Description

The curriculum spans the equivalent depth and sequence of a multi-workshop technical engagement for cloud migration teams, covering tool selection, automated workflows, and governance processes used in real enterprise migrations from discovery through post-cutover optimization.

Module 1: Assessing Migration Readiness and Tool Fit

Evaluate existing application dependencies and technical debt to determine which workloads are suitable for automation-assisted migration.
Select automation tools based on compatibility with legacy systems, such as mainframe interfaces or on-premises databases without cloud-native equivalents.
Analyze network latency and data egress constraints when deciding whether to automate data transfer in batches or via continuous replication.
Map IAM roles and AD/LDAP integrations to cloud identity providers before initiating automated provisioning workflows.
Decide whether to use agent-based or agentless discovery tools based on guest OS access restrictions and security policies.
Establish performance baselines for critical applications to validate post-migration behavior using automated monitoring triggers.

Module 2: Designing Automated Discovery and Dependency Mapping

Configure discovery tools to exclude non-migratable systems (e.g., air-gapped industrial control systems) from automated scans.
Adjust polling intervals for dependency mapping to minimize performance impact on production databases during business hours.
Integrate output from discovery tools into CMDBs using custom scripts when native integrations lack required field mappings.
Validate bidirectional traffic flows in auto-generated dependency maps to prevent misclassifying one-way dependencies.
Define thresholds for auto-flagging high-risk applications (e.g., >50 dependencies, custom protocols) for manual review.
Document exceptions where automated discovery fails (e.g., encrypted traffic, dynamic ports) and plan for manual validation.

Module 3: Selecting and Configuring Migration Automation Frameworks

Choose between open-source frameworks (e.g., Terraform) and vendor-specific tools (e.g., AWS Migration Hub) based on multi-cloud vs. single-cloud strategy.
Implement state file backend configurations in Terraform to prevent conflicts in team-based execution environments.
Customize pre-migration health checks in automation playbooks to include application-specific readiness criteria (e.g., log rotation, queue depth).
Version-control migration scripts and associate them with specific application release cycles to avoid configuration drift.
Configure rollback triggers in automation workflows based on failed health checks or SLA breaches during cutover.
Enforce parameter validation in templates to prevent invalid configurations (e.g., subnet overlap, unsupported instance types).

Module 4: Automating Lift-and-Shift Migrations

Set replication windows for VMware VMs using HCX to align with change management blackout periods and minimize downtime.

Modify Sysprep or cloud-init scripts automatically during migration to inject correct hostname, DNS, and NTP settings.

Pre-allocate Elastic IPs or reserved instances in target regions to avoid automation failures due to quota limits.

Automate security group creation based on observed traffic patterns, then refine rules post-migration to meet least-privilege standards.

Handle OS-level incompatibilities (e.g., driver conflicts) by injecting compatibility scripts during VM conversion.

Coordinate DNS cutover timing with application teams to ensure automated IP reassignment does not break dependent services.

Module 5: Automating Replatforming and Refactoring Workflows

Automate schema conversion from Oracle to Amazon RDS PostgreSQL, then manually review spatial or custom data types for accuracy.
Configure CI/CD pipelines to rebuild monolithic applications into containers using automated Dockerfile generation from process trees.
Use automated code scanners to flag deprecated APIs before initiating application modernization playbooks.
Integrate automated performance testing into refactoring pipelines to reject builds that exceed latency thresholds.
Map legacy cron jobs to cloud scheduler services (e.g., AWS EventBridge) using parsing scripts that handle time zone discrepancies.
Define auto-remediation rules for failed deployments, such as scaling down new instances and reverting DNS aliases.

Module 6: Governance, Compliance, and Security in Automated Migrations

Embed compliance checks (e.g., CIS benchmarks) into provisioning templates to prevent non-conforming resources from deploying.
Implement automated tagging policies and enforce them through pre-deployment validation gates in IaC pipelines.
Configure audit trails to log all automated actions, including tool-initiated API calls, for forensic accountability.
Restrict automation tool permissions using least-privilege IAM roles to prevent unintended resource modifications.
Integrate secrets management tools (e.g., HashiCorp Vault) into automation workflows to avoid hardcoded credentials in scripts.
Schedule automated drift detection scans to identify and report configuration changes made outside approved tooling.

Module 7: Post-Migration Optimization and Continuous Automation

Deploy automated cost anomaly detection rules to identify misprovisioned resources after migration completion.
Configure auto-scaling policies based on post-migration utilization data, adjusting cooldown periods to prevent thrashing.
Implement automated rightsizing recommendations using cloud-native tools (e.g., AWS Compute Optimizer) with manual approval gates.
Integrate migrated workloads into centralized logging and monitoring systems using automated agent deployment playbooks.
Establish automated backup and DR test schedules aligned with RPO/RTO requirements defined during migration planning.
Update runbooks and incident response procedures to reflect new cloud-native failure modes introduced by automation.