Introductions

Cloud computing offers unmatched flexibility and scalability for enterprises. However, even with the best planning and intentions, it often leads to unexpected cost surprises.

Through our experience in cloud cost management, we've identified a clear sequence of operations that organizations can follow to optimize their spending and maximize savings. This post outlines a practical, step-by-step approach to building a more cost-efficient cloud environment.

Before we dive in, it is important to recognize that there are no quick fixes when it comes to long-term cloud cost management. Success comes from consistently applying structured processes and using the right tools—paired with regular reviews and adjustments.

While the FinOps Foundation outlines a three-phase lifecycle model, our approach takes a slightly more prescriptive and operational view—especially when it comes to applying these principles in real-world cloud environments.

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Step 1: Appropriate Sizing

The first step in optimizing cloud costs is to right-size your cloud instances. This means selecting the right instance type and size based on actual usage data—not just assumptions. Many organizations tend to overestimate their resource needs and provision larger instances “just in case,” which often results in unnecessary costs and wasted capacity.

For example, one of our customers was running a high-memory instance for a web server, even though the memory usage was both low and stable. By switching to a smaller, more appropriate instance type, we reduced their costs by 30%—without impacting performance. While this may seem like a simple fix, we’ve found similar savings opportunities in nearly every environment we’ve reviewed.

In this step, it’s also important to consider modernization. Identify instances running on outdated or more expensive families and migrate them to the latest generation. Newer instance types typically offer better cost-to-performance ratios, so updating them before right-sizing helps you get the most value.

In short, appropriate sizing and modernization ensure your workloads get exactly the right amount of compute, memory, and storage—no more, no less—which is the foundation of sustainable cost optimization.

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Step 2: Scheduling and Automatic Scaling

Once your instances are properly sized, the next step is to optimize resource usage through scheduling and automatic scaling. These strategies ensure that cloud resources are available when needed—and minimized when they’re not.

Scheduling allows you to automatically start or stop instances based on usage patterns. For example, you can shut down non-critical workloads during nights or weekends to avoid paying for idle resources. Automatic scaling, on the other hand, dynamically adjusts the number of instances based on real-time demand. This ensures your application remains responsive during peak times while minimizing waste during periods of low activity.

Industries with predictable workloads can benefit greatly from this approach. Take the financial sector, for instance. While user access may continue after hours, most backend processing is tightly aligned with stock market trading hours. In this case, resources can be scaled down or turned off when the market is closed.

However, some environments—particularly those built on older or monolithic architectures—may not be as flexible. In these cases, using scheduled automation, burstable instance types, or containerized workloads can offer similar benefits.

With fixed operating hours and a known calendar of holidays, environments like financial systems present clear opportunities for scheduled cost savings. Simply aligning infrastructure usage with these known patterns can lead to meaningful reductions in spend. By combining proper sizing, scheduling, and automatic scaling, resources are closely aligned with workload requirements.

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Step 3: Commit to Savings Plans and Reserved Instances

After establishing an appropriately sized and expanded environment, businesses can use reservation and savings plans to further reduce costs. This provides discounted rates in exchange for a commitment to consistent use for 1 to 3 years.

Compared to pay-as-you-go or on-demand pricing, the savings can be over 70%. The important thing is not to pay for unused capacity by reserving only what you need after proper sizing. As discussed in another post in this blog post; you need to maintain a process to make the most of these opportunities, and if you have a dynamic environment like most companies, you should use the following platforms: OpsNow mitigates risk and ensures maximum efficiency.

Automated computing commitment is OpsNow's specialty, and we reserve instances after proper sizing and scheduling to reduce enterprise costs by 40% or more while ensuring high utilization and coverage. We do this through tools.

The greatest value is that OpsNow provides improved savings without the end customer having to commit to a typical 1- or 3-year term. By eliminating this risk, action can be taken quickly to ensure maximum savings.

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Step 4: Monitor Usage and Costs

The final step is continuous monitoring of cloud resource usage and costs. Cloud platforms provide detailed metrics that can be analyzed to identify waste and optimization opportunities. Leveraging notifications for more than one based on tag groups or other well-defined processes is an important and often overlooked step. Environments without a structured tagging process and no loose or inconsistent process for terminating unused resources are often considered cloud costs, but managed properly, can save 15% or more.

It's also essential to set usage thresholds and alerts to be notified of unusual activity. For example, a customer found that heavy batch jobs were unnecessarily using the CPU at maximum for several hours. By setting up alerts, we were able to take proactive steps to resolve the issue, and as a result, we were able to save more than 20% of our monthly costs.

Regular monitoring ensures that the environment remains the right size and scale and expands over time while also securing additional savings opportunities. Don't confuse performance management and customer experience with the financial aspects of cost optimization. Although they often use the same tools, their goals are different.

When to Consider Spot Instances

After an appropriate sizing, automatic scaling, and reservation process, businesses can further optimize costs by utilizing Spot Instances. This provides unused computing capacity at a discount of up to 70% compared to On-Demand.

The trade-off is that the cloud provider can reclaim Spot instances if capacity is needed. As a result, Spot instances are ideal for fault-tolerant workloads such as batch processing jobs, development and test environments, big data analytics, and any application with flexible startup and shutdown times. If you're using a Kubernetes environment, you probably already have an extensive Spot implementation, so it's a natural fit, but if you have too many failed requests or a state storage environment, balancing on-demand might make sense. ‍

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Methods for Optimizing Code

In addition to resource allocation and purchasing choices, another way to improve cloud efficiency is code optimization. Well-written code reduces demand on infrastructure while enabling instances to take full advantage of functionality. Although not within the scope of this post, this can have a significant impact on performance and compute utilization, so it should be the first part of an optimization task sequence.
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Common code optimizations include:

• Caching frequently accessed data
• Use more efficient algorithms and data structures
• Parallelizing computations between threads/processes
• Optimizing and tuning database queries
• Compress larger data sets
• Prevent inefficient resource usage patterns

Even small code improvements can lead to huge cost savings on a large scale. Reducing overall resource requirements by as little as 10% provides significant instance reduction opportunities. For example, a company reduced CPU utilization for each web request from 800 ms to 200 ms through code optimization. This enabled the server to handle 5 times more traffic without modifying the underlying VM.

Also, most of the cloud runs on NGINX. If your environment has NGINX or a similar load balancer, adjusting these tools can provide dramatic improvements that are an overlooked bottleneck between services and customers.

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Summary

To manage cloud costs, you must follow a best practice sequence of tasks. We first adjust the instance size, then enable scheduling and automatic scaling, then reserve capacity, and finally implement processes to monitor costs and identify anomalies. Effective implementation and periodic review can significantly reduce the hassle of unexpected cloud spending. Using the following tools, OpsNow addresses some of the issues by highlighting savings opportunities and providing reliable analysis. We think this is an important part. But just like anything else, you must play an active role in operations.