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Azure Docker Kubernetes Python

Ten small, standalone DevOps practice tasks, each demonstrating a distinct discipline — containerisation, cloud CI/CD with security scanning, build automation, distributed build infrastructure, serverless compute, container orchestration, database observability, continuous delivery orchestration, cloud data warehousing, and MLOps.

Tackled in order of simplicity to complexity, with az_cicd later extended with integrated security scanning.


Tasks

# Task What it demonstrates
1 docker_webserver Containerised web server — Docker fundamentals
2 az_cicd Automated CI/CD on Azure (Pipelines, Container Registry, App Service) with Trivy, Dependabot, and Snyk security scanning
3 java_gradle Java build automation and dependency management with Gradle
4 jenkins_remoting Jenkins controller/agent architecture — distributed, isolated build execution
5 az_function_storage HTTP-triggered Azure Function (Python, Consumption plan) writing to Blob Storage
6 az_aks_deployment Containerised workload deployed to a genuine Azure Kubernetes Service cluster
7 data_layer_monitoring Redis, MongoDB, and PostgreSQL with real CRUD operations, monitored via DataDog and Docker Autodiscovery
8 octopus_deploy Release promoted through Development, Staging, and Production via Octopus Deploy, to a real SSH-connected target
9 data_warehousing Azure Synapse serverless SQL pool running real analytical queries against data lake files
10 mlops_ai_pipeline Trained classifier, versioned, served live, automatically retrained and redeployed via CI/CD

Structure

Every task folder follows the same layout:

  • What was built — a plain account of the components and architecture
  • Commands used — complete, real commands
  • Verification Evidence — screenshots proving it worked
  • Troubleshooting notes — genuine issues hit and how they were resolved
  • Teardown — confirmation that infrastructure was cleanly removed

Every cloud resource in this repository was created, verified, documented, and deleted.

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