Description

This curriculum spans the technical and operational rigor of a multi-phase cloud migration advisory engagement, addressing the interdependencies of application, data, and infrastructure modernization across a large-scale enterprise environment.

Module 1: Assessing Application Readiness for Cloud Migration

Evaluate legacy application dependencies on on-premises middleware and determine refactoring requirements for cloud compatibility.
Inventory third-party software licenses and assess vendor support for cloud-hosted deployments, including BYOL (Bring Your Own License) eligibility.
Analyze application statefulness and identify data persistence patterns that may require redesign for cloud-native architectures.
Conduct performance benchmarking of current workloads to establish baseline metrics for post-migration validation.
Map application integration points with external systems and evaluate whether APIs require version upgrades or protocol changes.
Identify applications with regulatory or compliance constraints (e.g., data residency) that limit cloud region selection.

Module 2: Version Compatibility and Dependency Management

Resolve version conflicts between application components and cloud platform-supported runtime environments (e.g., Java, .NET).
Upgrade outdated libraries with known vulnerabilities while ensuring backward compatibility with existing code.
Coordinate patch levels across microservices to prevent inter-service communication failures during phased migration.
Manage transitive dependencies in containerized applications to avoid bloated or insecure images.
Validate database driver compatibility with cloud-managed database services (e.g., Amazon RDS, Azure SQL).
Document dependency trees for audit purposes and automate detection of deprecated or end-of-life components.

Module 3: Data Migration and Schema Evolution

Design schema transformation rules when migrating from on-premises databases to cloud-optimized data platforms (e.g., columnar to row-based).
Implement data type conversions that maintain precision and avoid data loss during ETL processes.
Coordinate cutover windows for database replication to minimize downtime and ensure transactional consistency.
Handle large binary objects (BLOBs) by evaluating compression, deduplication, or archival strategies pre-migration.
Apply data masking or tokenization during migration to protect sensitive information in test environments.
Test referential integrity across distributed systems where foreign key constraints are not enforced.

Module 4: Infrastructure as Code and Environment Parity

Refactor legacy deployment scripts into declarative IaC templates (e.g., Terraform, CloudFormation) with version-controlled modules.
Standardize environment configurations across dev, test, and production to eliminate configuration drift.
Integrate secret management (e.g., HashiCorp Vault, AWS Secrets Manager) into provisioning workflows to avoid hardcoded credentials.
Define rollback strategies in IaC that preserve state and avoid orphaned cloud resources.
Enforce naming conventions and tagging policies to support cost allocation and security governance.
Validate infrastructure templates against organizational security baselines using automated policy-as-code tools (e.g., Open Policy Agent).

Module 5: Application Refactoring and Modernization

Decompose monolithic applications into microservices with bounded contexts, considering transaction boundaries and data ownership.
Migrate session management from in-memory stores to distributed caches (e.g., Redis) for high availability.
Replace hardcoded endpoints with service discovery mechanisms in dynamic cloud environments.
Implement circuit breakers and retry logic to handle transient network failures in distributed systems.
Adapt logging mechanisms to support centralized aggregation (e.g., ELK, CloudWatch) and structured log formats.
Optimize application startup times for serverless or containerized environments with cold start implications.

Module 6: Security and Compliance in Cloud-Native Upgrades

Reconfigure firewall rules and security groups to follow least-privilege access principles in cloud networks.
Integrate identity federation (e.g., SAML, OIDC) with cloud provider identity services for centralized access control.
Upgrade TLS configurations to meet current cryptographic standards and disable deprecated protocols.
Implement encryption for data at rest and in transit using cloud-native key management services (KMS).
Conduct vulnerability scanning of container images and enforce admission controls in Kubernetes clusters.
Align audit logging configurations with compliance frameworks (e.g., HIPAA, SOC 2) and ensure log immutability.

Module 7: Continuous Integration and Deployment Pipelines

Reconfigure CI/CD pipelines to support cloud-specific deployment strategies (e.g., blue-green, canary).
Integrate automated testing for cloud infrastructure changes using unit and integration test frameworks.
Manage pipeline credentials with short-lived tokens and role-based access instead of long-term keys.
Optimize build artifacts for cloud deployment by minimizing size and standardizing formats (e.g., OCI images).
Implement approval gates for production deployments based on security scans and performance benchmarks.
Monitor pipeline execution times and failure rates to identify bottlenecks in upgrade workflows.

Module 8: Post-Migration Validation and Operational Governance

Establish performance SLAs and configure monitoring alerts for latency, error rates, and throughput deviations.
Conduct failover testing to validate disaster recovery procedures in the cloud environment.
Review auto-scaling policies to ensure they respond appropriately to real-world load patterns.
Reconcile cloud billing data with expected cost models and identify underutilized or orphaned resources.
Document operational runbooks for cloud-specific incidents (e.g., AZ outages, throttling).
Implement feedback loops from production telemetry to inform future upgrade cycles and capacity planning.