Description

This curriculum spans the technical, operational, and governance dimensions of virtualization capacity management, comparable in scope to a multi-phase infrastructure transformation program involving readiness assessment, platform selection, policy design, and ongoing optimization across hybrid environments.

Module 1: Assessing Virtualization Readiness Across Business Units

Conduct inventory audits of physical server utilization rates to identify underused assets suitable for virtualization.
Evaluate application dependencies to determine which workloads can be safely migrated without disrupting business operations.
Engage application owners to assess tolerance for shared infrastructure and potential performance variability.
Map regulatory and compliance constraints (e.g., data residency, audit trails) that may restrict virtualization scope.
Define criteria for workload classification (e.g., Tier 1 vs. Tier 2) to prioritize virtualization candidates.
Document existing support models and SLAs to anticipate changes in incident ownership post-virtualization.
Establish baseline performance metrics for CPU, memory, disk I/O, and network usage prior to migration.

Module 2: Designing Virtual Infrastructure Capacity Models

Select appropriate consolidation ratios based on historical peak usage, not averages, to avoid overcommitment.
Incorporate burst capacity requirements into capacity models for applications with variable workloads.
Model VM sprawl risk by defining quotas and approval workflows for VM provisioning.
Size host clusters to accommodate live migration and high availability without overloading remaining nodes.
Factor in hypervisor overhead (typically 5–10%) when calculating usable capacity per physical host.
Integrate storage latency and throughput constraints into VM placement decisions.
Define memory overcommit policies with safeguards for memory ballooning and swapping.

Module 3: Selecting Virtualization Platforms and Licensing Models

Compare vSphere, Hyper-V, and KVM based on existing skill sets, integration with backup systems, and support contracts.
Negotiate enterprise licensing agreements that align with long-term VM growth projections.
Assess per-core vs. per-socket licensing implications in high-core-count server environments.
Evaluate open-source solutions for non-mission-critical workloads to reduce licensing costs.
Determine support for GPU passthrough or SR-IOV for specialized applications.
Validate compatibility with existing monitoring, patching, and configuration management tools.
Plan for vendor lock-in risks when adopting proprietary management consoles or APIs.

Module 4: Implementing Resource Allocation Policies

Assign CPU and memory reservations for critical VMs to guarantee minimum performance levels.
Configure shares and limits to prioritize resource access during contention events.
Implement dynamic resource scheduling (DRS) rules with anti-affinity constraints for high-availability pairs.
Define storage QoS policies to prevent noisy neighbors from degrading I/O performance.
Enforce naming conventions and tagging standards for VMs to support chargeback and reporting.
Integrate resource policies with change management systems to audit configuration drift.
Set thresholds for automated alerts when resource usage exceeds defined baselines.

Module 5: Managing Storage and Network Virtualization Dependencies

Size shared storage arrays to support peak IOPS demands across all VMs on a host.
Implement thin provisioning with monitoring to prevent over-allocation and storage exhaustion.
Design VLAN and VXLAN segmentation strategies to align with security and compliance zones.
Configure NIC teaming and load balancing policies to optimize network throughput and redundancy.
Plan for storage vMotion compatibility across heterogeneous storage platforms.
Validate snapshot retention policies to avoid performance degradation and storage bloat.
Coordinate with storage and network teams on firmware and driver compatibility.

Module 6: Governing VM Lifecycle and Decommissioning

Implement automated VM provisioning workflows with mandatory business justification fields.

Enforce mandatory review periods for VMs before approval to prevent unauthorized deployments.

Conduct quarterly VM rationalization audits to identify orphaned or underutilized instances.

Integrate decommissioning processes with asset management systems to update CMDB records.

Define data retention requirements for VM backups and snapshots post-deletion.

Establish ownership accountability for VMs through designated system owners.

Monitor VM creation-to-retirement cycle times to identify governance bottlenecks.

Module 7: Integrating Virtualization with Capacity Planning Processes

Align virtualization capacity reviews with enterprise IT financial planning cycles.
Forecast hardware refresh needs based on VM density growth and host end-of-life dates.
Model the impact of new applications or cloud migrations on on-premises VM capacity.
Use predictive analytics to identify capacity shortfalls 6–12 months in advance.
Coordinate with cloud teams to evaluate hybrid scenarios when on-premises capacity is constrained.
Adjust capacity models to reflect changes in workload patterns (e.g., remote work, seasonal peaks).
Document assumptions and constraints in capacity models for audit and review purposes.

Module 8: Monitoring, Reporting, and Continuous Optimization

Deploy performance monitoring tools that correlate VM metrics with application performance.
Generate monthly capacity utilization reports segmented by business unit and application tier.
Identify underutilized hosts for potential rebalancing or hardware retirement.
Conduct root cause analysis on recurring resource contention events.
Validate capacity model accuracy by comparing forecasts to actual usage trends.
Adjust DRS and load-balancing thresholds based on observed migration patterns.
Establish feedback loops with application teams to refine performance expectations.