Description

This curriculum spans the technical and operational rigor of a multi-workshop cloud migration program, addressing the same deployment challenges encountered in enterprise advisory engagements, from application assessment and topology design to pipeline automation and post-migration governance.

Module 1: Assessing Application Readiness for Cloud Deployment

Evaluate legacy application dependencies on on-premises infrastructure such as shared file systems or local databases to determine refactoring requirements.
Conduct codebase analysis to identify hardcoded IP addresses, environment-specific configurations, or stateful components that inhibit cloud portability.
Classify applications using the Gartner 5R framework (Rehost, Refactor, Revise, Rebuild, Replace) based on technical debt and business criticality.
Engage application owners to negotiate ownership of configuration drift and patching responsibilities post-migration.
Assess licensing constraints for third-party software, particularly those with on-premises-only agreements or per-socket pricing models.
Define performance baselines for CPU, memory, I/O, and network latency to validate post-migration service levels.

Module 2: Designing Cloud Deployment Topologies

Select between single-region, multi-region, or hybrid topologies based on RTO/RPO requirements and data sovereignty regulations.
Implement VPC peering, transit gateways, or SD-WAN solutions to maintain secure connectivity between cloud and on-premises environments.
Decide on public vs. private subnets for workloads based on exposure risk, compliance needs, and integration with corporate identity providers.
Architect DNS routing strategies using split-horizon or cloud-based DNS to manage service discovery during phased cutover.
Configure NAT gateways or egress proxies to control outbound internet access and enforce data exfiltration policies.
Design IP address allocation schemes to prevent overlap across environments and support future scalability.

Module 3: Selecting Migration Deployment Patterns

Choose blue-green deployment for stateless applications to minimize downtime and enable rapid rollback via DNS or load balancer switching.
Implement canary releases with traffic weighting to validate new versions with real user loads before full promotion.
Determine whether to use lift-and-shift (rehost) for time-constrained migrations or refactor for long-term TCO optimization.
Orchestrate database migration using log shipping, replication, or snapshot cloning based on acceptable data lag and downtime windows.
Coordinate cutover timing with business stakeholders to avoid peak transaction periods and reduce user impact.
Use feature flags to decouple deployment from release, enabling incremental enablement without redeployment.

Module 4: Automating Deployment Pipelines

Integrate infrastructure-as-code (IaC) tools like Terraform or CloudFormation into CI/CD pipelines to enforce environment consistency.
Implement pipeline stages for security scanning, compliance validation, and drift detection before production promotion.
Manage secrets using centralized vaults (e.g., HashiCorp Vault, AWS Secrets Manager) instead of embedding in deployment scripts.
Enforce role-based access controls (RBAC) on deployment tools to separate developer, reviewer, and approver responsibilities.
Design rollback automation using versioned artifacts and infrastructure snapshots to reduce mean time to recovery (MTTR).
Configure pipeline triggers based on artifact provenance, not just code commits, to prevent unauthorized or untested deployments.

Module 5: Managing Stateful Workloads in the Cloud

Select between managed database services (e.g., RDS, Cloud SQL) and self-managed instances based on operational overhead tolerance.
Implement backup and recovery procedures for stateful components using cloud-native snapshot policies and cross-region replication.
Design storage class strategies (e.g., EBS GP3 vs. IO1, Azure Premium SSD) based on IOPS and latency requirements.
Address session persistence needs using distributed caches (e.g., Redis) instead of relying on local server storage.
Negotiate SLAs with cloud providers for managed services, particularly for backup retention and point-in-time recovery guarantees.
Plan for data egress costs when replicating large datasets across regions or during disaster recovery failover.

Module 6: Governing Deployment Security and Compliance

Enforce deployment policies using guardrails in IaC tools to prevent creation of public S3 buckets or unrestricted security groups.
Integrate static application security testing (SAST) and container scanning into deployment pipelines to block vulnerable builds.
Map deployment activities to compliance frameworks (e.g., SOC 2, HIPAA) by logging all configuration changes and access events.
Implement immutable infrastructure patterns to reduce configuration drift and simplify audit trails.
Define data classification rules to automatically encrypt sensitive workloads at rest and in transit.
Conduct periodic access reviews for deployment tooling to deprovision stale or overprivileged accounts.

Module 7: Monitoring and Optimizing Post-Deployment Operations

Configure observability stacks with centralized logging, distributed tracing, and metrics collection to diagnose deployment-related issues.
Set up anomaly detection on resource utilization to identify misconfigured autoscaling or memory leaks post-migration.
Use cost allocation tags to track cloud spend by application, team, or environment and identify underutilized resources.
Establish feedback loops from production monitoring to inform future deployment design and pipeline improvements.
Perform regular load testing in staging environments to validate scalability assumptions after infrastructure changes.
Review deployment failure root causes quarterly to refine rollback procedures and improve pipeline resilience.