Hybrid IT and Workload Placement Strategy: A Proven Approach for a Changing Landscape

Executive Summary

While cloud adoption continues, the assumption that every workload should move there has proven both costly and unrealistic.

Enterprises will continue to operate in a complex mesh of cloud, colocation, edge, and on-premises environments. Making the right placement decisions is critical. As more options become available, it is vital to have a framework you can apply to every new workload or whenever circumstances change – a “living” Workload Placement Strategy.

While sourcing options continue to expand, the principles of effective workload placement haven’t changed. Cloud economics are under pressure, platform licensing has become something no one expected a few years ago, and new infrastructure demands from GenAI and edge computing are reshaping what “best execution venue” really means. Successful organizations will have a deliberate, adaptable Workload Placement Strategy (WPS), driven by business goals, grounded in data, and executed with discipline.

This document outlines a structured, experience-driven approach to assisting IT leaders evaluate their environments, prioritize change, and position infrastructure to support both today’s realities and tomorrow’s needs.

Cloud adoption continues to grow, but not all implementations succeed. Gartner predicts 25% of organizations will have experienced significant dissatisfaction with their cloud adoption by 2028, due to unrealistic expectations, suboptimal implementation and/or uncontrolled costs.

To remain competitive, enterprises need a clear cloud strategy and effective execution. Gartner research indicates that those that have successfully addressed upfront strategic focus by 2029 will find their cloud dissatisfaction will decrease.^[i]

What’s Driving Change in Enterprise IT?

Enterprises face a host of new pressures.

• Gen AI workloads require specialized compute, massive data throughput, and real-time performance, challenging traditional infrastructure models.
• Cloud costs remain volatile, particularly in lift-and-shift or re-hosting scenarios where optimization is lacking.
• Licensing disruptions following Broadcom’s acquisition of VMware are triggering reassessments of virtualization strategy.
• Cloud repatriation is increasing, as organizations seek control, performance, or cost predictability by bringing select workloads back on-premises.

Together, these trends underscore the need for a clear and flexible Workload Placement Strategy that accounts for business priorities, technical fit, and the realities of a hybrid landscape.

Factors that drive the shift toward more intentional placement decisions include:

• Development pressure: New applications are typically built in the cloud, and developers expect rapid scaling and access to platform services.
• CapEx vs. OpEx tradeoffs: If you’re still managing your own data centers, capital investment decisions increasingly compete with flexible cloud alternatives.
• Cost misconceptions: Organizations can’t assume cloud will reduce costs automatically. Without re-architecture and governance, lift-and-shift migrations often lead to overspend.
• Governance and complexity: As environments become more distributed, workload placement decisions must be made with greater discipline to avoid fragmentation and risk.
• Multi-cloud reality: Even with the potential cost factors above, many enterprises now use multiple cloud providers, whether for resilience, performance optimization, strategic leverage, or just the flexibility this approach can offer.

Workload placement must be strategic, informed by data, and aligned across technical and business domains.

Establishing Strategic Direction

Before planning specific moves, organizations must first clarify their criteria. What does winning look like? What constraints or priorities shape how workloads should be placed or moved?

This directional thinking includes:

• Defining business outcomes and constraints: aligning placement strategy with business goals such as agility, resilience, risk tolerance, and financial governance, while accounting for constraints in budget, staffing, and timing
• Clarifying operating model preferences: considering how centralized vs. federated structures, platform ownership, and shared services affect placement decisions and long-term manageability
• Evaluating technology status and cloud orientation: identifying how such practices as platform engineering, internal developer platforms (IDPs), and site reliability engineering (SRE) fit within the organization’s appetite for cloud services, managed platforms, and infrastructure modernization
• Setting placement principles and decision criteria: establishing how we will evaluate tradeoffs across performance, security, latency, integration, and cost
• Anticipating operational complexity at scale: recognizing that shifts in placement may introduce new demands for observability, automation, and governance across increasingly distributed environments

A well-defined strategy provides direction for infrastructure decisions and room to adapt as business priorities change.

This approach recognizes that few organizations can execute wholesale transformation in a single phase. Instead, strategic direction gives structure to what may well be a multi-year effort.

Discovery and Dependency Mapping

Workload Placement Strategy begins with understanding what you have. That means not only collecting infrastructure and application data but also understanding how everything is connected.

Key areas include:

• Infrastructure discovery: servers, storage, network devices, and topologies
• Application mapping: where workloads run, how they interact, and who uses them
• Dependency identification: logical (e.g., application-to-database), physical (e.g., system-to-system), and operational (e.g., help desk, disaster recovery processes)

Modern tooling aids with discovery, but expert interpretation is critical. Tools do not replace the insight required to assess business function, shared services, and resilience impacts. However, tools that systematically leverage network traffic monitoring or server inventory can radically improve your understanding of the application infrastructure landscape.

By mapping and understanding dependencies early, organizations avoid costly surprises and minimize risk during change. This work also supports resilience analysis and prioritization based on business criticality.

Building the Workload Placement Strategy

With dependencies understood, the next step is to assess which workloads should be run elsewhere, which should remain in place, and why.

Placement decisions are multi-dimensional. Factors include:

• Integration and Dependency Mapping: When considering where a workload should run, you must know what it connects to, relies on, and supports.
• Performance Characteristics: Not all environments support all workloads equally, especially those with data locality, low-latency, or high-throughput requirements.
• Compliance, Security, and Data Residency: Data sovereignty, encryption standards, and access controls must be known and planned for from the start.
• Operational Fit and Support Model: Consider who will operate the workload, and how, if it moves to another hosting venue.
• Cost and Economic Viability: Cost decisions without context can lead to short-term gains and long-term regret.

A team comprised of stakeholders from Business/Product, Infrastructure, Application, Enterprise Architecture, DC/Cloud Ops, Governance/Risk/Compliance (GRC), and Finance should jointly guide this evaluation.

Planning the Path Forward

Once direction is set and workloads are assessed, organizations need a high-level roadmap that turns insight into action.

This roadmap should:

• Reflect known deadlines, events, or renewal cycles
• Sequence changes logically to reduce risk and balance capacity
• Flag transitional risk states, along with duration and mitigation plans
• Include resource and financial requirements across people, platforms, and partners

Managing the Hybrid Cloud

An effective strategy must align technical placement decisions with long-term manageability, supportability, and operational efficiency.

WPS focuses on where workloads belong, but it must also incorporate an understanding of how they will be supported in deployment. Hybrid cloud environments present persistent operational complexity that must be considered throughout planning and decision-making, not addressed after the fact.

Workload placement should inform IT management design, tooling, and architecture. As placement decisions potentially shift the application mix across environments, new management requirements may surface for how workloads are monitored, secured, or supported. A well-aligned WPS helps ensure these changes are communicated early, so operations can adapt in step with strategy.

Key elements of hybrid infrastructure management continue to include:

• Unified monitoring and observability to maintain visibility across cloud and on-prem environments
• Automated provisioning and configuration to ensure consistency and accelerate deployment
• Policy enforcement and governance to manage risk and maintain compliance across platforms
• Cross-platform root cause analysis to identify and resolve issues spanning multiple domains
• Integrated cost and capacity management to control spending and support informed planning

“Watch Items” as We Proceed

Organizations that have evolved into hybrid environments often encounter challenges when they later try to modernize or bring structure to that landscape. The transition from “how we got here” to “how we move forward” typically surfaces five issues:

• Inconsistent Data: Workload inventories, CMDBs, and dependency maps are often incomplete, outdated, or contradictory. Accurate decisions require reconciling the current state before making changes.
• Embedded Assumptions: Prior decisions, such as co-lo placements, “cloud first” mandates, or infrastructure investments, were made with the best available information at the time, but these assumptions can quietly constrain modern or future options.
• Operational Gaps: Hybrid sprawl often outpaces operational maturity. Tooling, monitoring, change control, and support models may not extend cleanly across environments, creating risk as strategy evolves.
• Stakeholder Misalignment: Business, security, finance, and IT often have different definitions of “best placement.” Without shared buy-in, efforts stall or result in less-than-comprehensive decisions.
• Timing Pressures: External events such as licensing changes, cloud renewals, or data center contract expirations may drive urgency that outpaces strategy.

Recognizing these challenges early allows teams to build a more resilient and modern plan.

About GTSG

At GTSG, we don’t believe in “on-the-job training” when it comes to critical infrastructure strategy. Our clients deserve experienced professionals, seasoned experts who bring deep industry knowledge and practical insight from day one.

What sets us apart is the ability not just to assess where workloads should run in an ideal world, but to anticipate the complex cascade effects and downstream impacts that real-world moves can trigger. This foresight only comes from experience.

Whether your organization is considering migration to the cloud, colocation, consolidation to a single on-premises data center, or any hybrid combination, you need a partner who understands the full business and resilience implications of those decisions.

With GTSG, you get:

• 100% experienced professionals who anticipate downstream consequences, applying proven methodologies
• True independence – we will not earn one dollar of commissions for recommending someone else’s product or service to you
• A highly competitive cost structure reflecting the seniority of our team and the lean efficiency of our organization
• Direct, committed engagement from leadership at a firm steeped in infrastructure strategy

We Hope This Has Been Helpful

If we can help you develop your strategy or move to new platforms as non-disruptively as possible, please write us at Partners@GTSG.com. Thanks.