The Cloud Was Supposed to Be the Efficient Answer. %%So Why Are Companies Still Burning Money on It?%%

The Cloud Is Everywhere Today

In every product, in every startup pitch. “We run in the cloud” has become synonymous with being modern, scalable and technologically mature. And, frankly, with good reason.

The cloud gave us something we didn’t have before. The ability to launch a global product in days, not months. The ability to scale infrastructure without owning a single server. The ability to experiment, iterate, fail and try again.

Even a decade ago, every manager without a shred of hands-on experience knew about the cloud that you only pay for what you use. It sounded beautiful.

But somewhere between that ideal and reality, something broke. Something fundamental.

The Quiet Problem That Isn’t Talked About Loudly Enough

Today, it’s no longer about whether the cloud works. It’s about whether companies can actually use it efficiently.

And here comes the hard reality. According to the Flexera 2026 State of the Cloud Report [a survey of 753 cloud decision-makers], managing cloud costs has been the number one challenge for the fourth year in a row - 85% of respondents flag it as their top issue. It has even overtaken security, which held the top spot for a decade.

Meanwhile, cloud budgets are growing at roughly 28% per year. 84% of organizations, per Flexera, admit they struggle to effectively manage their cloud spend. According to Crayon, 94% of IT decision-makers are actively struggling with cloud spending. And nearly half of companies report that they’re simply losing control over it.

Let’s look at the survey numbers:

• 29% of cloud spend is “wasted” - after five years of a declining trend, it ticked back up this year, thanks to AI and new PaaS services.
• StormForge found in its survey that organizations waste an average of 47% of cloud resources on over-provisioned infrastructure. In other words, they have more infrastructure than they need.
• According to Datadog, more than 80% of container spend goes to idle resources.
• CloudBolt adds that 98% of companies agree that Kubernetes is a major driver of cloud spend - but 91% can’t effectively optimize their clusters.

Not because people are incompetent. Not because the cloud doesn’t work. But because the cloud today is a brutally complex system that you can’t handle “just like that.” AWS alone has 2.3 million SKUs per Duckbill, all metered hourly. Add Azure, GCP, Kubernetes, Snowflake, Databricks and AI models billing by the token on top, and you get an invoice whose expected total nobody in the organization can reliably predict, not even with a crystal ball.

How We Even Got Here

Most companies moved to the cloud for very good reasons. Delivery speed. Scaling. Flexibility. High availability.

But that move often looked like this: lift & shift of existing systems [meaning a 1:1 move to the cloud with no optimization], quick decisions under pressure, compromises for the sake of time-to-market. And none of those things and decisions went away. They stayed in the architecture. They stayed in the data. They stayed in the way applications communicate, scale, and store information.

And that’s exactly where the problem starts. Not in the invoice. Not in the AWS console. Not in the FinOps dashboard. But deep in how the system is designed.

FinOps Is Not a Silver Bullet

In recent years, an answer with a name has emerged: FinOps. Dashboards. Alerts. Cost tracking. Budgets. And yes, FinOps matters. Flexera confirms that 63% of organizations already have a FinOps team and adoption is growing fast. But it’s becoming increasingly clear that FinOps often treats the symptoms, not the causes.

When you have a poorly designed system, you can optimize instances, buy reserved capacity, set up alerts, but you’ll never reach an optimal state.

Duckbill takes it in this article even further and argues that the very mantra “the cloud is expensive, we have to bring its price down” is framed wrong. Business leaders don’t actually care whether the bill is $100K or $10M. They want to be able to predict the bill, explain it and influence it. The problem isn’t the size of the number - the problem is unpredictability and a missing line of sight.

And you don’t solve that unpredictability with a dashboard telling you to shut down three idle instances.

In his article There Are No Magic Tricks in Cloud Cost Optimization, our CEO Adam Hamšík puts it even more bluntly: Reserved Instances, Savings Plans and Committed Use Discounts aren’t optimizations - they’re financial commitments. They reward predictable, well-designed workloads, which most customers simply don’t have. Locking yourself into a long-term commitment with a cloud provider without understanding your actual usage means waste on autopilot.

A third of the professional, and not exactly cheap, FinOps tools on the market sell you savings by comparing your current spend against the full on-demand price that nobody actually pays. The number in a tool like that looks great. In reality, you’ve just paid someone a commission to lock you into a pricing plan you could have bought directly. 

The Cloud Today Isn’t Infra. It’s a Complex Ecosystem

Today’s cloud isn’t just compute and storage. It’s typically a multi-cloud environment, AI workloads, distributed systems, event-driven architectures, dozens of managed services. And on top of all that, every decision has a financial impact, every architectural pattern has a trade-off, every shortcut eventually comes back as a problem.

AI doesn’t make this any easier. 82% of leaders, per Tech Monitor, admit that AI initiatives are increasing cloud complexity. Only 63% of companies are even tracking AI spend today - a year ago it was 31%. Governance is lagging behind adoption, and the longer we keep going like this, the harder it will be to fix.

You Can Do It In-House. But at What Cost?

It depends on scale, complexity, and where you want to invest your money. So yes - you can build it all yourself. Stand up a FinOps team. Set up governance. Learn the best practices. Make your own mistakes.

But it will cost you years. You’ll make mistakes someone has already made before you. And you’ll pay for them with real money. The difference between “we have a team” and “the team actually works” is several years of work.

That’s why more and more companies today are making the rational call: instead of trying to be experts at everything, they pick partners who have already been through it. Not because they couldn’t do it themselves. But because they don’t want to waste time.

The fact is, most cloud problems have already been solved. Just not at your company.

The Concrete Advantages a Partner Brings

When we talk about partnership with CTOs, DevOps, and tech leaders, a pragmatic question usually comes up: “What specifically do we gain over handling everything directly in AWS ourselves?”

First, co-funding programs and commercial benefits. AWS has a whole range of programs: Activate for startups [up to hundreds of thousands of dollars in credits], the Migration Acceleration Program [MAP] for companies migrating from on-prem or from another cloud, Proof of Concept funding for pilot projects. A direct customer has a hard time getting access to these programs. A partner with proven results and references can activate, structure, and maximize them. We do this on a weekly basis.

Second, private pricing and contract negotiation. Enterprise Discount Programs, private discounts, custom rate cards - all of these exist, and a partner opens those doors that an individual customer often doesn’t even see.

Third, battle-tested know-how. Our internal playbooks hold years of work and dozens of implementations we’ve learned from. That’s know-how you won’t find in the documentation, and it saves you months - on larger projects, even years.

How to Pick the Right One

“We’re an AWS partner” is something almost everyone says today. But the difference between partners is huge. If you want real value, you need someone who understands not just the tools but the decisions behind them. Someone who optimizes the system, not the invoice. Someone who not only tells you what to do, but can also deliver. And someone with enough projects under their belt to know what works and what doesn’t.

In our detailed guide we’ve laid out 11 specific criteria. 

And Here’s the Moment Where Everything Can Change

At Labyrinth Labs we do one thing: we help companies get the most out of the cloud. Not in theory. Not through presentations. But for real - in the architecture, in the systems, in production.

We are 2× AWS Consulting Partner of the Year for CEE [2024 and 2025]. The only firm in the region to do it back-to-back. AWS Partner Network officially announced this on its regional blog.

What does that mean in practice? Every year, AWS independently evaluates hundreds of partners in CEE against hard criteria - number of successfully delivered projects, customer satisfaction, depth of technical expertise, contribution to innovation, certified competencies, investment in educating the community. Winning that title once is hard. Winning it two years in a row is a statistical anomaly.

For us, it means two things. Validation from AWS - not PowerPoint, but real projects for 365.bank, Raiffeisenbank, Pixel Federation, Eramba, Vestberry, Quality Unit, and others. And a commitment to the community: AWS Community Days, AWS Summits, meetups, open-source contributions. That’s not marketing, that’s our DNA.

‍

Cloud Cost Optimization? Yes. But Not in the Way You Expect.

Companies today “optimize the cloud” in all kinds of ways. They shut down instances. Hunt for discounts. Set up alerts. 

Some even save money in one click - try it for yourself at stopburning.money.

We approach it differently. We start with the question: why does that system cost what it costs?

And very often we find that workloads aren’t designed efficiently, data is processed needlessly, infrastructure scales the wrong way. And that’s exactly where the biggest room for improvement lies.

Concrete example - when we helped Quality Unit migrate their SaaS product LiveAgent to AWS, we managed to cut tenant onboarding time by 70% and the deployment cycle by 85% (from weeks to days). For Pixel Federation, by migrating their legacy Hadoop/Spark setup to EKS we achieved a 60% performance gain alongside a reduction in operational overhead.

Cost savings aren’t the goal. They’re a by-product of doing things well.

‍

LARA: When the Data Finally Makes Sense

So we can do this at scale, we built our own platform: LARA. Not as a “magic button.” But as an efficient, well-optimized platform that fully embraces a cloud-native approach.

Because without data, you’re just guessing. And in the cloud, guessing is expensive.

LARA is built on Kubernetes, AWS best practices, and our own and proven open-source components. It gives customers networking, storage, security, monitoring, and observability as modular building blocks. The entire infrastructure is defined as Infrastructure as Code - with the full codebase for the customer, no vendor lock-in. CI/CD via GitHub and Argo CD. Centralized governance across accounts. Built-in mechanisms for rightsizing, autoscaling, and workload optimization from day one.

Years of work you’d otherwise do yourself, ready to deploy in a matter of days.

But Honestly?

Maybe you’re a developer. Maybe an architect. Maybe a CTO.

And maybe you’ve already had that moment when the cloud stopped making sense. Or when the system started getting more complicated than it was growing. Or when, in the middle of a late-night deployment, you felt that “this can be done better.”

The best moment is the one when you say to yourself: “OK, this is what I want to tackle now.” If you saw yourself in this text, if some of these things sound familiar, if you feel like the cloud at your company has more potential than you’re tapping into, get in touch with us.

The sooner you start making the right decisions, the less money you’ll burn. The cloud isn’t the problem. You just need to know what you’re doing in it and how.