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4 Insights into Modern Cloud Inefficiency

Bill Buckley
CloudZero

For the last 18 years — through pandemic times, boom times, pullbacks, and more — little has been predictable except one thing: Worldwide cloud spending will be higher this year than last year and a lot higher next year. But as companies spend more, are they spending more intelligently? Just how efficient are our modern SaaS systems?

CloudZero's new report, How Cloud Efficient Are Software Companies In 2024?, found that most companies have limited (or nonexistent) cloud cost management (CCM) programs, which prevent them from making a substantial profit.

This is particularly concerning in the context of AI spending, which will only exacerbate cloud inefficiency. AI, which has gripped the SaaS world as firmly as it has the public imagination, is notoriously difficult to manage. Immature CCM programs will buckle under its complexity and fail to maximize the profitability of AI-driven applications.

The good news is that companies can take some simple steps to remediate these issues. Let's look at some of this survey's key findings and how companies can reverse the trend of inefficiency and maximize their cloud profitability.

Most Companies Don't Proactively Manage Their Cloud Costs

One of the survey's most troubling findings is that 61% of companies don't have a formalized CCM program. This is consistent with The State of FinOps 2024, a report by the FinOps Foundation, which showed that 62% of companies are in the least mature stage (the "Crawl" stage) of FinOps. Formalized CCM spans numerous functions, from the most straightforward budgeting and forecasting to the most complex unit economics calculation, but most fundamental to CCM is cost allocation.

Cost allocation means assigning appropriate costs to individual customers, products, features, teams, microservices, etc. Complete cost allocation shows companies precisely what's driving their spending — and, by extension, where they're most (and least) efficient. The report found that just 9% of companies have complete or near-complete cost allocation.

If you don't know what's driving your spending, it's impossible to drive meaningful efficiencies. Upon instituting a formalized CCM program, companies reduce their cloud costs by 30% in the first year. Low allocation and infrequency of formalized CCM programs would suggest that companies are leaving profit on the table — and the next key finding confirms it.

COGS Inefficiency: Companies Are Leaving Profit on the Table

Roughly three-quarters of survey respondents said their cloud expenses account for at least 20% of their cost of goods sold (COGS), and more than a quarter (28%) said cloud costs account for more than half of their COGS. Since COGS is a key factor in gross margin (i.e., profitability) calculations, and companies that institute CCM programs tend to reduce their cloud costs by 30%, companies are leaving a lot of profit on the table.

A company with $100 million in revenue and $25 million in COGS would have a gross profit of 75% — good, in SaaS terms, but not elite. Now, imagine that their cloud costs represent 50% of their COGS — $12.5 million. A 30% reduction would lower their cloud costs to $8.75 million and their overall COGS to $21.25 million. Their gross profit would grow to 78.75% — near-elite.

Organizations Aren't Using the Most Powerful CCM Methods

An absence of strong CCM also means companies tend not to use its most powerful approaches — namely, software code optimization. While about half of companies take advantage of simple CCM methods — enterprise discounts, bulk purchasing discounts — just 28% of companies practice software code optimization. Software code optimization entails ad-hoc code fixes that make the software run more efficiently and at the highest scale levels, saving companies millions of dollars.

Software code optimization requires well-allocated, real-time, highly granular cost data and systems to notify the correct engineers when costs spike. Given that just 31% of companies have formal CCM programs, it's not surprising that roughly the same portion uses software code optimization.

Elite Cloud Efficiency Rate (CER): 92%+

Cloud Efficiency Rate (CER) is a universal benchmark for cloud cost efficiency. It compares your revenue to your cloud spend and shows you how much of every revenue dollar you keep versus how much you send to cloud providers. A company with an 80% CER sends $0.20 of every revenue dollar to its cloud providers; a company with a 90% CER sends $0.10 of every dollar to its cloud providers. The report shows that the top-quartile CER is 92%, meaning the most cloud-efficient SaaS companies send just $0.08 of every revenue dollar to their cloud providers.

CERs also tend to worsen as companies scale and add engineers. Angel/bootstrapped companies reported the highest median CER (92%), with every other category reporting significantly worse median CERs (80% across public, debt/private equity, and venture capital). Companies with 11–25 engineers have the highest median CER (87%), with 51–100 (75%) and 100+ (80%) representing significant CER declines.

Increase Your Profitability with CCM

Organizations that want to grow, maintain a high pace of innovation, and increase their cloud efficiency need to compare their CER to industry benchmarks, at minimum. To drive elite CER, they will need sophisticated CCM programs. This involves engagement from the engineering function, precise budgeting, complete allocation, and clear unit economics.

Technical teams buy cloud resources and manage their costs, so they're positioned to have the most positive impact on cloud efficiency. Providing technical teams with relevant, real-time cloud cost data will empower them to make better infrastructure and code decisions. This will make innovations more durable and result in a healthier bottom line for the business.

Methodology: CloudZero, in partnership with Benchmarkit, a B2B SaaS research firm, conducted the report. More than 700 cloud operations and finance professionals at SaaS companies throughout North America were surveyed on all things cloud spending.

Bill Buckley is SVP of Engineering at CloudZero

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Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...

4 Insights into Modern Cloud Inefficiency

Bill Buckley
CloudZero

For the last 18 years — through pandemic times, boom times, pullbacks, and more — little has been predictable except one thing: Worldwide cloud spending will be higher this year than last year and a lot higher next year. But as companies spend more, are they spending more intelligently? Just how efficient are our modern SaaS systems?

CloudZero's new report, How Cloud Efficient Are Software Companies In 2024?, found that most companies have limited (or nonexistent) cloud cost management (CCM) programs, which prevent them from making a substantial profit.

This is particularly concerning in the context of AI spending, which will only exacerbate cloud inefficiency. AI, which has gripped the SaaS world as firmly as it has the public imagination, is notoriously difficult to manage. Immature CCM programs will buckle under its complexity and fail to maximize the profitability of AI-driven applications.

The good news is that companies can take some simple steps to remediate these issues. Let's look at some of this survey's key findings and how companies can reverse the trend of inefficiency and maximize their cloud profitability.

Most Companies Don't Proactively Manage Their Cloud Costs

One of the survey's most troubling findings is that 61% of companies don't have a formalized CCM program. This is consistent with The State of FinOps 2024, a report by the FinOps Foundation, which showed that 62% of companies are in the least mature stage (the "Crawl" stage) of FinOps. Formalized CCM spans numerous functions, from the most straightforward budgeting and forecasting to the most complex unit economics calculation, but most fundamental to CCM is cost allocation.

Cost allocation means assigning appropriate costs to individual customers, products, features, teams, microservices, etc. Complete cost allocation shows companies precisely what's driving their spending — and, by extension, where they're most (and least) efficient. The report found that just 9% of companies have complete or near-complete cost allocation.

If you don't know what's driving your spending, it's impossible to drive meaningful efficiencies. Upon instituting a formalized CCM program, companies reduce their cloud costs by 30% in the first year. Low allocation and infrequency of formalized CCM programs would suggest that companies are leaving profit on the table — and the next key finding confirms it.

COGS Inefficiency: Companies Are Leaving Profit on the Table

Roughly three-quarters of survey respondents said their cloud expenses account for at least 20% of their cost of goods sold (COGS), and more than a quarter (28%) said cloud costs account for more than half of their COGS. Since COGS is a key factor in gross margin (i.e., profitability) calculations, and companies that institute CCM programs tend to reduce their cloud costs by 30%, companies are leaving a lot of profit on the table.

A company with $100 million in revenue and $25 million in COGS would have a gross profit of 75% — good, in SaaS terms, but not elite. Now, imagine that their cloud costs represent 50% of their COGS — $12.5 million. A 30% reduction would lower their cloud costs to $8.75 million and their overall COGS to $21.25 million. Their gross profit would grow to 78.75% — near-elite.

Organizations Aren't Using the Most Powerful CCM Methods

An absence of strong CCM also means companies tend not to use its most powerful approaches — namely, software code optimization. While about half of companies take advantage of simple CCM methods — enterprise discounts, bulk purchasing discounts — just 28% of companies practice software code optimization. Software code optimization entails ad-hoc code fixes that make the software run more efficiently and at the highest scale levels, saving companies millions of dollars.

Software code optimization requires well-allocated, real-time, highly granular cost data and systems to notify the correct engineers when costs spike. Given that just 31% of companies have formal CCM programs, it's not surprising that roughly the same portion uses software code optimization.

Elite Cloud Efficiency Rate (CER): 92%+

Cloud Efficiency Rate (CER) is a universal benchmark for cloud cost efficiency. It compares your revenue to your cloud spend and shows you how much of every revenue dollar you keep versus how much you send to cloud providers. A company with an 80% CER sends $0.20 of every revenue dollar to its cloud providers; a company with a 90% CER sends $0.10 of every dollar to its cloud providers. The report shows that the top-quartile CER is 92%, meaning the most cloud-efficient SaaS companies send just $0.08 of every revenue dollar to their cloud providers.

CERs also tend to worsen as companies scale and add engineers. Angel/bootstrapped companies reported the highest median CER (92%), with every other category reporting significantly worse median CERs (80% across public, debt/private equity, and venture capital). Companies with 11–25 engineers have the highest median CER (87%), with 51–100 (75%) and 100+ (80%) representing significant CER declines.

Increase Your Profitability with CCM

Organizations that want to grow, maintain a high pace of innovation, and increase their cloud efficiency need to compare their CER to industry benchmarks, at minimum. To drive elite CER, they will need sophisticated CCM programs. This involves engagement from the engineering function, precise budgeting, complete allocation, and clear unit economics.

Technical teams buy cloud resources and manage their costs, so they're positioned to have the most positive impact on cloud efficiency. Providing technical teams with relevant, real-time cloud cost data will empower them to make better infrastructure and code decisions. This will make innovations more durable and result in a healthier bottom line for the business.

Methodology: CloudZero, in partnership with Benchmarkit, a B2B SaaS research firm, conducted the report. More than 700 cloud operations and finance professionals at SaaS companies throughout North America were surveyed on all things cloud spending.

Bill Buckley is SVP of Engineering at CloudZero

Hot Topics

The Latest

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...