As FinOps professionals, we often focus on saving money, cutting cloud costs, and optimizing resource utilization. However, while these goals are critical for the business, they don’t always resonate with engineering teams. Engineers are not driven by cost-saving goals. Instead, they focus on building better, faster, and more efficient systems. If we want to engage with engineering teams effectively, we need to start speaking their language: efficiency.

Why Efficiency Matters to Engineers

Engineers spend countless hours optimizing their code and algorithms. They strive to write efficient code that reduces complexity — choosing O(n) over O(n²) whenever possible. But here’s the reality: no matter how optimized your code is, if your app runs on a wasteful infrastructure, all that effort is undermined. The conversation about engineering efficiency doesn’t end with the code. It must extend to the infrastructure it runs on.

For example, an application running on an oversized or underutilized EC2 instance may not just be a cost issue — it’s an engineering inefficiency. You’re using resources that are going to waste, which means you’re not fully optimizing the infrastructure your code depends on.

In fact, across the industry, average CPU utilization hovers around just 6%. That’s staggeringly inefficient! No engineer would be satisfied with that level of inefficiency in their code, so why accept it in infrastructure? By focusing the conversation on infrastructure efficiency, FinOps teams can connect with what engineers truly care about: smart resource utilization and technical excellence.

Efficiency Goes Beyond Code — Real-World Examples

Let’s talk about a few real-world examples that illustrate how engineering efficiency in infrastructure is directly related to cost optimization, but in a way that resonates with engineers:

EC2 Utilization: A Real Efficiency Example

Let’s break down one of the most common examples of inefficiency in cloud infrastructure: EC2 CPU utilization.

If your EC2 instance shows a CPU utilization of only 10%, you’re operating at just a fraction of its capacity. Even if you account for spikes and buffer by adding an extra 5–10% capacity (say, up to 20% for handling unexpected loads), you’re still left with 80% of unused capacity — a massive waste of both resources and cost.

In this case, right-sizing is key. By reducing the instance size to better match actual usage patterns (with a small buffer for spikes), you can dramatically cut down on waste without compromising performance. This isn’t just a cost-saving measure — it’s an efficiency optimization that aligns with engineers’ desire to run systems that are lean and fully utilized.

When engineers see that resizing an instance leads to more efficient infrastructure and fewer idle resources, they can get behind FinOps initiatives that support better technical performance and scaling.

S3 Storage Plan: Why Standard Shouldn’t Be Your Default for S3 Buckets That You Rarely Access

  • The Problem: Many teams upload files to S3 and never access them again. Statistics show that after 30 days, the likelihood of accessing an “old” file drops significantly. Despite this, many organizations continue to store these files in the S3 Standard storage class, which is optimized for frequent access and comes with a higher cost. This approach leads to waste, as you’re paying for a premium service while the files just sit there unused.
  • The Efficiency Solution: Instead of keeping these files in S3 Standard, you can automatically transition them to more cost-effective storage classes like S3 Glacier or S3 Intelligent-Tiering. These classes are designed for infrequently accessed data and offer much lower costs. This ensures that your infrastructure remains efficient by only using higher-cost storage for the files that truly need it.
  • The FinOps Impact: Moving unused files to cheaper storage options not only cuts costs but also aligns with data management efficiency. It ensures that you’re only paying for the level of service that matches the actual usage patterns of your data. Engineers will appreciate this focus on resource management, as it promotes smart infrastructure choices and prevents unnecessary waste.

RDS: Does Your RDS Really Need to Be Multi-AZ? Paying Double and for Data Transfer Between Availability Zones

  • The Problem: Many development environments run RDS instances with Multi-AZ configurations, designed for high availability and failover support. However, in non-production environments like dev or testing, do you really need this level of redundancy? Not only are you paying for an additional replica in another availability zone, but you’re also incurring data transfer costs between these zones. Additionally, do you need those extra replicas just to handle a few zero-connection moments?
  • The Efficiency Solution: For development or testing environments, consider scaling back to Single-AZ instances. Unless you’re running production-level workloads where failover is critical, you can save significantly by simplifying your architecture. Reducing unnecessary replicas or failover setups in development environments prevents waste and still allows you to meet your reliability needs without overpaying.
  • The FinOps Impact: Simplifying RDS configurations by avoiding Multi-AZ in non-production environments or eliminating unneeded replicas can cut your database costs in half while reducing data transfer expenses. This promotes infrastructure efficiency by aligning your architecture with actual needs. Engineers will appreciate the focus on right-sizing infrastructure and eliminating over-engineering where it’s not necessary, allowing them to focus resources on environments that truly need them.
FinOps Should Talk Engineering — Stop Talking Savings, Talk Efficiency!
Efficiency ScoreBoard

Tailored Automation to Maintain Efficiency Over Time

A lot of the time, business or application constraints come into play when analyzing your cloud usage. You need to consider these constraints to ensure that you’re optimizing in a way that doesn’t impact critical systems or workflows. This is why tailored automation is so critical for maintaining efficiency in the long term.

Even when you optimize infrastructure for efficiency, cloud environments are dynamic. Workloads shift, usage patterns change, and spikes in demand can happen unpredictably. This is where tailored automation becomes a game-changer.

By implementing customized automation workflows, you can continuously monitor resource utilization and ensure that efficiency is maintained over time. Automation helps you right-size instances, move files to the appropriate S3 storage class, and adjust database configurations based on changing usage patterns — all without requiring manual intervention.

With Wiv.ai’s workflow automation platform, this process becomes even more streamlined. Wiv.ai helps you build workflows that are specifically designed to monitor and optimize your cloud environment, ensuring that resources are always aligned with current usage needs. Wiv.ai’s automation doesn’t just stop at identifying inefficiencies — it actively ensures that your environment remains optimized, even as conditions change.

This continuous approach prevents inefficiencies from creeping back into your system over time. Engineers can trust that Wiv.ai’s tailored automation will help keep their infrastructure lean and efficient without constantly needing their attention.

When you talk about efficiency through automation, you’re speaking the engineer’s language: minimizing waste and ensuring the infrastructure runs smart — just like they strive to do with their code. With Wiv.ai, you not only achieve cloud efficiency but also see realized savings through automation that is custom-built for your unique needs.

Speak the Language Engineers Care About

The key takeaway here is simple: Efficiency equals engineering success. Engineers care about building systems that run smoothly, use resources wisely, and are scalable and performant. By framing FinOps initiatives around infrastructure efficiency, you align your goals with theirs.

Instead of telling an engineer that they’re wasting money, tell them that they’re wasting resources. Instead of talking about cloud cost optimization, talk about infrastructure optimization. Engineers value systems that are efficient and effective, and when they see that FinOps can help them achieve that, you’ll get their buy-in.

Remember the old saying: “When in Rome, do as the Romans do.” When engaging with engineers, speak their language — the language of efficiency. Show them how optimizing infrastructure is just as important as optimizing code. Once they understand this, the cost savings will follow naturally.

Conclusion: Align FinOps with Engineering Efficiency

FinOps isn’t just about cutting costs; it’s about optimizing resources. Engineers spend their time refining and optimizing code — why shouldn’t they do the same with infrastructure? By talking to them in terms of efficiency, FinOps can forge a stronger, more collaborative relationship with engineering teams. And when that happens, both sides win.

With the right tools, tailored automation, and a focus on efficiency, FinOps can help engineers build better, faster, and more scalable infrastructure. The result? Optimized cloud environments that run lean, reduce waste, and keep costs under control — without sacrificing technical excellence.