With cloud adoption rapidly increasing, the importance of cloud cost management is now front and center for organizations. But, despite best efforts, an estimate of up to 30% of cloud spending goes to waste. Even in the State of FinOps 2024 report, “reducing waste” emerged as the highest key priority for FinOps practitioners.
While there are numerous FinOps strategies to focus on, two of the most prominent strategies for optimizing cloud costs are usage optimization and rate optimization. While these approaches are fundamentally different in execution, they both aim to achieve the same result: maximizing the return on cloud investment (ROI).
This blog explains the differences between usage and rate optimization, explores their impact on cloud cost management, and highlights why focusing on both is essential for sustainable cloud efficiency. Read on!
What Is Cloud Rate Optimization?
Cloud rate optimization is the practice of reducing the per-unit cost of running workloads by leveraging and managing available discounts, pricing models, and agreements. It’s part of cloud cost optimization, allowing organizations to increase ROI and reduce operating expenses. It focuses specifically on negotiating better rates, purchasing reserved capacity, using discounts and commitments, and finding other ways to minimize the hourly or monthly fees associated with cloud resource usage.
Instead of optimizing for resource efficiency like usage optimization, cloud rate optimization is a financial exercise to cut the cost of cloud services. Teams work to understand spending patterns, identify savings opportunities, implement pricing improvements, and track savings over time.
The goal is to pay as little as possible for each unit of cloud capacity consumed while maintaining business needs and service levels at par. As cloud usage grows exponentially, rate optimization is crucial for cost-conscious enterprises.
Best Practices for Cloud Rate Optimization
To achieve successful cloud rate optimization, FinOps teams should keep the following best practices in mind:
Leverage long-term discounting
Cloud providers offer various pricing models. For example, On-Demand or pay-as-you-go models mean you only pay for what you actually provision, whereas discounting options like Reserved Instances or committed use discounts allow you to secure huge discounts in exchange for committing to a defined usage over 1 or 3 years.
For example, AWS RIs can help you save up to 72% compared to On-Demand pricing and provide a capacity reservation when used in a specific Availability Zone.
Each cloud pricing model has advantages and disadvantages. Selecting the right models for your business is a part of cloud rate optimization. With the right model per workload, you can reduce hourly/monthly fees and cut cloud costs without affecting performance.
Negotiate volume discounts
Enterprise users with extensive cloud usage can often negotiate custom enterprise agreements for better pricing structures that align with their consumption patterns. They can also negotiate for terms that offer protection from price increases and other changes.
As part of rate optimization, it’s always better to understand your current standing, have an overview of future forecasts and reach out to the concerned CSP to see if there’s a scope of negotiation. SMB customers can negotiate to optimize cloud costs by working with third parties to gain leverage and secure better pricing and improved public cloud rates.
Term length and prepayment options
Term and prepayment options can significantly impact overall cloud costs. Normally, by extending your term length and paying more of the commitment upfront, you can secure increased discounts.
For example, committing to a three-year term versus a one-year term can increase discounts by 20–30%, while choosing to prepay some or all of the commitment upfront can increase discounts by 5–10%.
Monitor regularly
While cloud usage may be flexible, your commitment plans are not. Commitment management isn’t a one-time task. You have to constantly measure the results and make adjustments to ensure the discount plans match your actual usage and deliver maximum cloud cost savings.
This ensures you’re not holding onto plans that are no longer optimal or missing out on new pricing options or reservations that better suit your needs or offer higher potential savings. Thus, you need to keep a close eye on your utilization, coverage, and Effective Savings Rate metrics. With these insights, you can optimize your plans and forecast better so you don’t needlessly overcommit or underutilize resources.
Leverage automation
Cloud rate optimization can be a difficult beast to tackle due to its dynamic changes, massive billing data, complex and evolving pricing models, and the significant expertise required to constantly align changing usage with various commitment plans. With different pricing models, term lengths, prepayment options, and the need for regular monitoring, optimizing rates can seem overwhelming.
Additionally, unlike usage optimization, which focuses on resource efficiency and requires engineering time and expertise to implement, rate optimization can be handled independently. It’s not an efficient use of valuable engineering hours for a task that can be fully automated.
Fully autonomous tools like ProsperOps can help manage and optimize your cloud discount instruments to ensure maximum savings and minimum commitment risk. Beyond automating rate optimization, ProsperOps is also aware of special pricing agreements and incorporates strategic decision-making that adapts to each customer’s unique circumstances and unit economics.
This tailored approach ensures that not only are you benefiting from automation, but also from a personalized strategy that maximizes value and aligns with your specific financial goals.
What Is Cloud Usage Optimization?
Cloud usage optimization is the process of analyzing and adjusting cloud resource usage to ensure that organizations are getting the most value for their spending. The goal is to closely match provisioned resources to actual usage, reducing overprovisioning and cloud waste. This saves money and enhances the performance, reliability, and sustainability of cloud environments. Effective usage optimization includes activities like right-sizing workloads, eliminating idle resources, scaling dynamically with demand, and load balancing efficiently.
While rate optimization lowers cloud costs, usage optimization makes every dollar work harder. The two approaches work together to minimize expenses and maximize returns on cloud investments.
Best Practices of Cloud Usage Optimization
Follow these strategies to maximize cloud usage optimization:
Right-size resources
Instance Rightsizing is the process of analyzing and adjusting the size and type of cloud instances to better fit the specific needs of your workloads. By rightsizing instances, organizations can ensure that they are not paying for more resources than necessary while maintaining optimal application performance.
Because both over- and under-provisioning can lead to waste, it’s best to use historical or estimated usage metrics to drive optimal compute, storage, and memory capacity provisioning and mitigate waste.
Identify idle resources
Identifying and acting upon the idle/unused resources can help you save a lot in the cloud. A few major examples of usage waste include idle instances, outdated storage, orphaned resources, and over-provisioning. To optimize cloud usage and reduce unnecessary costs, teams must prioritize eliminating these idle resources, like EC2 instances, RDS databases, and S3 buckets that are rarely (or even never) used, etc.
You can leverage third-party usage optimization platforms that help you with automated recommendations with these saving opportunities to accelerate your usage optimization.
Auto-scale services
By configuring services and infrastructure to scale out and in automatically as usage and traffic fluctuate, you can better align cloud capacity with demand, thereby reducing waste and optimizing costs. This is possible with auto-scaling services that adjust resource allocation automatically based on demand, scaling up resources when demand increases and scaling down when it decreases to optimize cloud usage.
Implement efficient load balancing
Load balancing is the process of managing and distributing network traffic across multiple servers to optimize performance, increase availability, and prevent any single server from becoming a bottleneck.
This ensures that applications can handle high traffic volumes without performance degradation or downtime, leading to a more resilient and scalable infrastructure. And because the probability of failure is reduced, it helps you save money on repairs and backups frequently.
Perform continuous monitoring and optimization
Cloud visibility and monitoring are the foundation of every process in FinOps. For effective usage optimization, teams must continuously track detailed usage data and cloud bills. This regular monitoring enables them to identify savings opportunities, adjust configurations, and right-size workloads to maintain cost-effective and efficient cloud usage over time.
Use automation
Without automation, teams will have to spend most of their engineering time and efforts to identify and implement these saving opportunities — which will slow down innovation and growth. So it’s necessary to seek automation especially with monitoring and automated recommendations.
Automated usage optimization employs machine learning to analyze historical usage and identify underutilized, rarely used, or unused resources. These insights enable organizations to take action on areas to reduce cloud spend without impacting performance.
For a more detailed analysis of different FinOps automation capabilities, explore our blog on FinOps automation.
Key Differences Between Rate and Usage Optimization
FinOps teams need to work out a comprehensive strategy that combines both rate and usage optimization to create an immediate yet sustainable framework for reducing cloud costs.
Let’s examine some of the biggest differences between the two cost optimization techniques to illustrate why businesses need to consider both.
Objective
The goal of rate optimization is to minimize the per-unit cost of cloud services. It aims to pay less per hour or GB. Usage optimization instead focuses on maximizing the efficiency and value of cloud resources. It reduces waste through better utilization.
Focus of optimization
Rate optimization centers on negotiating better pricing and discounts to reduce the hourly or monthly fees for cloud infrastructure and services. Whereas, usage optimization targets architectural efficiency, workload sizing, and automation to minimize wasted resources and over-provisioning.
Strategies employed
To realize minimized costs, rate optimization leverages Reserved Instances, Savings Plans, committed use discounts, sustained use discounts, custom contracts, volume discounts, and spot pricing. Altogether, this contributes to less money spent per unit.
Meanwhile, to maximize efficiency, usage optimization focuses on right-sizing workloads, eliminating unused resources, implementing auto-scaling, and practicing efficient load balancing.
Impact on cloud architecture
Rate optimization is largely financial, with minimal architectural impact. Usage optimization often requires reconfiguring deployments for efficiency, like auto-scaling groups and optimized database instances.
Measurement of success
Rate optimization focuses on cost savings per GB, vCPU hour, or other industry metrics like utilization rate, coverage rate, and Effective Savings Rate (ESR). Usage optimization measures success via utilization percentages, resource saturation, and efficiency benchmarks.
Long-term approach
Rate optimization delivers quick cost savings that compound over time. Usage optimization establishes sustainable efficiency and lean resource usage, driving enduring value. Together, both optimization strategies enable cost-efficient innovations that deliver immediate savings today with a sustainable, long-term approach to continue growing savings into the future.
Cloud Rate vs. Usage Optimization: Comparison Table
| Basis | Rate Optimization | Usage Optimization |
| Objective | Reduce the cost per unit of cloud resources consumed. | Reduce overall cloud consumption without impacting performance. |
| Focus | Negotiating better rates | Optimize architecture |
| Strategies/Components | Reserved Instances, Savings Plans and CUDs Custom contracts Volume discounts Spot pricing | Right-sizing workloads Eliminating unused resources Implementing auto-scaling Practicing efficient load balancing |
| Impact on cloud spend | Reduces costs by securing lower prices for the same amount of resource consumption. | Reduces costs by optimizing and reducing the amount of resources used. |
| Measurement | Utilization rate Coverage rate Effective Savings Rate | Utilization percentages Resource saturation Efficiency benchmarks |
| Flexibility | Less flexible, as it often requires long-term commitments or prepayment for resources. | Highly flexible, as it focuses on real-time adjustments to usage patterns. |
| Best Suited For | Stable workloads with predictable usage patterns. | Dynamic or unpredictable workloads where actual usage varies. |
| Potential Risks | Overcommitting to plans that aren’t fully used Limited savings if workloads change unexpectedly | Potential service disruption if optimization efforts aren’t carefully managed (e.g., scaling down too aggressively) |
| Automation Potential | Fully autonomous rate optimization platforms like ProsperOps can autonomously manage the purchase, renewal, and optimization of these discount instruments. Algorithms and policy-based automation handle the investing and renewal processes without any manual effort. | Automation potential with autoscaling, real-time monitoring, and resource rightsizing tools. But involves human involvement because of the decision-making involved. |
Implementing Rate and Usage Optimization
Integrating rate and usage optimization efforts enables your team to maximize value, minimize waste, and reduce costs while enhancing efficiency so you can benefit from compounding savings over time.
But to get the most out of both optimization approaches, it’s critical to find the right balance for your business. The best timing and order in which you implement each method can vary based on your organizational needs and capabilities.
Usage or rate optimization first?
There’s a common misconception that you shouldn’t implement rate optimization until your usage optimization is complete. But while optimizing usage can reduce the overall consumption of resources, it doesn’t address the underlying cost structure because you will still pay higher rates for the resources you use.
In reality, both usage and rate optimization are ongoing, iterative processes that should be addressed simultaneously. This approach aligns with the FinOps framework, which encourages continuous evaluation and adaptation of both usage patterns and cost structures.
By addressing both strategies in parallel, organizations can more effectively adapt to changing workloads and market conditions, maximizing savings and efficiency at every stage. Rather than viewing these strategies as one-time efforts, making them part of an ongoing cloud management process ensures that your business continuously optimizes for both cost and performance, now and into the future.
Simplify Your Cloud Cost Optimization Efforts With ProsperOps
FinOps adoption is increasing with more businesses prioritizing cloud rate and usage optimization. There are plenty of tips and best practices companies can use to reduce their cloud costs. However, using a tool such as ProsperOps to optimize cloud costs automatically is by far the easiest and most effective approach.
ProsperOps automatically blends discount instruments, such as AWS Savings Plans, Google Cloud committed use discounts, and Azure Reservations, to maximize savings and minimize commitment risk. By removing the effort, latency, and risk associated with manually managing rigid, long-term commitments, we fully automate rate optimization for you.
With ProsperOps automation, there is no impact on engineering. Our platform setup is quick, and our systems work behind the scenes to optimize your cloud costs. This allows your teams to concentrate on innovation and growth while we automate rate optimization for you.
To see ProsperOps in action, book a demo today.
