Description

This curriculum spans the technical breadth of a multi-workshop program on virtualization in DevOps, comparable to an internal capability build for managing CI/CD environments with production-grade infrastructure automation, security controls, and performance tuning across VMs and containers.

Module 1: Foundations of Virtualization in CI/CD Pipelines

Selecting between full machine virtualization (e.g., VMware, KVM) and container-based isolation (e.g., Docker) based on build environment fidelity and startup latency requirements.
Designing VM templates with pre-installed toolchains to reduce pipeline initialization time in Jenkins or GitLab Runners.
Implementing snapshot-based rollback mechanisms for build environments to ensure reproducibility after dependency updates.
Configuring secure boot and TPM emulation in VMs used for signing artifacts to meet compliance requirements.
Managing VM sprawl in CI systems by enforcing auto-termination policies after pipeline completion.
Integrating virtualization layer logs with centralized monitoring to detect pipeline performance bottlenecks tied to hypervisor contention.

Module 2: Hypervisor Selection and Infrastructure Integration

Evaluating Type 1 vs Type 2 hypervisors based on security boundaries, performance overhead, and support for nested virtualization in development environments.
Automating VM provisioning via Terraform or Ansible against vSphere, Hyper-V, or libvirt APIs with idempotent configuration scripts.
Allocating CPU pinning and memory reservations to critical VMs hosting integration test suites to prevent resource starvation.
Implementing live migration policies for long-running test environments to enable host maintenance without disruption.
Enforcing network segmentation between development, staging, and production VMs using VLANs or NSX-T policies.
Validating hardware-assisted virtualization (Intel VT-x/AMD-V) availability across physical hosts before deployment.

Module 3: Containerization and Lightweight Virtualization

Choosing between Docker, Podman, or containerd based on rootless execution needs and daemonless operation requirements.
Configuring seccomp, AppArmor, and SELinux profiles to restrict container capabilities without breaking application functionality.
Implementing ephemeral containers for testing to prevent state leakage across test runs.
Managing container image trust using Notary or Cosign for signed, verifiable image deployment.
Optimizing image layers to reduce pull times in distributed build agents across regions.
Integrating container runtime metrics with Prometheus for visibility into memory and CPU usage per build job.

Module 4: Infrastructure as Code for Virtual Environments

Versioning VM configurations in Git using Terraform modules with environment-specific variables for dev, test, and prod.
Implementing state locking via remote backends (e.g., S3 with DynamoDB) to prevent race conditions during parallel VM changes.
Using Packer to build golden images with hardened OS baselines and pre-cached dependencies.
Enforcing policy-as-code with HashiCorp Sentinel or Open Policy Agent to block non-compliant VM configurations.
Automating drift detection by comparing running VM configurations against IaC templates in CI.
Designing reusable module interfaces that abstract virtual network, storage, and compute for multi-cloud consistency.

Module 5: Networking and Service Isolation in Virtualized DevOps

Configuring CNI plugins (e.g., Calico, Cilium) to enforce network policies between microservices in test clusters.
Setting up service meshes (e.g., Istio, Linkerd) in staging VMs to simulate production traffic routing and fault injection.
Implementing DNS isolation for parallel test environments using Consul or Kubernetes DNS scoping.
Managing NAT and port forwarding rules for developer-accessible services running in private VM networks.
Allocating static IP addresses to integration test databases to maintain stable connection strings.
Monitoring network throughput between VMs and containers to identify bottlenecks in data-intensive pipelines.

Module 6: Storage Management and Data Persistence

Selecting between ephemeral, persistent, and shared storage for VM-based build agents based on artifact retention policies.
Configuring NFS or iSCSI mounts for centralized artifact repositories accessible across VM pools.
Implementing LVM snapshots for database test environments to enable fast reset between test suites.
Encrypting virtual disks at rest using LUKS or platform-managed keys (e.g., AWS KMS, Azure Disk Encryption).
Managing container volume lifecycles to prevent orphaned data accumulation on host systems.
Optimizing I/O performance by aligning VM disk types (thin vs thick provisioned) with workload access patterns.

Module 7: Security, Compliance, and Lifecycle Governance

Enforcing VM patching schedules using automation tools (e.g., Ansible, Puppet) to meet internal audit requirements.
Integrating vulnerability scanning (e.g., Trivy, Clair) into VM and container image builds.
Implementing role-based access control (RBAC) for VM management interfaces across developer teams.
Archiving and decommissioning stale VMs based on inactivity thresholds and tagging policies.
Conducting periodic access reviews for privileged virtualization accounts (e.g., vCenter, libvirt).
Generating compliance reports for VM inventory, configurations, and change history using CMDB integrations.

Module 8: Performance Optimization and Scalability

Right-sizing VMs for specific pipeline stages (e.g., larger instances for integration tests, smaller for linting).
Implementing auto-scaling groups for VM-based runners based on queue depth in CI systems like GitHub Actions.
Monitoring hypervisor-level metrics (CPU ready time, memory ballooning) to detect resource contention.
Using CPU and memory overcommit ratios cautiously in non-production environments with clear SLA trade-offs.
Optimizing boot times via initramfs trimming and service disabling in VM templates.
Load-testing virtualized environments under peak CI concurrency to validate infrastructure capacity.