Reserved Instances vs Spot Instances: Which Saves More?

Spot instances have a significant interruption risk but can save more, possibly up to 90% off on-demand pricing. For a commitment of one to three years, reserved instances offer guaranteed uptime and substantial savings of up to 72%. The ideal option will rely on how much disruption your workload can handle vs how much capacity and price you require.

In essence, cloud instances are virtual servers that offer processing power whenever needed. Consider them as rental computers that you may use anytime you want without having to deal with actual hardware. To accommodate varying workload requirements, they are available in a range of sizes and configurations.

Three primary types predominate when weighing your options: On-Demand, Reserved, and Spot Instances. Each has distinct pricing structures and functions that might significantly affect your cloud budget:

• On-Demand Instances: Pay-as-you-go with maximum flexibility but at premium prices
• Reserved Instances: 1-3 year commitments with substantial discounts (up to 72%)
• Spot Instances: Unused capacity at deep discounts (up to 90%) but can be terminated with minimal notice

It is impossible to overestimate the significance of selecting the best purchase option. By moving from On-Demand to Reserved Instances, a startup with steady workloads could save up to 72%, while businesses with flexible applications might gain more from the significant savings offered by Spot Instances.

In this article, we will focus on reserved and spot instances and which of them should be your best option.

Spot Instances

The demand for clever cost-optimization techniques is growing along with cloud utilization. For certain kinds of workloads, Spot Instances offer a flexible and significantly reduced option, while Reserved Instances offer long-term savings and dependability. You may significantly reduce the cost of your cloud infrastructure by knowing when and how to employ Spot Instances. Here’s a thorough explanation of Spot Instances, including their advantages, difficulties, best use cases, and advice on how to make the most of them.

Major cloud providers like AWS, Azure, and Google Cloud offer a virtual machine pricing mechanism called Spot Instances. They enable consumers to utilize underutilized processing power at significantly reduced costs—typically up to 90% less than On-Demand rates. When capacity is required elsewhere, the supplier may, however, abruptly stop these instances. Spot instances are perfect for low-cost, non-critical computing since they are made for applications that are adaptable, stateless, or able to withstand disruptions.

The price of Spot Instances is their main selling point. Spot Instances provide a technique to significantly cut cloud costs if you’re conducting large-scale compute-intensive operations or workloads that can be interrupted and resumed. Additionally, they are excellent for expanding parallel workloads without breaking the bank. Spot Instances offer a low-cost sandbox for teams wishing to test or prototype in the cloud without going over budget.

Pros and Cons of Using Spot Stances

Spot Instances have significant trade-offs notwithstanding the savings. The largest risk is interruption, as cloud providers can end your instance at any time with as little as two minutes’ notice (AWS). Unless they are built to withstand disturbances, their unpredictability renders them inappropriate for stateful or mission-critical applications. Furthermore, when capacity is limited, you might not be able to start Spot Instances; availability is not guaranteed. Additionally, there is little control over the instance lifecycle, which necessitates careful planning and automation of infrastructure.

Advantages 

• Massive cost savings: Spot Instances are typically 70–90% cheaper than On-Demand instances, making them ideal for cost-sensitive workloads like batch processing, containerized jobs, and data analysis.
• Scale compute capacity affordably: You can run large-scale workloads (e.g., distributed training, high-throughput simulations) at a fraction of the cost, enabling experimentation or parallelism that would be too expensive otherwise.
• Same performance as On-Demand: Spot Instances use the same underlying hardware and offer identical performance, networking, and storage options.
• Seamless integration with autoscaling: You can mix Spot and On-Demand Instances in Auto Scaling Groups, helping reduce costs while maintaining baseline reliability.

Disadvantages 

• Interruptions: AWS can terminate Spot Instances with just a 2-minute warning when capacity is no longer available at your bid price. This makes them unsuitable for critical or stateful workloads without fault tolerance.
• Unpredictable availability: Spot capacity fluctuates based on regional demand. There’s no guarantee your preferred instance type will always be available at the Spot price.
• Can lead to double-paying: If you have unused Reserved Instances or Savings Plans, running workloads on Spot can waste those prepaid commitments.
• Limited support for some services: Not all AWS services support Spot Instances (e.g., managed RDS, Lambda, or certain GPU workloads in Bedrock or SageMaker).

Suitable Use Cases for Spot Instances

1. Batch Processing Jobs – Data-heavy workloads like ETL jobs, media transcoding, or genomic sequencing that can run asynchronously and tolerate restarts.
2. Stateless Web Services – Microservices or backend services that can be quickly replaced or scaled horizontally.
3. Machine Learning Model Training – Training tasks that run for hours or days but can checkpoint progress and resume on different instances.
4. CI/CD Pipelines – Build and test environments in continuous integration pipelines where jobs are short-lived and reproducible.
5. Big Data Analytics – Distributed compute jobs like Hadoop or Spark that can scale across multiple spot instances and handle node failures.

How to Optimizing Spot Instance Use

1. Use Auto Scaling with Mixed Instance Types – Combine On-Demand, Reserved, and Spot Instances in autoscaling groups to maintain availability and flexibility.
2. Implement Checkpointing – For long-running jobs, save intermediate progress so that tasks can resume after interruptions.
3. Use Spot Fleets or Spot Instance Pools – Diversify across instance types and availability zones to reduce the risk of termination and improve availability.
4. Leverage Interrupt Handling Scripts – Use lifecycle hooks or scripts to gracefully shut down or migrate tasks when a termination notice is received.
5. Monitor and Automate with Cloud-Native Tools – Use tools like AWS EC2 Spot Advisor or GCP Recommender to identify optimal configurations and pricing opportunities.

When utilized properly, Spot Instances can be a potent weapon in your toolbox for cutting costs. Incorporating Spot Instances for flexible, non-critical operations can significantly reduce your overall cloud spend, even though Reserved Instances are still necessary for predictable workloads. You can design a cloud infrastructure that maximizes savings without sacrificing performance by knowing their advantages and disadvantages.

Read Also: Cloud Auto-Scaling: What It Is and Why It Matters

Reserved Instances

With reserved instances, you may set aside a certain amount of processing power for a predetermined amount of time—typically one or three years. Compared to On-Demand, you can receive a savings of up to 72% on monthly or hourly charges since you sign a long-term contract. Reserved instances reserve capacity exclusively for the availability zone to which they are assigned. You can start the instances whenever needed if you reserve the capacity. To maximize cloud expenditures, if you are committing to a RI for one or three years, make sure you will use all of its capacity during that time. Workloads with a consistent and predictable demand, such as databases and web servers, are better suited for reserved instances.

There are two types of Reserved Instances available:  

Standard RIs: They are usually used in workloads that have little to no variation in performance over the period of several months or years. With standard RIs, you can modify the scope, availability zone, instance size, and networking type of the reserved instances. You can also sell them on the Reserved Instance Marketplace in some cases. 

Convertible RIs: They are used for workloads that require flexibility in terms of changing operating systems or instance families. Note that you cannot sell them in the Reserved Instance Marketplace.

Pro and Cons of Reserved Instances

Reserved instances have many drawbacks despite their financial advantages. First of all, they necessitate a long-term commitment, which may restrict flexibility in the event that your infrastructure requirements change. Additionally, RIs are not portable across all instance types, which might result in inefficiencies if you overprovision. Additionally, you could not get the anticipated cost reductions if you don’t fully employ the capacity you’ve committed to. To lessen these problems, some providers offer marketplaces or convertible RIs, although careful planning and resource predictions are still necessary.

Pros

• Significant cost savings: Standard RIs offer up to 72% off compared to On-Demand pricing, and Convertible RIs offer up to 55%, making them ideal for steady-state workloads.
• Predictable billing: RIs provide consistent hourly billing, which simplifies budgeting and long-term forecasting.
• Convertible RIs can be exchanged: Convertible RIs allow you to change instance families, OS types, or tenancies during the term, so you’re not locked into your original configuration (for a slightly lower discount).
• Standard RIs can be resold: If your usage changes, you can often resell unused Standard RIs in the RI Marketplace — unless they were purchased through an EDP or special discount.

Cons

• Commitment risk: You’re locked into a 1- or 3-year term. If your usage drops or changes, you may end up paying for unused capacity.
• Lack of real-time flexibility: Unlike On-Demand or Spot, RIs can’t adapt dynamically to changes in traffic, infrastructure design, or new instance types.
• Complexity: There are literally thousands of types of RI — without careful planning, you can overcommit or choose the wrong type, leading to wasted spend.
• Management overhead: Tracking utilization, managing expirations, and optimizing coverage across accounts and services can be time-consuming without the right tooling.

When to Choose for Reserved Instances

1. Always-On Applications – Ideal for systems that run 24/7, like web servers, APIs, or backend services.
2. Databases and Caching Layers – For relational databases, in-memory data stores, or NoSQL clusters that have predictable workloads.
3. Enterprise Software Licensing – If you’re running licensed software like Windows Server or SQL Server, RIs help reduce cost over time.
4. Internal Tools and Infrastructure – Perfect for tools like monitoring systems, CI/CD platforms, or VPNs that have stable usage patterns.

Best Practices for Leveraging Reserved Instances

1. Analyze Historical Usage – Use tools like AWS Cost Explorer or Azure Advisor to identify consistent usage patterns before committing.
2. Choose the Right Payment Option – Evaluate All Upfront, Partial Upfront, or No Upfront based on your cash flow and cost-saving goals.
3. Use Convertible RIs When Flexibility Is Needed – Convertible RIs allow you to change instance types and configurations during the term.
4. Combine with Other Pricing Models – Blend RIs with On-Demand and Spot Instances for a balanced, cost-efficient architecture.
5. Monitor and Reassess Regularly – Cloud usage can evolve, so track utilization and modify your reservation strategy annually or as needed.

Difference Between Spot Instances vs Reserved Instances

Take into account these five factors that affect infrastructure strategy, operational dependability, and cost effectiveness while choosing between Spot Instances and Reserved Instances (RIs).

1. Budget Consideration

Spot Instances offer steep discounts — great for cutting costs on interruptible workloads or handling intermittent usage spikes (e.g., nightly batch jobs, bursty dev/test environments). RIs are better for predictable, steady-state workloads where you know you’ll need capacity 24/7. But upfront cost isn’t the only consideration:

• Spot may save money on compute, but costs engineer time — handling interruptions, diversifying capacity pools, and tuning autoscaling logic.
• RIs save time with predictable behavior — but they’re “always on” whether you use the compute or not.
• You can’t “turn off” an RI — unused hours are wasted. You can shut down Spot to avoid cost.
• If you’ve already bought RIs or Savings Plans and use Spot instead, you risk double paying — unused commitments plus active Spot spend.

2. Workload Attributes

Spot works well for jobs that are fault-tolerant, parallelizable, or transient — like EMR, Spark, containerized ML training, or infrastructure experiments.

Reserved Instances are a better fit for workloads that need guaranteed continuity: production services, persistent databases, and monolithic applications that don’t tolerate interruption.

Key distinction: Spot is an operational fit, not just a financial one — it only works if your workload is architected to restart, resume, or tolerate gaps.

3. Interruption Risk and Engineering Resilience

Spot Instances can be reclaimed at any time with just 2 minutes’ notice. That risk isn’t theoretical — in high-demand periods or narrow capacity pools, interruptions are frequent and unpredictable.This can cause real problems:

• Job failures or data loss if workloads don’t checkpoint or save intermediate state.
• Pipeline instability in systems like Spark or Airflow, especially when preempted in the middle of a DAG.
• Scaling delays when autoscalers can’t replace capacity fast enough, leading to queue buildup or latency.
• Increased engineering overhead from writing interruption handlers, diversifying across instance types, and tuning retry logic.

If your system isn’t designed for ephemeral compute — or you don’t have the tooling to help with that complexity — Spot might be more trouble than it’s worth.

4. Control, Flexibility, and Lock-In

Spot gives you tactical flexibility — start and stop whenever you want, across a wide range of instance types. You’re not locked in; you can turn off Spot instances any time.

RIs offer financial efficiency if you know what you need — but they’re locked to instance families and regions (unless you use Convertible RIs, which can be difficult to manage without an automation platform).

Another mechanism adding flexibility is the Standard RI marketplace — but it’s worth noting that you can only resell RIs under certain circumstances and any RI purchased under a discount like EDP cannot be resold. Additionally, AWS has tightened policies around third-party resellers, limiting resale flexibility and making the process more restrictive than in previous years.

5. Layering Spot and Reserved Requires Orchestration Discipline

For the most flexibility and discounts, you’ll likely need a combination of both Spot and Reserved Instances. Many teams combine RIs for baseline workloads and Spot for burst capacity — a best practice in theory, but harder in execution. Without precise orchestration, you risk inefficiencies like:

• Double paying: Spot instances running while Reserved capacity sits idle.
• Inefficient placement: Workloads landing on higher-cost On-Demand or incorrectly matched instances.
• Coverage waste: Reserved Instances applied to workloads that are scaled down or relocated.