10 days. 10 hands-on labs. All production-style.

Azure Cloud Foundations & Your First AIOps Pipeline

Before any intelligent operations can run, the team needs a working Azure foundation and a local AI toolchain, the groundwork for every AIOps build that follows.

• Azure fundamentals, resource groups and the ARM control plane
• AIOps lifecycle: Observe, Detect, Decide, Act
• Azure account, CLI and Python setup
• Install Ollama and deploy a local LLM

Hands-on lab: First AIOps tool. Build your first AI-assisted Azure administration tool with Azure CLI resource discovery and an AI-powered resource summary generator.

Azure Identity, RBAC & Access Intelligence

Identity is the new perimeter: access must be governed with least privilege and watched by ML that spots suspicious logins before they become incidents.

• Microsoft Entra ID, RBAC and custom roles
• Managed Identity and Service Principals
• Key Vault integration via the Microsoft Graph API
• Login analytics with an Isolation Forest model

Hands-on lab: Identity monitoring solution. Build an AI-powered Azure identity monitoring solution with custom RBAC roles and suspicious login detection.

Azure Networking & Traffic Intelligence

As the network grows, the team needs segmented, private connectivity and traffic intelligence that flags anomalies humans would miss.

• Virtual Networks and Hub-Spoke
• NSG and network security
• Private Endpoint and multi-VNet architecture
• NSG Flow Logs and Traffic Analytics

Hands-on lab: Network monitoring system. Develop an intelligent network monitoring system with VNet peering, Storage Private Endpoint and ML-based network anomaly detection.

Azure Compute & Predictive Scaling

Workloads are bursty and reactive scaling is too slow: compute must forecast demand and scale ahead of it.

• Virtual Machine Scale Sets and Azure Container Apps
• Autoscaling and predictive scaling
• Azure Monitor metrics collection
• CPU forecasting with ARIMA

Hands-on lab: AI-driven autoscaling. Implement AI-driven autoscaling for cloud workloads using VMSS, Container Apps and automated predictive scaling.

Azure Storage Intelligence

Storage costs creep as data ages: tiering and lifecycle decisions should be made intelligently, not manually.

• Blob Storage and storage tiers
• Lifecycle management and Azure CDN
• Decision Tree model for tiering
• Static website hosting

Hands-on lab: Storage lifecycle automation. Create intelligent storage lifecycle automation with blob analytics and automated storage tier optimisation.

Observability & Self-Healing Cloud

Alerts alone do not fix anything: the platform needs observability wired to automation that heals common failures on its own.

• Azure Monitor and Application Insights
• Log Analytics and KQL
• Event-driven automation
• Event Grid and Automation Runbooks

Hands-on lab: Self-healing cloud platform. Build a complete self-healing cloud platform with custom KQL queries, ML-based metric analysis and self-healing infrastructure.

AI Incident Response Agent

Incident volume outpaces the on-call team: an AI agent must classify, route and act on alerts in real time.

• Event Grid and Service Bus
• Azure Functions and AI decision engines
• Alert pipeline and queue processing
• AI incident classification and intelligent routing

Hands-on lab: AI incident response assistant. Develop an AI-powered incident response assistant with API Management integration and intelligent routing.

AI-Assisted Infrastructure as Code

Infrastructure changes must ship fast and safe: AI accelerates authoring while policy and security scanning hold the line.

• Infrastructure as Code with Bicep and Terraform
• GitHub Actions and Policy as Code
• AI-assisted Terraform generation
• Checkov scanning and AI code review

Hands-on lab: AI-assisted IaC pipeline. Automate enterprise infrastructure deployment using AI, with Bicep modules and a CI/CD pipeline in GitHub Actions.

FinOps & AI Cost Intelligence

Cloud spend needs an owner and a forecast: FinOps plus ML turns cost from a surprise into a managed, predictable signal.

• Azure Cost Management and FinOps
• Reserved Instances and Savings Plans
• Machine-learning cost prediction
• Cost anomaly detection

Hands-on lab: AI cost optimisation platform. Build an AI-powered Azure cost optimisation platform with cost analytics and AI cost recommendations.

Azure Security Intelligence

Security findings pile up faster than they can be triaged: AI must prioritise what matters and drive continuous hardening.

• Defender for Cloud and Secure Score
• Encryption and Zero Trust
• Security automation
• AI-based finding prioritisation

Hands-on lab: Security advisory platform. Create an intelligent Azure security advisory platform with private endpoints, security hardening and compliance reporting.

Capstone

Intelligent Enterprise Azure Platform

Bring all ten days together into one production-style Intelligent Enterprise Azure Platform: architected, coded, monitored, secured and operated with AI and ML.

• Container Apps, Functions and Storage
• Service Bus, Event Grid and Key Vault
• Azure Monitor and Application Insights
• Infrastructure as Code and GitHub Actions CI/CD
• AI incident agent and decision engine, Machine Learning across signals
• Self-healing automation with cost and security intelligence