Description

This curriculum spans the equivalent of a multi-workshop technical advisory engagement, covering the sequence and decision frameworks used in real migration programs from initial assessment through post-live optimization.

Module 1: Strategic Assessment and Readiness Evaluation

Selecting which on-premises workloads to migrate based on technical debt, business criticality, and interdependencies with legacy systems.
Conducting a TCO analysis that includes hidden costs such as data egress fees, licensing changes, and operational overhead in the cloud.
Defining migration timelines using business cycle constraints, such as avoiding peak transaction periods or aligning with fiscal planning.
Establishing cross-functional migration governance with clear RACI matrices for infrastructure, security, and application teams.
Assessing vendor lock-in risks when choosing cloud-native services versus maintaining portability with containerization.
Documenting compliance requirements early (e.g., data residency, audit logging) to prevent rework during migration execution.

Module 2: Cloud Architecture and Design Optimization

Deciding between lift-and-shift and refactor approaches based on application architecture and long-term scalability needs.
Designing VPC/VNet topologies with segmentation for production, development, and disaster recovery environments.
Selecting appropriate compute types (e.g., reserved instances, spot instances, serverless) based on workload predictability and cost sensitivity.
Implementing auto-scaling policies that balance performance SLAs with cost control under variable load.
Integrating CDN and edge caching strategies for globally distributed user bases to reduce latency and bandwidth costs.
Architecting for high availability using multi-AZ or multi-region deployments while evaluating cost-benefit trade-offs.

Module 3: Data Migration and Storage Strategy

Choosing between online and offline data transfer methods based on data volume, network bandwidth, and downtime tolerance.
Implementing staged data cutover with bidirectional synchronization to minimize risk during database migration.
Classifying data by access frequency to assign appropriate storage tiers (e.g., hot, cool, archive) and reduce costs.
Encrypting data at rest and in transit using cloud provider KMS or customer-managed keys with documented key rotation policies.
Validating referential integrity and data consistency post-migration using automated reconciliation scripts.
Establishing retention and lifecycle policies for backups, logs, and temporary storage to prevent uncontrolled growth.

Module 4: Identity, Access, and Security Integration

Mapping on-premises AD/LDAP identities to cloud IAM roles using federation with SSO and conditional access policies.
Enforcing least-privilege access through granular IAM policies and just-in-time privilege elevation.
Integrating cloud security logging with existing SIEM systems for centralized monitoring and incident response.
Implementing infrastructure-as-code scanning to detect misconfigurations before deployment (e.g., public S3 buckets).
Configuring network security groups and firewall rules to allow only necessary inter-service communication.
Conducting penetration testing and vulnerability assessments post-migration to validate security posture.

Module 5: Automation and DevOps Enablement

Standardizing infrastructure provisioning using Terraform or CloudFormation templates to ensure consistency across environments.
Integrating CI/CD pipelines with cloud environments to automate testing, deployment, and rollback procedures.
Managing secrets using dedicated vault services instead of embedding credentials in configuration files or environment variables.
Implementing drift detection to identify and remediate configuration changes made outside of IaC workflows.
Using blue-green or canary deployment strategies to reduce risk during application updates in the cloud.
Creating reusable deployment modules for common patterns (e.g., web server clusters, database replicas) to accelerate future migrations.

Module 6: Performance Monitoring and Cost Governance

Setting up cloud-native monitoring (e.g., CloudWatch, Azure Monitor) with custom dashboards for key performance indicators.
Configuring alerts for abnormal resource utilization or cost spikes using budget thresholds and anomaly detection.
Conducting regular cost allocation tagging audits to ensure accurate chargeback and showback reporting.
Right-sizing underutilized instances based on performance telemetry and historical usage patterns.
Implementing automated shutdown schedules for non-production environments to reduce idle resource costs.
Using FinOps practices to align cloud spending with business units and enforce accountability through showback reports.

Module 7: Business Continuity and Operational Readiness

Designing and testing disaster recovery runbooks that include failover and failback procedures for cloud workloads.
Validating backup integrity and recovery time objectives (RTO) through scheduled recovery drills.
Updating incident response playbooks to include cloud-specific scenarios such as service outages or IAM breaches.
Training operations teams on cloud console navigation, CLI tools, and troubleshooting cloud-native services.
Establishing change advisory boards (CAB) to review and approve production changes in the cloud environment.
Documenting operational handover procedures, including escalation paths and support contracts with cloud providers.

Module 8: Post-Migration Optimization and Continuous Improvement

Conducting a post-implementation review to assess migration success against KPIs such as downtime, cost, and performance.
Refactoring applications to leverage cloud-native services (e.g., managed databases, event queues) for improved resilience.
Implementing feedback loops from development and operations teams to refine cloud standards and tooling.
Updating architectural decision records (ADRs) to reflect lessons learned and guide future cloud initiatives.
Establishing a cloud center of excellence (CCoE) to maintain governance, share best practices, and drive innovation.
Scheduling periodic cloud optimization reviews to identify underused resources, emerging services, and cost-saving opportunities.