DevOps Engineer

☐ Linux & Shell · Required · 6 hrs

File system, permissions, processes, cron, grep, awk, sed. DevOps runs on Linux — every server, every container.

• Linux and Shell Scripting for Data Engineers (Data Engineering): https://chaduvuko.com/learn/data-engineering/linux-shell

☐ Networking · Required · 5 hrs

TCP/IP, DNS, HTTP/S, load balancers, firewalls, VPNs. You will configure VPCs and security groups daily.

• What is a Network? (Networking): https://chaduvuko.com/learn/networking/what-is-a-network
• The TCP/IP Model — How the Internet Works (Networking): https://chaduvuko.com/learn/networking/tcp-ip-model
• DNS — How Domain Names Become IP Addresses (Networking): https://chaduvuko.com/learn/networking/dns
• HTTP and HTTPS — The Protocol Powering the Web (Networking): https://chaduvuko.com/learn/networking/http-and-https

☐ Git & GitHub · Required · 3 hrs

Branching strategies, GitFlow, hooks. Infrastructure code lives in Git just like application code.

• Git and Version Control for Data Projects (Data Engineering): https://chaduvuko.com/learn/data-engineering/git-for-data

☐ Bash + Python · Required · 6 hrs

Automate deployments, write health-check scripts, parse logs. A DevOps engineer who can't script is just a GUI clicker.

• Linux and Shell Scripting for Data Engineers (Data Engineering): https://chaduvuko.com/learn/data-engineering/linux-shell
• Building a CLI Tool (Python): https://chaduvuko.com/learn/python/building-a-cli-tool

☐ Docker · Required · 5 hrs

Dockerfile, layers, multi-stage builds, docker-compose, networking between containers. The foundation of modern deployments.

☐ Cloud (AWS or Azure) · Required · 10 hrs

IAM, VPC, EC2/VMs, S3/Blob, managed databases, security groups. AWS is most common; Azure dominates enterprises.

• AWS Introduction (AWS): https://chaduvuko.com/learn/aws/introduction
• Azure Introduction (Microsoft Azure): https://chaduvuko.com/learn/azure/introduction

☐ CI/CD Pipelines · Required · 6 hrs

GitHub Actions, Jenkins, or Azure Pipelines. Build → test → push image → deploy. The core delivery mechanism.

• DataOps and CI/CD for Data Pipelines (Data Engineering): https://chaduvuko.com/learn/data-engineering/cicd-pipelines

☐ Kubernetes · Required · 15 hrs

Pods, Deployments, Services, Ingress, ConfigMaps, HPA, RBAC. K8s is the operating system of the modern cloud.

☐ Terraform (IaC) · Required · 8 hrs

Resources, modules, state, remote backends, workspaces. Infrastructure as Code is mandatory at $140K+ roles.

• Infrastructure as Code for Data Engineers (Data Engineering): https://chaduvuko.com/learn/data-engineering/infrastructure-as-code

☐ Monitoring & Alerting · Required · 5 hrs

Prometheus, Grafana, ELK stack, alert rules, dashboards. You can't fix what you can't see.

• Data Observability — Metrics, Logging and Anomaly Detection (Data Engineering): https://chaduvuko.com/learn/data-engineering/monitoring-observability

☐ DevSecOps Basics · Recommended · 4 hrs

SAST/DAST in pipelines, secrets management (Vault/AWS Secrets Manager), image scanning. Security moves left.

• DevSecOps — Security Embedded in the Pipeline (Cybersecurity): https://chaduvuko.com/learn/cybersecurity/devsecops

☐ GitOps (ArgoCD / Flux) · Recommended · 5 hrs

Declarative deployments where Git is the single source of truth. Standard at Shopify, Reddit, Gopuff.

☐ Service Mesh (Istio) · Optional · 6 hrs

mTLS, traffic management, observability at the mesh layer. Overkill for most, but asked at senior levels.

☐ SRE Practices · Recommended · 8 hrs

SLI/SLO/SLA, error budgets, runbooks, blameless post-mortems, on-call rotations. Where DevOps meets reliability.