Description

This curriculum spans the technical and organisational complexity of a multi-workshop cloud transformation program, addressing the same infrastructure automation, governance, and operational rigor applied in enterprise advisory engagements for large-scale cloud adoption.

Module 1: Strategic Alignment of Cloud Infrastructure with Business Objectives

Define service-level objectives (SLOs) in collaboration with business units to align cloud performance with customer experience requirements.
Select cloud deployment models (public, private, hybrid) based on data sovereignty regulations and latency constraints for global operations.
Negotiate enterprise agreements with cloud providers while balancing long-term cost predictability against architectural flexibility.
Map existing on-premises workloads to cloud-native equivalents, identifying candidates for rehost, refactor, or retire based on TCO analysis.
Establish cross-functional steering committees to resolve conflicts between infrastructure scalability goals and application delivery timelines.
Integrate cloud adoption milestones into enterprise roadmap planning cycles to ensure budget and resource alignment across departments.

Module 2: Cloud Governance and Compliance Frameworks

Implement policy-as-code using tools like AWS Config Rules or Azure Policy to enforce tagging standards and resource naming conventions at scale.
Configure multi-account strategies with centralized logging and audit trails to meet SOX, HIPAA, or GDPR compliance requirements.
Design identity federation between on-premises directories and cloud IAM systems, managing least-privilege access across hybrid environments.
Conduct quarterly access reviews for privileged roles, automating deprovisioning workflows for offboarded personnel.
Integrate cloud security posture management (CSPM) tools into CI/CD pipelines to detect non-compliant infrastructure changes pre-deployment.
Document data classification policies and map them to encryption-at-rest and encryption-in-transit requirements across regions.

Module 3: Infrastructure as Code (IaC) Implementation at Scale

Standardize Terraform module interfaces across teams to ensure reusable, versioned components for networking, compute, and storage.
Enforce state file locking and remote backend configuration using S3 with versioning and DynamoDB for state locking.
Integrate static analysis tools like Checkov or tfsec into pull request workflows to catch misconfigurations before merge.
Manage secrets using dedicated vault solutions (e.g., HashiCorp Vault) instead of embedding them in IaC templates or environment variables.
Structure IaC repositories using GitOps principles, with environment-specific branches or separate repos for staging and production.
Implement drift detection mechanisms to identify and remediate manual changes made outside of IaC pipelines.

Module 4: Cloud Networking and Connectivity Design

Design hub-and-spoke VPC architectures with shared transit gateways, balancing segmentation needs against inter-service latency.
Configure DNS resolution across hybrid environments using private hosted zones and on-premises forwarders.
Implement secure site-to-site connectivity using IPsec VPNs or Direct Connect with BGP failover configurations.
Enforce micro-segmentation using security groups and network ACLs based on application tier and data sensitivity.
Optimize data transfer costs by routing cross-region traffic through private backbone networks instead of public internet.
Plan IP address space allocation across regions and accounts to avoid CIDR overlap during future mergers or workload migrations.

Module 5: Scalable and Resilient Compute Architecture

Configure auto-scaling groups with predictive and dynamic scaling policies based on CloudWatch or Prometheus metrics.
Select instance families based on workload profiles (e.g., memory-intensive, compute-optimized) and leverage spot instances with fallback logic.
Design containerized workloads using EKS or AKS with node auto-provisioning and pod disruption budgets.
Implement health checks and circuit breakers in microservices to prevent cascading failures during infrastructure outages.
Configure placement groups and spread policies to distribute critical workloads across failure domains.
Use launch templates instead of launch configurations to enable version-controlled instance provisioning with consistent configurations.

Module 6: Continuous Integration and Delivery for Infrastructure

Design multi-stage deployment pipelines with manual approval gates for production promotions in regulated environments.
Integrate infrastructure testing using tools like Terratest to validate network connectivity and security group rules post-deployment.
Implement canary analysis using metrics and logs to automatically roll back faulty infrastructure changes.
Enforce pipeline immutability by building artifacts once and promoting them across environments without modification.
Configure pipeline permissions using role-based access and just-in-time elevation to prevent unauthorized deployments.
Monitor pipeline execution times and failure rates to identify bottlenecks in testing or provisioning stages.

Module 7: Cost Management and Resource Optimization

Implement chargeback or showback models using cost allocation tags to attribute cloud spend to business units.
Negotiate reserved instance commitments based on 90-day usage patterns, balancing savings against architectural agility.
Automate shutdown schedules for non-production environments using time-based Lambda functions or Cloud Functions.
Use cost anomaly detection tools to identify unexpected spikes in spending and trigger automated alerts.
Right-size underutilized instances using performance metrics from CloudWatch or Operations Suite, validating impact on application SLAs.
Evaluate storage tiering strategies, migrating infrequently accessed data to lower-cost classes with lifecycle policies.

Module 8: Monitoring, Observability, and Incident Response

Design centralized logging architecture using CloudWatch Logs Insights or Datadog to aggregate logs from multi-account environments.
Define meaningful alert thresholds based on SLO error budgets to reduce alert fatigue and prioritize incidents.
Implement distributed tracing for microservices using X-Ray or OpenTelemetry to diagnose latency bottlenecks.
Configure synthetic monitoring to proactively test critical user journeys from external vantage points.
Integrate incident management platforms (e.g., PagerDuty) with auto-remediation scripts for common failure scenarios.
Conduct blameless postmortems for major incidents, updating runbooks and architecture diagrams based on root cause findings.