The DevOps Journey

From Code to Production: An Interactive Story

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01
Chapter One

The Commit

Every deployment begins with a developer pushing code. But what happens next? In modern DevOps, a single git push triggers an entire automated pipeline that validates, builds, and deploys your application without manual intervention.

Git GitHub Version Control
View IDP Project →
$ git add .
$ git commit -m "feat: add new feature"
[main 7a3b91c] feat: add new feature
3 files changed, 127 insertions(+), 12 deletions(-)
$ git push origin main
Enumerating objects: 11, done.
Counting objects: 100% (11/11), done.
✓ Successfully pushed to main
✓ GitHub Actions triggered
02
Chapter Two

The CI/CD Pipeline

GitHub Actions springs into action. The pipeline validates code quality, runs tests, builds Docker images, and prepares for deployment. Each step must pass before proceeding—preventing bad code from reaching production.

GitHub Actions Docker Automated Testing
View Live CI/CD →

Validation

YAML syntax check, security scan

Build

Docker image creation, dependency install

Test

Unit tests, integration tests

Deploy

Infrastructure provisioning triggered

03
Chapter Three

Infrastructure as Code

Terraform provisions cloud resources automatically. VPCs, load balancers, compute instances—all defined in code. No clicking through consoles. No manual configuration. Infrastructure that's reproducible, versioned, and auditable.

Terraform AWS Azure IaC
View Terraform Code →
$ terraform init
✓ Terraform initialized
$ terraform plan
Plan: 12 to add, 0 to change, 0 to destroy
+ aws_vpc.main
+ aws_subnet.public[0]
+ aws_eks_cluster.main
$ terraform apply
✓ Apply complete! Resources: 12 added
04
Chapter Four

Kubernetes Orchestration

Kubernetes deploys your application across multiple nodes. Three replicas ensure high availability. Rolling updates enable zero-downtime deployments. Health checks automatically restart failed pods. Self-healing infrastructure at scale.

Kubernetes EKS AKS K3s
View Multi-Cloud K8s →

Kubernetes Cluster (3 Replicas)

Node 1
Node 2
Node 3

Traffic distributed across all pods via Service Load Balancer

05
Chapter Five

Service Mesh & GitOps

Istio adds automatic mTLS encryption between services. ArgoCD ensures GitOps workflows—your Git repository is the single source of truth. Traffic management, canary deployments, and distributed tracing all come built-in.

Istio ArgoCD GitOps mTLS
View Service Mesh →
🔒 Istio Service Mesh Status
✓ mTLS enabled: All services encrypted
✓ Traffic routing: Canary 10% / Stable 90%
✓ Distributed tracing: Jaeger active
📊 ArgoCD Sync Status
✓ Git repo: https://github.com/.../k8s-manifests
✓ Sync status: Synced (auto-sync enabled)
✓ Health: All resources healthy
06
Chapter Six

Full Observability

Prometheus scrapes metrics. Grafana visualizes dashboards. Loki aggregates logs. Jaeger traces requests across microservices. When something breaks at 3 AM, you know exactly what, where, and why—reducing MTTD from 45 minutes to 13 minutes.

Prometheus Grafana Loki Jaeger
View Observability Stack →
Request Rate
1.2K/s
Error Rate
0.01%
Latency (p95)
142ms
Uptime
99.95%