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3 Ways to Minimize Cloud Costs

With a little creativity, you can battle soaring cloud costs and embrace a more customized cloud approach
Greg Hohenbrink
Wursta

For well over a year now, small businesses and enterprises alike have been scrambling to unlock cost efficiencies in response to a persistent economic downturn. Shoring up revenue wherever possible has become mission critical, and even as business leaders eye new technology solutions to improve their workflows, keeping purse strings tightened remains top of mind.

If your company is considering migrating to the cloud and/or looking to make better use of your current cloud investments, look no further! Let's explore three ways you can minimize cloud spend while maximizing the value derived from your tech stack.

1. Start with Strategy

Creating a more efficient cloud spend requires a proactive approach. It's imperative to start at the very beginning, i.e. taking stock of every technology investment your company makes and evaluating its purpose. Don't skip the pre-work here; getting a holistic strategy in place is absolutely essential, especially in an environment where every penny counts.

Start by ensuring you truly understand the objective of every app within your tech stack and how often it's actually used. Is this a superfluous tool that employees are reluctant to adopt? Or is it a core part of their daily workflows? Once you've determined the value the tool provides your business, you can dive deeper into your evaluation by asking the following questions:

■ Do we have the proper processes in place for maximum efficiency?

■ Are we getting the most out of this application?

■ Could we execute in a more efficient way by building a custom application or investing in application integration?

You may be surprised at how many opportunities for consolidated tools you'll uncover — there are a number of multifunctional tech solutions on the market that offer more comprehensive capabilities, which means you may be able to say goodbye to a vendor or two without sacrificing any value.

If you're struggling to implement a technology strategy on your own, there are plenty of resources online you can turn to. You may also find it helpful to work with a consultant who can lead you through the process, especially if you're a smaller shop already juggling a number of priorities.

2. Customize Your Cloud Environment

Users new to the cloud may struggle to identify the true use cases for cloud technology at first. It's crucial to understand that one solution likely won't solve for all of your needs — so thoughtful and methodical customization will go a long way.

The cloud's adaptability and flexibility are two of its biggest advantages. You may consider embracing strategies like "just-in-time" services: an approach to reducing waste by ensuring you're investing in just what you need, when you need it, and nothing more. Starting small and scaling as needed is possible, so long as you're willing to evaluate alternative options to your legacy systems.

Reducing redundant applications and resources, offloading to different storage buckets, and leveraging on-demand tools and APIs are all practical strategies for increasing value and reducing waste when it comes to cloud spend.

3. Consider Adopting a Hybrid Approach

When it comes to determining whether your data belongs in the cloud or on-premises, a hybrid approach can be incredibly beneficial. Instead of trying to cut corners on costs in the short term, think about what makes the most sense for your business given your industry and the type of data in question.

For example, the heavily regulated financial and healthcare industries face more compliance around their use and storage of data, so it's wise (and in some cases mandatory) to store their most sensitive information on-premises. That said, it's easy to fall down the slippery slope of over-investing in servers and other equipment needed for on-site data storage. It's crucial to carefully evaluate what needs to be on-premises versus what can realistically be stored in the cloud.

A hybrid approach is useful for less regulated industries as well. It's not practical for businesses that work with large amounts of data every day to pull information into the cloud, process it, then bring it back down — keeping high-touch data stored on-premises may lead to more efficient processes.

Business leaders should keep in mind that while it may seem cheaper in the short term to purchase ten servers for on-premises data storage, the cost of staffing that operation is much more expensive and may be unsustainable in the long run. The same is true with equipment upgrades, repairs, and the other hidden costs that come with on-premises data centers.

The ROI for migrating even some of your data to the cloud won't be achieved right away, but with a little bit of patience, you'll begin to see the cost savings 5-10 years down the line.

Conclusion

No matter your relationship with the cloud, there are a multitude of opportunities to leverage this technology to your advantage without damaging your budget. Cost efficiency and streamlined processes go hand in hand. A creative and strategic approach won't just save your business money in the long run; it will also ensure you're getting the most out of the tools you actually need.

Greg Hohenbrink is Cloud Services Director at Wursta

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

3 Ways to Minimize Cloud Costs

With a little creativity, you can battle soaring cloud costs and embrace a more customized cloud approach
Greg Hohenbrink
Wursta

For well over a year now, small businesses and enterprises alike have been scrambling to unlock cost efficiencies in response to a persistent economic downturn. Shoring up revenue wherever possible has become mission critical, and even as business leaders eye new technology solutions to improve their workflows, keeping purse strings tightened remains top of mind.

If your company is considering migrating to the cloud and/or looking to make better use of your current cloud investments, look no further! Let's explore three ways you can minimize cloud spend while maximizing the value derived from your tech stack.

1. Start with Strategy

Creating a more efficient cloud spend requires a proactive approach. It's imperative to start at the very beginning, i.e. taking stock of every technology investment your company makes and evaluating its purpose. Don't skip the pre-work here; getting a holistic strategy in place is absolutely essential, especially in an environment where every penny counts.

Start by ensuring you truly understand the objective of every app within your tech stack and how often it's actually used. Is this a superfluous tool that employees are reluctant to adopt? Or is it a core part of their daily workflows? Once you've determined the value the tool provides your business, you can dive deeper into your evaluation by asking the following questions:

■ Do we have the proper processes in place for maximum efficiency?

■ Are we getting the most out of this application?

■ Could we execute in a more efficient way by building a custom application or investing in application integration?

You may be surprised at how many opportunities for consolidated tools you'll uncover — there are a number of multifunctional tech solutions on the market that offer more comprehensive capabilities, which means you may be able to say goodbye to a vendor or two without sacrificing any value.

If you're struggling to implement a technology strategy on your own, there are plenty of resources online you can turn to. You may also find it helpful to work with a consultant who can lead you through the process, especially if you're a smaller shop already juggling a number of priorities.

2. Customize Your Cloud Environment

Users new to the cloud may struggle to identify the true use cases for cloud technology at first. It's crucial to understand that one solution likely won't solve for all of your needs — so thoughtful and methodical customization will go a long way.

The cloud's adaptability and flexibility are two of its biggest advantages. You may consider embracing strategies like "just-in-time" services: an approach to reducing waste by ensuring you're investing in just what you need, when you need it, and nothing more. Starting small and scaling as needed is possible, so long as you're willing to evaluate alternative options to your legacy systems.

Reducing redundant applications and resources, offloading to different storage buckets, and leveraging on-demand tools and APIs are all practical strategies for increasing value and reducing waste when it comes to cloud spend.

3. Consider Adopting a Hybrid Approach

When it comes to determining whether your data belongs in the cloud or on-premises, a hybrid approach can be incredibly beneficial. Instead of trying to cut corners on costs in the short term, think about what makes the most sense for your business given your industry and the type of data in question.

For example, the heavily regulated financial and healthcare industries face more compliance around their use and storage of data, so it's wise (and in some cases mandatory) to store their most sensitive information on-premises. That said, it's easy to fall down the slippery slope of over-investing in servers and other equipment needed for on-site data storage. It's crucial to carefully evaluate what needs to be on-premises versus what can realistically be stored in the cloud.

A hybrid approach is useful for less regulated industries as well. It's not practical for businesses that work with large amounts of data every day to pull information into the cloud, process it, then bring it back down — keeping high-touch data stored on-premises may lead to more efficient processes.

Business leaders should keep in mind that while it may seem cheaper in the short term to purchase ten servers for on-premises data storage, the cost of staffing that operation is much more expensive and may be unsustainable in the long run. The same is true with equipment upgrades, repairs, and the other hidden costs that come with on-premises data centers.

The ROI for migrating even some of your data to the cloud won't be achieved right away, but with a little bit of patience, you'll begin to see the cost savings 5-10 years down the line.

Conclusion

No matter your relationship with the cloud, there are a multitude of opportunities to leverage this technology to your advantage without damaging your budget. Cost efficiency and streamlined processes go hand in hand. A creative and strategic approach won't just save your business money in the long run; it will also ensure you're getting the most out of the tools you actually need.

Greg Hohenbrink is Cloud Services Director at Wursta

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...