlenecks from senior team members
- Increases deployment frequency through reduced risk
- Improves confidence in releases through extensive automated testing
- Reduces stress for development teams
- Enables faster feature delivery to users
As Nana emphasizes, CI/CD is so fundamental that it should be the context for learning all other DevOps tools. Whether you’re working with Docker, Kubernetes, monitoring, or infrastructure automation, it all serves the greater goal of reliable, automated software delivery.
The initial investment in pipeline setup pays dividends immediately and compounds over time. Teams that implement proper CI/CD practices often wonder how they ever functioned without them.
