Demystifying total costs of cloud and IT infrastructure

While enterprises have different perspectives and approaches to tackling IT challenges, the answer typically comes down to one thing: money. IT economics is one of the primary techniques that can help enterprises differentiate and choose among IT platforms, using cost as the metric.

DXC Technology provides guidance on choosing the best and most cost-optimized platforms and systems for business applications. We tap into our extensive expertise in delivering advanced IT solutions across the globe to help enterprises find the best path to digital transformation. To enhance our expertise, DXC uses a total cost of ownership (TCO) tool developed by Hitachi to help enterprises compare the total costs of different platforms at a high level, using unit cost modeling. We then drill deeper to provide a more detailed analysis. Let’s explore the various parameters that we consider when determining cloud and IT infrastructure TCO.

Platform Principles

In general, one style of IT deals with legacy systems that are often on-premises. Another style of IT deals with new systems that are often in the public cloud. A third style is a hybrid cloud model, in which systems are a mix of on-premises private cloud and public cloud. Regardless of the style, several long-standing principles remain true when determining platform costs:

• Transformation of IT platforms must demonstrate a clear business benefit or differentiation.
• Organizations often need consulting help for analyzing, considering or changing IT modes.
• Planning is key to ensure that the IT style fits the required applications, or else unexpected costs could be incurred.
• The right platform can be defined in multidimensional terms of performance, cost, security, growth, management and risk.

With years of cloud history behind us, we have a clear understanding of what platform or architecture fits a specific business situation. DXC has helped enterprises across the globe identify and implement effective IT infrastructure solutions that deliver massive business benefits while reducing costs. In one case, Zurich Financial Group cut provisioning costs by 30 percent by moving workloads to the cloud.

There are industry and customer-tailored assessment methods that align operational qualities with business qualities, separate from the platform. DXC helps enterprises use IT economics and total cost models to identify the optimal platform delivery choices, based on unique customer operating conditions and cost sensitivities.

While it is important to maintain the status quo of buying (depreciating), operating and refreshing IT assets in the local data center, other options should also be evaluated. Cloud options include moving to private cloud, where assets are consumed but typically not purchased; a private cloud can be on-premises or offsite, and can be managed by an outside firm or by the current IT staff. Hybrid extends the private cloud, where some part of the infrastructure can be deployed in a public cloud.

By comparing total costs for each platform decision, DXC can assist enterprises before they make short- and long-term business commitments. We recommend the following multidimensional cost approach.

Total cost calculations and comparisons

Over the past few decades, we have learned that the total cost of IT is much more than the purchase price. For one, we now know that public cloud architecture costs are greater than the subscription rates. Much has been written about all the cost elements that make up IT TCO, including a white paper by Hitachi. Not all costs are equal in weight and impact.

Cloud costs also have a variability that is often overlooked. We frequently see cost exclusions related to cloud in areas such as added networks, onboarding, offboarding, overuse of tariffs and operational risks that include data center security, power, cooling and so on. A multidimensional approach is needed to define and optimize costs.

When customers ask how to reduce or measure costs, the answer always includes: “It’s complicated.” Using IT economics and then contrasting the do-it-yourself (DIY) versus private versus public cloud costs, we can quickly establish the “complicated” variables in creating cost and architecture comparisons.

The deterministic variables are:

Each industry has different regulations, security and protection needs. Even though no two companies are alike, within an industry, patterns and trends can affect solution costs:

• Federal standards, compliance regulations and security protocols can have a significant impact on whether some data  storage or data processing can be done outside of a secured environment in the cloud.
• Data sovereignty requirements differ greatly by industry and country. For federal (and some state and local) organizations, data sovereignty introduces new risks when considering public cloud offerings. Public cloud providers can move data and processing to locations that are beneficial to the provider, but may therefore violate some data locality requirements.
• Some industries, such as telecommunications, prefer capitalization of assets.

Data infrastructure hygiene refers to protecting, preserving and optimizing the data infrastructure for superior performance. A top objective of this relates to minimizing costs related to operating and maintaining the data infrastructure. A key consideration is the age of assets, which affects decisions in this way:

• If the on-premises, owned assets are approaching end of life, it might be a good time to consider private or public cloud options for some of the assets.
• If the assets are relatively new, taking an asset write-down will only add extra costs to a cloud transformation. Newer systems should stay in place and be fully depreciated (“sweat the asset”).
• Sometimes refreshing old hardware with newer hardware will provide a lower total cost compared to the higher maintenance and environmental costs of keeping old gear.

Greenfield investment or transformation

When a new system or environment is being planned, hosting the greenfield environment in a public or private cloud is usually the lowest-cost option. This is especially true for quick-start development activities, where mean time to deliver a virtual machine (VM) is measured in minutes, not weeks. 

For traditional systems, the transformation to the cloud can be an expensive, onetime investment. Not all applications or systems work well in the cloud. We tend to see high-cost cloud transformations where applications and systems not built for the cloud are moved there anyway, regardless of application needs.

Workload type

Data is the lifeblood of enterprise computing, and workloads are the means of dealing with the data. These workloads have a huge influence on cost decisions:

• Development/test. These systems often favor cloud because it can accommodate rapid deployment and the need to scale up and down.
• Internet of Things (IoT)/Analytics. This is a new category and poised to be cheaper in the cloud. Cloud vendors can offer data-lake and ingestion services for the back end, and front-end analytic tools in a turnkey package.
• Production applications. These are business critical and tend to be on-premises because performance requirements and network latency can be addressed. Also, processing and storage can be secured in a private facility and network.
• Virtual desktop infrastructure (VDI). VDI favors cloud or hosted cloud with many small operating systems and application servers.
• Database management systems (DBMS). These systems favor on-premises solutions because of security and performance requirements. 

Continue reading more about the help avilable for IT planners, cloud and IT infrastructure cost examples, and the economics of cloud.