The Importance of a Workload Placement Strategy

The data centre strategy of an enterprise is a critical component of the IT strategy and, consequently, they must be closely aligned. In the cloud-mobile era, data centres have become part of the fabric of enterprise IT, and the data centre strategy is built around the applications that drive the digital transformation initiatives

The IT organisation needs to evaluate the appropriate model to support them. More specifically, they need to look at the requirements of individual workloads, as these are the units of deployment in an agile IT infrastructure.

There are many effective ways to classify workloads. Microsoft’s model focuses on the criticality scale breaking workloads into 6 categories:


Affects the company's mission and might noticeably affect corporate profit-and-loss statements.


Affects the mission of a specific business unit and its profit-and-loss statements.


Might not hinder the mission, but affects high-importance processes. Measurable losses can be quantified in the case of outages.


Impact on processes is likely. Losses are low or immeasurable, but brand damage or upstream losses are likely.


Impact on business processes isn't measurable. Neither brand damage nor upstream losses are likely. Localised impact on a single team is likely.


No business owner, team, or process that's associated with this workload can justify any investment in the ongoing management of the workload.


Plotting workloads is important to gain an insight into where and how to invest, because each of the four workload categories demands a different approach:

  1. Invent: Core applications in Dev-Test stage start out as non-mission critical applications and are typically designed to provide a competitive business edge. Agility to facilitate innovation is the key infrastructure and operations requirement.
  2. Deploy to scale: When core applications are deployed in a production environment, they become mission critical. As a result, the infrastructure and operations requirements shift to reliability and performance.
  3. Manage scale: When mission-critical applications are no longer core and become mainstream (e.g. ERP systems), the infrastructure and operations requirements shift to efficiency.
  4. Offload: When context applications are neither mission critical nor core (e.g. email) they can be offloaded to a deployment model suited to the most efficient use of resources (e.g. SaaS).

Most mid- or large-sized enterprises have workloads in each of these four categories, and there are no absolutes in terms of preferred deployment models for each of the four categories, as different performance, compliance, data sovereignty and/or customisation requirements apply.

The probable conclusion from a workload classification exercise is that for most enterprises a hybrid IT environment is desirable, as different workloads have different infrastructure and operational requirements.

In a hybrid model, people, processes and applications are connected to each other, yet sourced from multiple locations and from a variety of providers. This creates at least two new challenges for IT organisations that are on the journey to becoming a Digital Enterprise. Firstly, how to seamlessly and securely interconnect the different public and private IT environments, and, secondly, how to create an agile IT delivery model allowing workloads to shift from one environment to the next or back.

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