Platform Engineer

☐ Linux & Networking · Required · 6 hrs

OS internals, kernel networking, eBPF basics, performance tools. Platform engineers need to understand what runs underneath containers.

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

☐ Go or Python · Required · 8 hrs

Write platform tooling, CLI tools, Kubernetes controllers. Go is the language of the cloud-native ecosystem.

• What is Python? Setup & Your First Program (Python): https://chaduvuko.com/learn/python/what-is-python-setup
• Functions — Defining, Parameters, Return Values (Python): https://chaduvuko.com/learn/python/functions

☐ Git & GitOps · Required · 3 hrs

Everything as code. The platform itself is software — treat it that way.

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

☐ Docker & OCI · Required · 4 hrs

Container internals, image building best practices, multi-arch builds, container security scanning. The container is the unit of deployment.

☐ Kubernetes (Deep) · Required · 20 hrs

Operators, CRDs, admission webhooks, scheduler, etcd, networking plugins (CNI), storage (CSI), multi-tenancy. Platform teams own the cluster.

☐ Terraform & Pulumi · Required · 8 hrs

Modules, remote state, workspaces, policy as code. The platform team provisions all cloud resources.

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

☐ CI/CD Platform · Required · 7 hrs

GitHub Actions, Tekton, ArgoCD, progressive delivery (Argo Rollouts). Design the delivery platform other engineers use.

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

☐ Observability Platform · Required · 8 hrs

Deploy and operate Prometheus, Grafana, Loki, Tempo at cluster scale. Platform engineers run the tools other teams rely on.

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

☐ Service Mesh (Istio/Linkerd) · Recommended · 7 hrs

mTLS, traffic management, observability, canary deployments at the mesh layer. Complex but powerful for microservices at scale.

☐ Platform Security · Required · 6 hrs

OPA / Kyverno policies, RBAC, secrets management (Vault), image signing (Cosign), SBOM. Security is a platform concern.

• Security Architecture — Defense in Depth and Zero Trust (Cybersecurity): https://chaduvuko.com/learn/cybersecurity/security-architecture
• DevSecOps — Security Embedded in the Pipeline (Cybersecurity): https://chaduvuko.com/learn/cybersecurity/devsecops

☐ Developer Experience · Required · 5 hrs

Developer portals (Backstage), self-service scaffolding, golden path templates, feedback loops. A platform nobody uses is wasted infrastructure.

☐ Internal Dev Platform (IDP) · Recommended · 8 hrs

Platform APIs, environments on demand, cost showback, DORA metrics. The IDP is the product the platform team ships.

☐ FinOps & Cost Engineering · Recommended · 4 hrs

Kubecost, cloud cost allocation, spot/preemptible automation, rightsizing. Cloud bills at scale are an engineering problem.

• Cost Optimization (Snowflake): https://chaduvuko.com/learn/snowflake/cost-optimization
• Performance Tuning and Cost Optimisation (Data Engineering): https://chaduvuko.com/learn/data-engineering/performance-tuning