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Yevhenii Sukhov
CTO
No matter the scale of operation, regular IT infrastructure costs grow restlessly, and to stay competitive, teams and businesses must simultaneously grow their investments in IT and in capacity-boosting technology (like generative AI, machine learning, smart automation, etc.).
This can be pretty difficult to do, and even impractical at the outcome, unless you approach things insightfully. While investing heavily in IT departments and tech/digital maintenance, many companies still fail to achieve visible effects and yield returns from their efforts (for a bunch of reasons highlighted below).
Do you overspend on your IT infrastructure? Then using this article’s proven strategies for smoothing out the edges and optimizing expenses will help save major costs and get more returns and profits.
There are numerous potential factors that can hinder a business’s financial plan, making them vainly overspend rather than efficiently allocate their IT resources.
Legacy and monoliths
Legacy software (CRMs, ERPs, custom business platforms, etc.) may not be out of date, but it usually flies right under all relevant market trends, so it is overly complex and difficult to manage and scale due to that stale infrastructure. This can be reflected in multiple aspects:
Vain usage of legacy solutions and poor outlook of the tech stack as a whole leads us to the point where we easily let hidden costs seep into our budget, especially when it comes to the ongoing cloud infrastructure costs.
Businesses often come across seemingly profitable all-in-one plans or fixed cloud platform tariffs, believing they will save expenses long-term. That’s not always true, and delegating software systems under the full control of the platform/cloud provider is not always such a great idea.
Even when covering relatively moderate expenses, you may still be overpaying for stuff you don’t use regularly or at all. In 2022, Zylo made a good, exhaustive report, stating that average organizations tend to employ only 60% of the SaaS licenses they have. At the same time, companies tend to add at least eight new apps to their tech stacks every thirty days. And those are mid-pandemic readings.
Manual processes are the most expensive to manage, each task and workflow, however small and routine, taking up time and productivity resources. You should try and minimize those in order to get rid of time- and mental effort-consuming routines.
If you haven’t yet, it’s high time you indulged in all the fruits of smart automation and, especially, DevOps, which aligns purely technical tasks with managerial and operational workflows, making things that much easier.
Just for a big picture of things — over 80% of surveyed companies and IT decision makers either implement or prioritize the implementation of DevOps today. But you probably already knew that.
Even more hidden expenses can be generated by the idle performance of legacy or under-optimized databases. Like a legacy platform, an on-premise database that was adopted by a business a long time ago may still work just fine. Through the years, it also becomes packed to the brim with essential data assets and BI.
It is extremely important to keep such databases flexible, scalable, and up-to-date throughout. Otherwise, you may simply not be able to migrate all the data it packs without losses, let alone all the expenses an internal system refactoring or full switch of the database system would require.
Here’s a pressing question — in general, how efficiently does your tech or development team conducts software deployments? Integration and deployment practices go stale along with the software that goes out of trend and turns legacy.
Your company- or project-wide software deployment practices are irrational and prone to generate more unnecessary IT infrastructure costs if:
Apart from unwanted and growing expenses, other effects of a poorly organized, insufficiently managed, or under-optimized IT infrastructure can be plenty, pretty negative, and expensive.
You can be spending an extra 15% of the budget each year just on legacy software maintenance. All the overspending that results from poor IT infrastructure management adds up to a separate article of expenditure that you ultimately don’t have to cover.
Old software or poorly integrated infrastructure processes provoke overall performance bumps and the inability of business systems to work at a rapid capacity under stress loads.
Platforms that take too long to process forms, fail to respond quickly, or are inaccessible in other ways affect the entire user experience, which in turn lowers user/customer satisfaction rates.
An outdated or limited-in-features system may not be as reliable in data protection and compliance with some of the latest regulations (like GDPR or the upcoming Europe AI Act).
Systems that work with personal user data or consumer information, like eCommerce, healthcare, or real estate platforms, are the most important to keep properly updated to protect valuable or confidential data.
One data leak or regulative violation may cost too much — your customer’s trust and brand’s reputation.
A stale IT infrastructure drags a business behind, not letting it adapt to expanding customer audiences and growing demands, business-wise or technological. A legacy software system that you cannot gradually build up in capacity is limited in performance.
It cannot handle the necessary peak loads over time. All in all, the bad IT infrastructures we’re talking about in this article aren’t scalable ones.
Yes, investing in DevOps and sufficiently managing tech support is not always a guarantee of cost-efficiency. For one thing, working in complicated, low-performance environments, DevOps engineers must dedicate more time to mending infrastructural flows than to actual work on the project.
Another recurring question is the lack of automation in the DevOps and software support practices. Manual DevOps and support take more time, spawn more risks, and cost dramatically more in the long run.
Do you still overspend on your IT infrastructure management? Let’s audit your system and find ways to optimize it.
Now that we have a good outlook of all the negative effects and outcomes of under-optimized infrastructures, let’s move on to actually figuring out how to prevent and eliminate all of the above.
Mainly, we’ll learn how to reduce IT infrastructure costs by using proven, relevant methods and tech solutions. Each of the strategies described below helps lower extra expenses across the board, including hardware and maintenance, virtualization and resource allocation, development and support, security, and compliance costs.
A smart approach to leveraging available cloud tech would be to move the whole IT infrastructure to the cloud. Or, at least its digitized parts and tools. This can be done with the help of a cloud-based IaaS — Infrastructure-as-a-Service platform.
As for the choice of cloud platforms to power the whole thing, your most proven options are Azure or AWS.
Originally a hybrid team/workflow structuring methodology, DevOps has formed a huge market of its own and maximized the use of containerization solutions in ongoing development projects. Docker and Kubernetes being the two main tools of choice for most DevOps specialists.
The containerization allows DevOps engineers to “pack up” and deploy applications in containers, which makes things simpler, faster, and less error-prone. This also helps a lot in optimizing costs of IT infrastructure by saving time and other workflow resources through virtualization.
The platforms are equally popular in use, according to stats, and skills in Kubernetes and Docker containerization were the most demanded among all DevOps skills according to the worldwide DevOps tech stack analysis conducted in 2024.
Legacy software systems are usually monolithic in their architecture, which means they are built as a whole block, making it difficult to enhance and integrate them. If that is your case, you can try and migrate from the monolithic to a much more flexible and manageable microservice architecture.
With this “block-based” type of architecture, the software is broken down into modules — separate services, each with its own function or responsibility. You can tweak and scale these modules independently, which means three things:
Automated resource allocation and scaling help reduce IT infrastructure costs by dynamically matching your infrastructure’s capacity to your actual workload in real time.
Instead of provisioning fixed resources that might remain underused, e.g., during off-peak times, automation allows your system to automatically “scale out” (add resources) when demand grows and “scale in” (remove resources) when demand drops.
This not only optimizes performance but also minimizes wasted computing power, energy, and operational costs.
The pay-as-you-go or PAYG model enables businesses to pay only for the cloud resources they consume rather than committing to large, fixed-capacity contracts. This flexibility means that during off-peak times, you aren’t paying for idle capacity, and during demand spikes, you can scale up quickly without major direct expenses.
This model helps manage a more agile and responsive infrastructure, helping organizations avoid over-provisioning and minimizing waste, which surely saves felt costs over time.
Database optimization will require tuning and refining database systems to improve query performance, reduce latency, and maximize throughput. Techniques such as indexing, query optimization, partitioning, and smart resource allocation help make sure that the database runs up to the business’s needs.
An optimized database minimizes the load on underlying hardware, reduces energy consumption, and delays the need for costly upgrades. Ultimately, it enhances the user experience and supports smoother business operations.
Integrating security and compliance directly into your infrastructure minimizes the risk of breaches and regulatory fines. Built-in security features — such as automated patch management, encryption, access control, and live monitoring — reduce the need for extra third-party tools and manual oversight.
This helps stick with industry standards, protect sensitive data, and maintain operational integrity, ultimately reducing the potential financial and reputational costs of covering security incidents.
Implementing Continuous Integration and Continuous Deployment automates the software development lifecycle, from code integration to testing to deployment. This automation speeds up release cycles and minimizes human error, reducing downtime and the cost associated with manual deployments.
By integrating testing early and often, CI/CD pipelines catch issues before they escalate, ensuring more stable releases and lower operational overhead. In essence, a robust CI/CD process not only improves developer productivity but also lowers the total cost of ownership by reducing errors and accelerating time-to-market.
Don’t know which method suits you best? Let’s analyze your business and craft an optimization plan.
The question you might have by now is whether it’s possible to enhance an existing IT infrastructure and cut out unnecessary costs without actually disrupting the running processes (and spawning more real-time expenses)?
This is quite possible, but there are “if”s — certain limitations are pretty impossible to avoid altogether, like:
We had the pleasure of implementing a project that required an IT infrastructure rehaul and improvement to engage more active users at a balanced cost. We ended up working through a multi-angled approach, where we automated, optimized, and freshened up the existing infrastructure.
To analyze the results, here’s a post-case IT infrastructure cost breakdown:
With a 25 times (!) larger user base, Project B operates at lower infrastructure costs. This is achieved through a carefully optimized architecture, ensuring both efficiency and scalability.
For a similar project like Project A, forecasted savings indicate that infrastructure expenses could be reduced by up to 5X, from $1,000 to $150–$200 after implementation.
As such, this case is a vivid demonstration of how much companies can optimize and boost their performance and productivity simply by working on and bettering what they already have in place.
We can implement a similar case for you — entrust us with your vision and we will help you see it in action, however abstract or demanding it may be.
While it can be highly beneficial long-term and lower expenses in a major way, infrastructure optimization is a very responsible, sensitive undertaking. If you’re up for it, make sure to consider these essential pitfalls and challenges.
Outdated applications might not run seamlessly in a modern environment. Legacy systems often require formidable modifications — or even partial rewrites — to achieve full-on compatibility and maintain performance.
Shifting to a new infrastructure may call for more changes in your application’s architecture. In many cases, certain modules will need to be rewritten to match modern standards, adding both time and cost.
Moving databases to a new platform is rarely instantaneous. A well-thought-out migration plan is essential to minimize downtime and grant data integrity throughout the transition.
The process of adapting legacy systems and reengineering code demands specialized expertise. Engaging experienced professionals can help manage a smooth transition, avoid common risks, and prevent expensive errors.
As you can see, this article packs a lot of insights on infrastructure pains, ideas, and guiding tips for implementing infrastructure optimization. However, it is equally important to weigh out your priorities and understand when such an undertaking would NOT be the best thing to set in motion.
There is no sense in going for IT infrastructure optimization when:
When you run a software system for a digital tech or business foundation (or both), covering all the underlying IT infrastructure costs can turn into a challenge of its own. Depending on the scale of operations, keeping the software intact and updated can be resource-intensive as is.
However, after reading this article, you should get a good idea of how to minimize the costs for IT infrastructure in the most relevant and proven ways. One last thing you need to set things in motion and actually start optimizing is a trusty tech specialist.
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Yevhenii provides deep technical insights into software architecture and development. His expertise sheds light on building scalable, robust systems, and solving technical challenges...
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