About DevOps
DevOps is the practice of bridging software development and IT operations so that
code moves from a developer's laptop to production quickly, safely, and repeatably.
It starts with the Foundations: comfort with Linux,
scripting with Bash and a language like Python or Go, and the
networking concepts (DNS, HTTP/S, load balancers, firewalls) that
everything else sits on top of.
From there, Version control with Git and a hosting platform like
GitHub or GitLab keeps every change tracked and shareable, which sets up the
Containers phase: packaging apps with Docker, then
orchestrating them at scale with Kubernetes and, once a system grows
into many services, managing traffic between them with a service mesh like Istio.
Infrastructure as Code tools such as Terraform and Ansible let you
provision and configure infrastructure the same way you version application code,
which is what makes working across Cloud providers (AWS, Azure, GCP),
serverless platforms, and resilient design patterns like auto-scaling and canary
deployments actually manageable.
Delivery pipelines tie it together: CI/CD tools like
Jenkins or GitHub Actions automate the build-test-deploy cycle, while
GitOps tools like ArgoCD keep a cluster's state in sync with a Git
repo and an artifact registry stores what gets built along the way. Around all of that
sit Secret Management for anything sensitive, and
Observability — metrics, logs, and distributed tracing — so you can
actually see what a running system is doing.
DevOps is less a single tool and more a set of practices and a toolchain that changes
as a team's scale changes. This course walks through that toolchain in the order teams
typically adopt it, so each module builds on the one before it.
Content
13 modules
01
Operating Systems
Linux fundamentals: the file system layout, how processes work, and the permissions model behind almost every server you'll ever touch.
Linux
Processes
Permissions
02
Scripting & Automation
Bash scripting and CLI tools for daily terminal work, plus a general-purpose language — Python or Go — for writing real automation and tooling.
Bash
Python
Go
03
Networking & Protocols
TCP/IP fundamentals, DNS resolution, HTTP/S, and the load balancers, firewalls, and VPNs that shape how traffic actually reaches a service.
TCP/IP
DNS
Load Balancing
Firewalls
04
Version Control & Hosting
Git fundamentals — branching, commits, pull requests — plus hosting a repo on GitHub, GitLab, or Bitbucket and the collaboration workflows built on top.
Git
GitHub
GitLab
05
Containers
Docker fundamentals: building images, running containers, persisting data with volumes, and container networking.
Docker
Images
Volumes
06
Orchestration & Service Mesh
Kubernetes — pods, deployments, services, Helm — for running containers at scale, plus Istio or Linkerd for managing traffic between services once a system grows into many microservices.
Kubernetes
Helm
Istio
mTLS
07
Infrastructure as Code
Provisioning cloud infrastructure declaratively with Terraform, Pulumi, or CloudFormation, then keeping servers configured consistently with Ansible, Chef, or Puppet.
Terraform
Ansible
CloudFormation
08
Cloud Providers
Picking one of AWS, Azure, or GCP to go deep on first: their core compute, storage, and networking primitives.
AWS
Azure
GCP
09
Serverless & Cloud Patterns
Running code without managing servers using Lambda, Cloud Functions, or Azure Functions, plus resilient design patterns like auto-scaling, circuit breakers, and blue-green or canary deployments.
Lambda
Auto-scaling
Canary Deployments
10
CI/CD Pipelines
Automating build, test, and deploy with Jenkins, GitHub Actions, GitLab CI, or CircleCI, so every change ships through the same pipeline.
Jenkins
GitHub Actions
GitLab CI
11
GitOps & Artifacts
Using ArgoCD or Flux to keep a Kubernetes cluster's state continuously synced to Git, plus storing build outputs in Nexus, Artifactory, or a container registry.
ArgoCD
Flux
Artifactory
12
Secret Management
Keeping credentials, API keys, and certificates out of code and config using Vault, AWS Secrets Manager, or SOPS.
Vault
Secrets Manager
SOPS
13
Observability
Monitoring infrastructure with Prometheus, Datadog, or CloudWatch, centralizing logs with the ELK/EFK stack or Loki, and tracing requests across services with Jaeger or OpenTelemetry.
Prometheus
ELK Stack
OpenTelemetry
Projects
6 builds
Docker Tutorial for Beginners [FULL COURSE in 3 Hours]
Go from Docker basics to building images, running multi-container apps with Docker Compose, and pushing to a container registry.
Kubernetes Tutorial for Beginners [FULL COURSE in 4 Hours]
Take a containerized app and orchestrate it: pods, deployments, services, and a hands-on demo project deployed to a local cluster.
GitHub Actions Tutorial - Basic Concepts and CI/CD Pipeline with Docker
Wire up a complete CI/CD workflow that builds a Docker image on every push and pushes it to a private Docker registry.
6 Docker Projects for Absolute Beginners
Six hands-on Docker builds in one session: SSH between two Ubuntu containers, then dockerizing Apache, Nginx, a Flask app, a Node.js app, and a WordPress site.
Complete DevOps + AIOps End-to-End Project
A full project walkthrough from system design foundations through the project workflow, a complete DevOps implementation, and AIOps integration on top.
End-to-End DevOps on a Golang Web Application
A capstone-style build: multi-stage Docker images, Kubernetes manifests, CI with GitHub Actions, CD with Argo CD, Helm charts per environment, an ingress controller, and DNS mapping for the live domain.
What You Can Do After This Course
By the end of the curriculum you'll have shipped three real projects and covered the
full toolchain a professional DevOps role expects. Concretely, you'll be able to:
Operate confidently on Linux — navigate the file system, manage processes and permissions, and automate tasks with Bash.
Reason about networks — DNS, HTTP/S, load balancing, and firewalls, so you can debug connectivity issues instead of guessing.
Containerize and orchestrate applications — build Docker images and deploy them to Kubernetes with pods, deployments, and services.
Provision infrastructure as code — define cloud resources with Terraform and keep server configuration consistent with Ansible.
Work across the cloud — deploy to AWS, Azure, or GCP, use serverless where it fits, and apply resilient design patterns like auto-scaling and canary releases.
Build delivery pipelines — automate build-test-deploy with CI/CD tools, adopt GitOps with ArgoCD or Flux, and manage build artifacts.
Secure and observe production systems — manage secrets safely, and monitor metrics, logs, and traces to see what a running system is actually doing.