Infrastructure costs went up. Here are the decisions that brought them back down.

The VMware renewal premium no longer matched what the workloads required. The environment needed enterprise virtualization, HA, DR, storage and support — not necessarily VMware.

Mapped workload dependencies, validated the replacement hypervisor against compute, storage, networking, HA/DR and operating requirements, then moved workloads in planned waves.

The VMware requirement was still valid, but the incumbent procurement structure made the renewal more expensive and less flexible than the technical requirement justified.

Validated the required core footprint, term and support requirements, then compared the renewal against a managed VCSP procurement path.

A 420-location environment had network cost, cloud egress and workload placement moving together, but they were being evaluated as separate decisions.

Modeled provider consolidation, traffic paths, cloud connectivity and workload placement against one future-state infrastructure run rate.

AWS consumption and VMware licensing were both under cost pressure, but treating them independently hid how one infrastructure decision affected the other.

Rightsized cloud consumption and the VMware footprint together, then modeled the resulting infrastructure run rate as one decision.

Eight plants supporting ERP, MES and multi-cloud traffic were approaching a network decision while cloud-transfer costs were becoming part of the same operating expense.

Evaluated WAN architecture, private connectivity, cloud traffic patterns and workload placement together instead of renewing the carrier design in isolation.

The business had a viable AI use case, but data architecture, infrastructure placement, control requirements and ongoing consumption were not ready to support it.

Pressure-tested the data path, infrastructure requirements, governance model and AI operating economics before scaling the application.

A legal environment with roughly 900 employees and two data centers faced a VMware renewal at the same time as server and VDI infrastructure decisions.

Evaluated the retained VMware footprint, hardware requirements, VDI dependencies and data-center options as one connected lifecycle decision.

The client removed more than 45% of its VMware footprint through Azure movement and rightsizing, yet the incumbent renewal still increased.

Rebuilt the retained VCF requirement, validated the remaining core footprint and changed the procurement structure while preserving continued write-down flexibility.

A legal organization of roughly 1,100 people, including about 650 attorneys, was adopting AI faster than governance, tooling visibility and consumption controls could keep up.

Modeled approved tools, shadow AI, token consumption, data requirements and governance as one operating framework.

A professional-services environment with roughly 1,200 employees and 1,450 identities had Microsoft licensing, security, support and Copilot decisions overlapping.

Modeled entitlements, identity counts, security overlap, Azure dependencies, CSP/MSP roles and AI licensing together.

The VMware renewal was based on Broadcom’s core-count inventory, even though much of the environment was oversubscribed. On top of that, several VCF services included in the renewal would not actually be used.

Reviewed the actual workloads, reduced the licensed core count by 22%, removed VCF services that were not needed, and rebuilt the renewal around what the environment really required.

AWS and VMware were being managed as two separate cost problems, even though the same applications and infrastructure decisions were driving both bills.

Reviewed the AWS environment, reduced unnecessary cloud spend, and moved the VMware workloads that still needed VMware into a managed VCF platform.

The company was paying about $30K a month in cloud egress charges. Moving the application was not necessary to fix the cost.

Changed how the traffic left the cloud and how it connected to the network, without moving or redesigning the application.

The VMware renewal was being handled as a pricing exercise. The bigger opportunity was to first determine how many cores and which VMware products were actually needed.

Reviewed the core count, VMware products, support requirements, and alternate ways to buy VMware before the renewal was signed.

A large VMware environment was approaching a licensing decision and wanted to reduce its dependence on VMware without creating unnecessary migration risk.

Used automated discovery and migration planning to identify which workloads could move and then migrated them from VMware to native cloud services in planned waves.

Nearly 900 VMware VMs had to be addressed before the next licensing decision. The company wanted to move quickly without turning the migration into one massive cutover.

Moved the environment in phases, retiring older systems and moving the remaining workloads to native cloud services over time.

On-premises infrastructure was getting more expensive, difficult to scale, and harder to protect with the existing disaster-recovery setup.

Moved critical workloads to cloud infrastructure and replaced older backup, firewall, and VPN tools with cloud-based services.

Growth was putting pressure on the existing infrastructure. Users were seeing latency, capacity was getting tight, and telecom and operating costs kept rising.

Moved most of the infrastructure to a hybrid cloud design, added private SASE connectivity, and placed compute closer to the users who needed it.

The cloud migration happened quickly, but cloud costs were not being managed closely enough afterward. Resources were oversized, discounts were being missed, and teams lacked clear ownership of spend.

Right-sized resources, applied Microsoft licensing benefits, shut down resources when they were not needed, added policies, and used reservations for predictable workloads.

The company was paying for the same private-cloud capacity whether it was using it or not.

Moved the infrastructure and a major business application to public cloud services where capacity could grow and shrink with demand.

Too much money was going into physical servers, separate database licenses, renewals, maintenance, and security for a large database environment.

Consolidated more than 90% of the back-end databases onto cloud infrastructure instead of maintaining them separately.

A global application platform needed strong local performance and security, but the company did not want to keep paying for enough fixed infrastructure to handle occasional peak demand.

Moved the core applications to cloud infrastructure that could scale up when demand increased and scale back when it did not.

The old network backbone was expensive, complicated, and made it difficult to connect directly to several public clouds.

Replaced the legacy backbone with software-defined connections located closer to the cloud providers.

Connecting workloads in colocation facilities to public cloud environments was too expensive and required too much manual network work.

Replaced traditional connections with virtual circuits that could be turned up between regions and cloud providers as needed.

The company depended too heavily on expensive MPLS from a single carrier, making the global WAN costly and difficult to change.

Rolled out secure SD-WAN and used local internet connections where they made sense instead of forcing every site onto MPLS.

A global manufacturer needed more bandwidth and a faster way to connect new international offices, but the existing MPLS network was too expensive and slow to expand.

Replaced MPLS with a managed SD-WAN service across four continents.

The global network needed much more bandwidth, but simply buying more of the same legacy WAN would have made the cost problem worse.

Moved to managed SD-WAN and changed how sites connected to the global network.

Every new cloud connection took too long and required too much manual network work.

Centralized the cloud network and automated the connections between cloud environments and outside partners.

Connecting clouds, data centers, and partners required a large network team and weeks of engineering work.

Moved to a cloud-based network platform with one place to manage policy, connectivity, and security across environments.

The disaster-recovery environment took up 20 cabinets and carried all the power, space, and infrastructure cost that came with them.

Rebuilt DR in a higher-density colocation design while keeping the required replication and availability in place.

The internal IT team was spending too much time and money maintaining servers, redundancy, disaster recovery, equipment, and security.

Moved the servers into managed colocation and replicated applications and data to a cloud-based recovery environment.

Employees were working across older communication tools and disconnected systems. The same data had to be entered more than once, which wasted time and created extra support cost.

Moved communications into Microsoft Teams, automated repetitive workflows, built a modern Azure data platform, and consolidated IT support.

The company wanted employees to use Copilot at scale, but it also needed security, governance, training, and real adoption — not just licenses sitting unused.

Rolled out Microsoft 365 Copilot with structured training, internal champions, governance, and custom agents for specific work.

Employees in financial services were spending too much of their day writing meeting notes and completing follow-up work after client calls.

Put Copilot directly into the tools employees already used for meetings, documents, email, and client work.

Employees were wasting time searching through documents and systems to find policies, procedures, and internal answers.

Built an AI agent that could search Microsoft knowledge sources and service systems and return the answer in one place.

Customer-support teams were spending too much time routing cases, handling repetitive work, and escalating issues that could have been resolved sooner.

Added AI assistance, automation, and smarter routing directly into the cloud contact center.

The contact center was relying on older tools, too many conversations were reaching live agents, and call abandonment was too high.

Moved to a cloud contact center and added conversational AI to handle more chat and digital requests automatically.

Scheduling and contact-center tools were disconnected, making it harder to staff correctly and manage productivity.

Brought the channels together and used actual contact data to improve scheduling and outbound work.

Managers and employees were spending too much time on repetitive administrative work that did not require their expertise.

Tested Copilot against ten real business tasks first, measured the results, and used those results to decide where to expand it.

A very large global workforce was using too many overlapping collaboration and productivity tools, which increased cost and made work inconsistent across regions.

Standardized the company on Microsoft 365 and Copilot while still allowing regions to configure the tools for local needs.