Learning path / 10 published lessons
Cloud infrastructure and delivery
Connect containers, Kubernetes, cloud services and infrastructure-as-code to operational decisions. Compare resource identity, networking, persistent state and rollout boundaries rather than copying commands blindly.
What you’ll work toward
- A Dockerfile EXPOSEs 8000 and copies site-packages but not console scripts. Why might the image start fail?
- Explain the version and execution boundaries before applying the examples
- Trace Pod ownership, scheduling, probes and Service endpoint eligibility
- Distinguish rejected Deployment selectors from disconnected Service selectors
Completion is stored on this device only. Nothing is locked; start where it makes sense.
Start this pathBefore the first lesson
- Basic programming and HTTP; follow the chapter or cloud-track sequence
These are the starting lesson’s prerequisites, not requirements for every advanced topic below.
How to practise this subject
Review a proposed deployment without provisioning it: identify credentials, permissions, network exposure, cost signals and a rollback plan. Execute only in a separately authorized, isolated environment.
- 01
Docker — Images, Layers, Dockerfile, Networking
Understand container images, cache invalidation, runtime isolation and service networking through a multi-stage Python reference design and measured acceptance criteria.
- 02
Kubernetes I — Pods, Deployments, Services
Kubernetes without the mysticism — Pods run containers, Deployments keep N of them alive, Services give them a stable IP. Reason through and optionally deploy a local app, with selectors, probes and rollout failure analysis.
- 03
Kubernetes II — ConfigMaps, Secrets, HPA, Network Policies
Connect configuration, secret rotation, autoscaling and network isolation to a complete reference workload, then reason through controller and recovery failures.
- 04
Azure Cloud — Identity, Storage, Networking, App Service
The four pillars of every real Azure workload — Entra ID + RBAC, Storage & Cosmos, VNets & Private Endpoints, App Service & Container Apps. What to pick and why.
- 05
Infrastructure as Code — Terraform / Bicep Basics
Build a versioned Azure Terraform module on paper, understand state and dependency graphs, and rehearse plan review, drift, import, refactoring and recovery without cloud writes.
- 06
Orchestrating ML Pipelines with Azure Data Factory
Leveraging Azure Data Factory for Scalable and Efficient Machine Learning Workflows
- 07
Taking the Azure Fabric Ignite Edition Challenges to Complete
Microsoft Learn Challenge conducting a challenge to get good in few of the challenges which are super useful to complete to gain knowledge on Microsoft Fabric.
- 08
Exploring different services in GCP
Exploration and documentation of different services offered in GCP
- 09
Exploring Azure Data Explorer and Best Practices
A self-sufficient deep-dive on Azure Data Explorer (ADX/Kusto) — architecture, the KQL language from zero to advanced, ingestion patterns, performance/cost levers, and operational best practices.
- 10
Basics of Azure AI Foundry
A self-sufficient guide to Azure AI Foundry — what it is, how the hub/project/deployment model works, how to ship a grounded agent end-to-end with SDK + Bicep, and the security/eval/cost levers you cannot skip.