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The High Cost of Low Cloud Cost Visibility

Bill Buckley
CloudZero

Cloud spending continues to soar. Globally, cloud users spent a mind-boggling $563.6 billion last year on public cloud services, and there's no sign of a slowdown. In fact, Gartner predicts that spending will soar to $678.8 billion this year.

This skyrocketing spending growth underscores the importance of cloud cost optimization. If done properly, organizations can transform cost data into actionable business insights and coordinates to maximize the ROI of their cloud investments.

CloudZero's State of Cloud Cost Report 2024 found that organizations are still struggling to gain control over their cloud costs and that a lack of visibility is having a significant impact. Among the key findings of the report:

Cloud costs are out of control. Most organizations say they don't have control over their cloud costs. The number of companies reporting that their costs are "way too high" rose in comparison to a similar survey conducted in 2022.

Companies lose productivity due to low visibility. Almost 90% of participants indicated that a lack of cloud cost visibility keeps them from performing their job well. That is an increased level of lost productivity compared to the previous survey.

Cloud cost: Not just for executives. In 2024, the whole leadership hierarchy is interested in cloud costs. It's no longer merely a C-suite issue but has become a company-wide focus of attention.

With engineering ownership comes cost control. The survey data indicates that when the engineering function owns cloud cost management, the result is better business outcomes, such as higher confidence in reporting accuracy. 81% of survey participants noted that when engineering has some level of ownership, their cloud costs are "about where they should be."

Engineering ownership also increases finance-engineering alignment. When engineers take part in cloud cost management, their priorities are essentially indistinguishable from those of the finance team.

The Cost of Low Visibility

It's concerning that less than 50% of organizations said their cloud costs are healthy; in fact, 58% of respondents said their costs are too high. What's more worrisome is the survey data revealing a rise in the number of organizations reporting that their costs are "way too high" — a shift from 11% in 2022 to 14% this year. Though that's not a massive increase, it does reveal an ongoing lack of control with respect to cloud costs.

When asked how effectively survey participants can allocate cloud spend to the various parts of their business, 42% responded that they can only estimate those costs. More surprising still, more than 20% of participants have little to no idea how much those various parts cost. Two-thirds of organizations can't accurately measure unit costs.

Adding insult to injury, two-thirds of organizations noted that looking into rising cloud costs interferes with both finance and engineering workflows. The survey data shows this has a greater effect on companies than in years past.

As for the engineers themselves, 66% noted that their work is disrupted to some degree by a lack of visibility into cloud costs. And 22% of those reported high levels of disruption, double the figure (11%) in 2022.

The Secret Is Engineering Engagement

High-functioning engineering teams want their work to be connected to business and user outcomes. The fact that many of them can't attribute cloud costs to business units reveals a serious problem in cloud software engineering.

Every engineering decision is a buying decision

Cloud cost optimization starts with engineers. Every engineering decision is a buying decision; whenever an engineer spins up a new cloud resource, they incur a new cost. When engineers have thorough visibility into their cloud costs, their purchasing decisions are based on reality, not guesswork — and the survey results validate this idea. Greater visibility yields greater engineering engagement, leading to better business outcomes like cost savings, maximized profits, and increased accountability.

Methodology: This report is based on a survey conducted by CloudZero of 1,000 US engineering and finance workers (50/50 split) in firms with 100 to 9,999 employees and with at least $500,000 annual total cloud spend who use either Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure as their primary cloud service provider. The survey was carried out in January 2024.

Bill Buckley is SVP of Engineering at CloudZero

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

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New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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The High Cost of Low Cloud Cost Visibility

Bill Buckley
CloudZero

Cloud spending continues to soar. Globally, cloud users spent a mind-boggling $563.6 billion last year on public cloud services, and there's no sign of a slowdown. In fact, Gartner predicts that spending will soar to $678.8 billion this year.

This skyrocketing spending growth underscores the importance of cloud cost optimization. If done properly, organizations can transform cost data into actionable business insights and coordinates to maximize the ROI of their cloud investments.

CloudZero's State of Cloud Cost Report 2024 found that organizations are still struggling to gain control over their cloud costs and that a lack of visibility is having a significant impact. Among the key findings of the report:

Cloud costs are out of control. Most organizations say they don't have control over their cloud costs. The number of companies reporting that their costs are "way too high" rose in comparison to a similar survey conducted in 2022.

Companies lose productivity due to low visibility. Almost 90% of participants indicated that a lack of cloud cost visibility keeps them from performing their job well. That is an increased level of lost productivity compared to the previous survey.

Cloud cost: Not just for executives. In 2024, the whole leadership hierarchy is interested in cloud costs. It's no longer merely a C-suite issue but has become a company-wide focus of attention.

With engineering ownership comes cost control. The survey data indicates that when the engineering function owns cloud cost management, the result is better business outcomes, such as higher confidence in reporting accuracy. 81% of survey participants noted that when engineering has some level of ownership, their cloud costs are "about where they should be."

Engineering ownership also increases finance-engineering alignment. When engineers take part in cloud cost management, their priorities are essentially indistinguishable from those of the finance team.

The Cost of Low Visibility

It's concerning that less than 50% of organizations said their cloud costs are healthy; in fact, 58% of respondents said their costs are too high. What's more worrisome is the survey data revealing a rise in the number of organizations reporting that their costs are "way too high" — a shift from 11% in 2022 to 14% this year. Though that's not a massive increase, it does reveal an ongoing lack of control with respect to cloud costs.

When asked how effectively survey participants can allocate cloud spend to the various parts of their business, 42% responded that they can only estimate those costs. More surprising still, more than 20% of participants have little to no idea how much those various parts cost. Two-thirds of organizations can't accurately measure unit costs.

Adding insult to injury, two-thirds of organizations noted that looking into rising cloud costs interferes with both finance and engineering workflows. The survey data shows this has a greater effect on companies than in years past.

As for the engineers themselves, 66% noted that their work is disrupted to some degree by a lack of visibility into cloud costs. And 22% of those reported high levels of disruption, double the figure (11%) in 2022.

The Secret Is Engineering Engagement

High-functioning engineering teams want their work to be connected to business and user outcomes. The fact that many of them can't attribute cloud costs to business units reveals a serious problem in cloud software engineering.

Every engineering decision is a buying decision

Cloud cost optimization starts with engineers. Every engineering decision is a buying decision; whenever an engineer spins up a new cloud resource, they incur a new cost. When engineers have thorough visibility into their cloud costs, their purchasing decisions are based on reality, not guesswork — and the survey results validate this idea. Greater visibility yields greater engineering engagement, leading to better business outcomes like cost savings, maximized profits, and increased accountability.

Methodology: This report is based on a survey conducted by CloudZero of 1,000 US engineering and finance workers (50/50 split) in firms with 100 to 9,999 employees and with at least $500,000 annual total cloud spend who use either Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure as their primary cloud service provider. The survey was carried out in January 2024.

Bill Buckley is SVP of Engineering at CloudZero

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...