Description

This curriculum spans the technical and operational rigor of a multi-workshop cloud migration program, addressing the same workload assessment, architecture redesign, and operational integration challenges encountered in enterprise advisory engagements.

Module 1: Assessing Application Portfolio for Cloud Suitability

Conducting dependency mapping to identify tightly coupled components that may hinder independent scaling in cloud environments.
Evaluating legacy application runtime compatibility with cloud provider-supported operating systems and middleware.
Classifying applications by criticality and compliance requirements to determine migration sequencing and hosting constraints.
Measuring current on-premises utilization patterns to avoid over-provisioning during cloud resource estimation.
Identifying applications with persistent local storage dependencies that require refactoring for stateless cloud operation.
Documenting third-party software licensing restrictions that may limit deployment options in public cloud.

Module 2: Selecting Migration Strategies (Rehost, Refactor, Replatform, etc.)

Determining whether to rehost via lift-and-shift based on time-to-market pressures versus long-term technical debt accumulation.
Assessing the feasibility of refactoring monolithic applications into microservices when source code access is limited.
Deciding to replatform databases by migrating from on-premises SQL Server to managed cloud instances with minimal code changes.
Evaluating cost and effort of retiring shadow IT applications discovered during inventory instead of migrating them.
Using TCO calculators to compare break-even points between rehosting and refactoring for business-critical line-of-business apps.
Establishing criteria for selecting SaaS alternatives over migrating custom-built applications with overlapping functionality.

Module 3: Designing Cloud-Native Architecture Patterns

Implementing API gateways to manage service-to-service communication in distributed workloads across availability zones.
Selecting container orchestration platforms (e.g., EKS, AKS) over VM-based deployments for dynamic scaling requirements.
Integrating serverless compute for event-driven components while managing cold start implications for latency-sensitive workflows.
Designing data partitioning strategies for cloud databases to comply with data residency regulations across regions.
Replacing hardcoded configuration values with cloud parameter stores or secret management services for secure deployment.
Implementing circuit breakers and retry logic in application code to handle transient cloud network failures.

Module 4: Data Migration and Synchronization Planning

Choosing between online and offline data transfer methods based on data volume, network bandwidth, and acceptable downtime.
Validating referential integrity after database schema conversion from on-premises to cloud-managed DB engines.
Scheduling cutover windows to minimize impact on dependent batch processing and reporting systems.
Implementing change data capture (CDC) to maintain synchronization during phased migration of transactional systems.
Handling large binary objects (BLOBs) by migrating to object storage and updating application paths accordingly.
Encrypting data in transit and at rest during migration using customer-managed or cloud provider keys.

Module 5: Identity, Access, and Security Integration

Extending on-premises Active Directory to cloud using hybrid identity services while managing authentication latency.
Mapping application service accounts to cloud IAM roles with least-privilege permissions to reduce attack surface.
Configuring conditional access policies for cloud workloads based on user location, device compliance, and risk signals.
Integrating application logging with cloud-native security information and event management (SIEM) platforms.
Rotating credentials and secrets automatically using cloud key management and rotation policies.
Enforcing encryption for application data stored in cloud databases using transparent data encryption (TDE) or application-level encryption.

Module 6: Performance, Scalability, and Resiliency Engineering

Configuring auto-scaling groups based on custom metrics derived from application-level performance counters.
Implementing health checks that reflect actual application readiness, not just OS-level responsiveness.
Designing multi-region failover for stateful applications using asynchronous data replication and DNS routing.
Optimizing database connection pooling to prevent exhaustion under auto-scaling workloads.
Using content delivery networks (CDNs) to cache static assets and reduce origin server load for web applications.
Stress-testing application performance under simulated cloud network jitter and packet loss conditions.

Module 7: Monitoring, Observability, and Operational Governance

Instrumenting applications with distributed tracing to diagnose latency across microservices in cloud environments.
Setting up centralized log aggregation with filtering and retention policies aligned to compliance requirements.
Defining service level objectives (SLOs) and error budgets for migrated applications to guide operational decisions.
Automating alerting on anomalous resource consumption that may indicate misconfiguration or security incidents.
Enforcing tagging standards across cloud resources to enable chargeback and cost allocation reporting.
Conducting regular cost optimization reviews using cloud provider cost anomaly detection and usage reports.

Module 8: Managing Post-Migration Technical Debt and Optimization

Refactoring applications originally rehosted with minimal changes to leverage managed cloud services incrementally.
Decommissioning legacy infrastructure only after verifying data consistency and user access in the new environment.
Revising disaster recovery runbooks to reflect cloud-native backup and restore procedures for each workload.
Updating CI/CD pipelines to incorporate infrastructure-as-code validation and security scanning for cloud deployments.
Re-evaluating reserved instance or savings plan commitments based on actual post-migration usage patterns.
Establishing feedback loops with development teams to address performance bottlenecks identified in production monitoring.