Description

This curriculum spans the technical, operational, and governance dimensions of cloud migration with a scope and granularity comparable to a multi-phase advisory engagement, addressing real-world challenges from workload assessment and data integration to security governance, cost control, and organizational change.

Module 1: Assessing Enterprise Readiness for Cloud Migration

Conducting a workload dependency analysis to identify monolithic applications requiring refactoring before migration.
Evaluating existing SLAs against cloud provider uptime commitments to determine compliance risks.
Mapping on-premises identity management systems to cloud IAM frameworks, including federation requirements.
Inventorying data sovereignty constraints that restrict where specific data can be hosted geographically.
Assessing internal skill gaps in cloud operations and determining whether to upskill or outsource.
Reviewing existing change management processes for compatibility with cloud-native deployment velocity.
Quantifying technical debt in legacy systems to prioritize migration candidates based on risk and cost.

Module 2: Designing Cloud Architecture and Deployment Topology

Selecting between single-tenant and multi-tenant architectures based on security, cost, and isolation needs.
Defining VPC peering and transit gateway strategies to enable secure inter-account and hybrid connectivity.
Deciding on region and availability zone distribution to balance resilience and data transfer costs.
Architecting for disaster recovery using active-passive vs. active-active configurations across regions.
Implementing DNS routing policies (e.g., latency-based, failover) to optimize user experience.
Designing edge caching layers using CDN integration for global application performance.
Establishing network segmentation models using security groups and NACLs aligned with zero-trust principles.

Module 3: Data Migration and Integration Strategy

Choosing between online and offline data transfer methods based on volume, bandwidth, and downtime tolerance.
Implementing schema transformation workflows when migrating from on-premises databases to managed cloud services.
Configuring change data capture (CDC) pipelines to maintain data consistency during cutover phases.
Validating referential integrity post-migration across distributed data stores.
Establishing data retention and archival rules in alignment with regulatory requirements.
Integrating legacy APIs with cloud-based API gateways while maintaining backward compatibility.
Managing data encryption key rotation during and after migration using cloud KMS.

Module 4: Application Refactoring and Modernization

Decomposing monolithic applications into microservices using domain-driven design principles.
Replacing legacy session management with stateless authentication mechanisms compatible with auto-scaling.
Containerizing applications using Docker and orchestrating with Kubernetes for portability.
Implementing feature flag systems to decouple deployment from release in production environments.
Migrating batch processing jobs to serverless functions with event-driven triggers.
Refactoring direct database access patterns to use service APIs for improved security and observability.
Updating logging frameworks to support centralized ingestion into cloud-native monitoring tools.

Module 5: Security, Compliance, and Identity Governance

Implementing least-privilege IAM roles and policies across development, staging, and production accounts.
Configuring cloud security posture management (CSPM) tools to detect misconfigurations in real time.
Integrating cloud audit logs with SIEM systems for centralized threat detection and response.
Enforcing encryption at rest and in transit for all data assets, including snapshots and backups.
Conducting third-party penetration testing on migrated workloads before full production cutover.
Establishing automated compliance checks using infrastructure-as-code scanning tools.
Managing privileged access with just-in-time (JIT) elevation and session recording.

Module 6: Operationalizing Cloud Infrastructure Management

Implementing infrastructure-as-code using Terraform or CloudFormation for consistent provisioning.
Setting up automated drift detection to identify and remediate manual configuration changes.
Defining tagging standards for cost allocation, resource ownership, and automation triggers.
Configuring auto-scaling policies based on performance metrics and scheduled demand patterns.
Establishing backup and snapshot retention schedules aligned with RPO and RTO requirements.
Integrating monitoring agents to collect custom application metrics alongside infrastructure telemetry.
Creating runbooks for common failure scenarios, including DNS outages and database failovers.

Module 7: Financial Governance and Cost Optimization

Implementing chargeback or showback models using cloud cost allocation tags.
Negotiating reserved instance or savings plan commitments based on historical usage patterns.
Setting up budget alerts and automated actions for resources exceeding cost thresholds.
Right-sizing compute instances based on performance monitoring and utilization trends.
Identifying and decommissioning orphaned resources such as unattached disks and idle load balancers.
Optimizing data transfer costs by minimizing cross-region and cross-cloud egress.
Using spot instances for fault-tolerant workloads while managing interruption risks.

Module 8: Change Management and Post-Migration Stabilization

Revising incident response procedures to account for cloud-specific failure modes.
Conducting blameless post-mortems after migration-related outages to update operational playbooks.
Transitioning support responsibilities from migration teams to ongoing cloud operations teams.
Updating documentation to reflect new architecture diagrams, access paths, and escalation procedures.
Running performance benchmarking to validate that SLAs are met under production load.
Establishing feedback loops with business units to identify usability or performance gaps.
Implementing continuous improvement cycles using cloud operations metrics and stakeholder input.