Description

This curriculum spans the technical and organisational complexity of a multi-workshop automation transformation program, addressing the same scope of challenges encountered in enterprise-wide cloud migration and IaC governance initiatives.

Module 1: Assessing Application Readiness for Cloud Automation

Evaluate legacy application dependencies on monolithic databases to determine refactoring requirements before automation deployment.
Identify applications with hardcoded IP addresses or static configurations that will fail in dynamic cloud environments unless remediated.
Classify workloads by statefulness and session persistence needs to determine compatibility with auto-scaling and infrastructure-as-code patterns.
Conduct inventory audits using discovery tools to map interdependencies between services, networks, and data stores for migration sequencing.
Define criteria for "lift-and-shift" versus "re-architect" based on automation maintainability, cost, and future scalability.
Establish ownership models for application portfolios to assign accountability for automation readiness remediation tasks.

Module 2: Designing Infrastructure as Code (IaC) Governance

Implement module versioning and registry controls to prevent configuration drift across development, staging, and production environments.
Enforce mandatory peer review and automated policy checks (e.g., using Open Policy Agent) before IaC merge requests are approved.
Select between declarative (e.g., Terraform) and imperative (e.g., CloudFormation with custom resources) approaches based on team skill and rollback complexity.
Define naming, tagging, and metadata standards in IaC templates to ensure consistent resource identification and cost allocation.
Integrate secrets management (e.g., HashiCorp Vault or AWS Secrets Manager) into IaC pipelines to avoid hardcoded credentials.
Plan for state file management and locking in distributed teams to prevent concurrent execution conflicts and state corruption.

Module 3: Automating Migration Execution and Cutover

Orchestrate phased data replication using tools like AWS DMS or Azure Data Box while managing network bandwidth constraints and latency.
Design automated rollback playbooks that trigger on failed health checks during cutover to minimize downtime exposure.
Coordinate DNS TTL reductions and pre-warming strategies to accelerate traffic redirection post-migration.
Automate pre-cutover validation checks including connectivity, authentication, and data consistency across replicated systems.
Use blue-green deployment patterns in automation scripts to reduce risk during application migration events.
Log and monitor all migration automation steps in a centralized audit trail for post-event analysis and compliance.

Module 4: Securing Automated Cloud Environments

Embed security baseline checks (e.g., CIS benchmarks) into CI/CD pipelines to block non-compliant infrastructure deployments.
Automate the rotation of IAM roles and service account keys based on defined lifecycle policies and usage patterns.
Implement network segmentation through automated deployment of VPCs, security groups, and NACLs aligned with zero-trust principles.
Integrate vulnerability scanning tools into provisioning workflows to detect misconfigurations before resources go live.
Enforce encryption-at-rest and encryption-in-transit policies via IaC templates for databases, object storage, and data transfers.
Configure automated incident response triggers that isolate or terminate resources violating security policies.

Module 5: Managing Multi-Cloud and Hybrid Automation

Standardize automation interfaces across cloud providers using abstraction layers like Crossplane or Pulumi to reduce vendor lock-in.
Deploy consistent logging and monitoring agents across on-premises and cloud environments using configuration management tools.
Automate failover testing between cloud regions and on-premises data centers to validate disaster recovery runbooks.
Manage identity federation and SSO integration across hybrid environments with automated provisioning and deprovisioning.
Optimize data egress costs by scheduling cross-cloud data syncs during off-peak bandwidth windows.
Establish unified policy enforcement for resource quotas, tagging, and access controls across heterogeneous environments.

Module 6: Optimizing Costs Through Automation

Automate rightsizing recommendations by analyzing historical CPU, memory, and I/O utilization from monitoring systems.
Schedule start/stop automation for non-production environments based on team working hours and CI/CD activity.
Implement auto-tiering of storage (e.g., S3 Intelligent-Tiering) using lifecycle policies triggered by access patterns.
Deploy budget alerts with automated remediation actions such as instance downscaling when thresholds are exceeded.
Use spot instance automation with checkpointing for fault-tolerant workloads to reduce compute costs by up to 70%.
Track and attribute cloud spend to business units using automated tagging enforcement and chargeback reporting.

Module 7: Monitoring, Observability, and Feedback Loops

Automate alert threshold tuning based on historical performance baselines to reduce false positives in monitoring systems.
Deploy synthetic transaction checks to validate end-user experience post-automation changes.
Integrate observability pipelines that correlate logs, metrics, and traces to diagnose automation-induced failures.
Use automated anomaly detection to identify deviations in resource consumption after infrastructure changes.
Implement feedback mechanisms from production monitoring into CI/CD pipelines to prevent recurring issues.
Standardize dashboard templates across teams to ensure consistent visibility into automation health and performance.

Module 8: Scaling Automation Across the Enterprise

Define self-service automation catalogs with pre-approved templates to balance agility and governance.
Implement role-based access controls (RBAC) in automation platforms to restrict destructive operations by user role.
Establish centralized automation centers of excellence to maintain standards, share reusable modules, and resolve cross-team conflicts.
Automate compliance reporting for regulatory frameworks (e.g., SOC 2, HIPAA) using real-time configuration audits.
Measure automation maturity using KPIs such as deployment frequency, change failure rate, and mean time to recovery.
Manage technical debt in automation scripts by scheduling periodic refactoring and deprecation cycles.