Are Reserve Instances Truly Cost-Savers in the Cloud?

Rachana Gupta
3 min readSep 27, 2023


The cloud computing industry has experienced an exponential rise in popularity over the past decade, with organizations worldwide adopting cloud-based services for their scalability, flexibility, and cost-efficiency. Among the numerous pricing options offered by cloud service providers, Reserve Instances have gained significant attention for their potential cost-saving benefits. Even the cost saving recommendations from vendors seems to indicate reserving saves cost. In this article, we will explore why Reserve Instances may not be the cost-savers they appear to be.

Understanding Reserve Instances

Reserve Instances, also known as Reserved Virtual Machine Instances or Reserved Instances (RIs), are long-term commitments offered by cloud providers like AWS, Azure, and Google Cloud. These commitments involve customers prepaying for a specific amount of compute capacity in exchange for reduced hourly rates compared to On-Demand Instances. The idea is that by making an upfront commitment, organizations can save substantially on their cloud computing costs over time.

The Pitfalls of Reserve Instances (RIs)

1. Fixed Capacity and Limited Flexibility

One of the fundamental drawbacks of Reserve Instances is their inflexibility. When organizations purchase RIs, they commit to a fixed amount of compute capacity for a specific period, typically one or three years. This can be problematic because cloud workloads are often dynamic and change over time. As a result, organizations may find themselves with excess or insufficient capacity, leading to inefficient resource allocation.

2. Unused Capacity of instances

One of the most significant issues with RIs is the potential for unused capacity. In many cases, organizations overestimate their future compute requirements when purchasing RIs. This can result in paying for unused resources, effectively negating any potential cost savings. Furthermore, when workloads change, it may be challenging to repurpose or modify RIs to match new requirements.

3. Limited Coverage and not work for all use cases

RIs are specific to a particular instance type, region, and availability zone, limiting their applicability. If an organization’s workloads or requirements change, they may find themselves locked into RIs that no longer align with their needs. This can lead to a loss of cost savings and the need to purchase additional On-Demand Instances to accommodate changing workloads.

4. Hidden Costs which the vendor doesn’t disclose

While RIs offer lower hourly rates, they come with upfront costs that can be substantial. These upfront payments can strain an organization’s budget and reduce the immediate cash flow benefits of using cloud services. Moreover, the commitment to RIs may deter organizations from exploring alternative cloud services or providers that might offer more cost-effective solutions.

5. Complex operations Management

Effectively managing RIs requires a deep understanding of an organization’s workloads and future needs. Many organizations struggle with optimizing their RI portfolios, resulting in missed savings opportunities or unnecessary expenses. This complexity can lead to added administrative overhead and the need for specialized tools or expertise.


While Reserve Instances may seem like a cost-saving solution in the cloud, they often fall short of delivering on their promises. The inflexibility, potential for unused capacity, limited coverage, hidden costs, and complex management associated with RIs can undermine their cost-saving potential. To truly optimize cloud spending, organizations should consider a more dynamic approach, such as using a mix of On-Demand Instances, Spot Instances, and Reserved Instances strategically based on their workloads’ specific requirements. Additionally, regularly reviewing and adjusting cloud resources is essential to ensure that costs remain in line with actual usage, rather than being bound by rigid RI commitments. In the end, the key to cost savings in the cloud is not just about locking into commitments but about adapting and optimizing resources as needed.