Analyze and compare hybrid network topologies for AI workloads. You'll build comparison matrices evaluating latency, cost, and scalability, then make evidence-based recommendations for stakeholder review.

This module teaches you to extend Azure's control plane to Kubernetes clusters running outside Azure. You'll register clusters with Azure Arc, deploy policy and monitoring extensions, and verify unified management across your hybrid infrastructure.

This module teaches you to identify and act on optimization opportunities for hybrid AI workloads. You'll analyze Azure Advisor recommendations, implement changes, and produce cost-savings reports that demonstrate measurable impact.

This module teaches you to implement zero-trust networking for microservices using the Istio Service Mesh. You'll configure mutual TLS authentication, verify encrypted communication between services, and validate your security posture meets organizational requirements.

This module teaches you to assess workload portability across cloud providers. You'll deploy the same AI model to AKS, EKS, and GKE, collect performance data, and produce a portability assessment with platform recommendations.

This module teaches you to provision GPU node pools on AKS using Terraform. You'll create reusable modules with spot instance support and cluster autoscaling, then validate that the infrastructure responds correctly to workload demands.

This module teaches you to benchmark and select optimal storage configurations for GPU training workloads. You'll compare disk types, measure I/O performance, and document your decision with supporting performance data.

This module teaches you to implement and verify data residency controls using Azure Policy and Purview. You'll create policies that restrict storage to compliant regions, run compliance scans, and remediate non-conforming resources to achieve audit-ready status.

This module teaches you to evaluate deployment options for data with strict sovereignty requirements. You'll compare sovereign clouds, public clouds with regional restrictions, and hybrid approaches, then produce a decision document that balances compliance, latency, and cost trade-offs.

Apply hybrid cloud architecture skills to conduct a focused review of a multicloud AI deployment. Learners assess the architecture across all five WAF pillars, identify the highest-priority risks, and produce a remediation plan suitable for stakeholder presentation.