AWS Spot Instances offer discounts of up to 90% compared to On-Demand pricing. However, Spot management can be complex—especially when trying to balance your Spot usage with Reserved Instance (RI) and Savings Plan (SP) discounts. Since RIs and SPs are based on long-term commitments, shifting too much usage to Spot risks leaving prepaid commitments unused, resulting in wasted costs. For organizations with rapidly scaling usage, this balancing act can be particularly challenging.

If you’re looking for a comprehensive Spot management platform, sorting through the options can be complex. Solutions like Spot.io and Cast AI are designed to automate Spot Instance selection and management. On the other hand, platforms like nOps take a holistic cost optimization approach by integrating Spot, commitment management, and resource optimization to maximize your savings.

This guide explores how nOps, Spot.io, and Cast AI stack up in the Spot management landscape, detailing each platform’s unique features, advantages and disadvantages to help you make the best choice for your team.

The origin of Spot.io and Cast.ai

Spot.io (originally Spotinst) and Cast.ai launched in 2015 and 2019 respectively. As AWS Spot Instances emerged and grew in popularity due to their deep discounts, both platforms emerged to address the complexity of managing unpredictable Spot capacity interruptions. By automating Spot Instance selection, they helped companies benefit from Spot discounts. Spot.io was acquired by NetApp in 2020, and since then, the complexity of Kubernetes-based architecture has only continued to grow. 

What is Spot.io?

Logo of Spot.io Spot.io is a cloud cost management and optimization platform that automates Spot management. Its solutions are designed to balance savings with availability, integrating with Kubernetes and other orchestration tools to handle instance scaling and workload distribution based on demand. Spot.io includes features like Ocean, which automates Kubernetes infrastructure management to help users reduce cloud costs by dynamically adjusting nodes and optimizing workloads.

What is Cast.ai?

Logo of Cast AI Cast.ai is a Kubernetes-focused multi-cloud automation and optimization platform that provides automated scaling, rightsizing, and Spot management for Kubernetes clusters across AWS, Google Cloud, and Azure. The platform helps optimize resource allocation, enabling organizations to reduce cloud costs and maintain performance. CAST AI exclusively focuses on optimizing Kubernetes environments across different cloud providers.

nOps: All-In-One Cloud Cost Optimization

Unlike Spot.io and Cast.ai, which specialize in automating Spot Instance management and Kubernetes optimization, nOps provides a more holistic approach with deeper visibility into all aspects of cloud costs. nOps offers comprehensive insights across compute, storage, and networking, not just Spot or Kubernetes. This full-spectrum visibility, combined with automated optimization, enables teams to not only see cost-saving opportunities but also to act on them automatically—ensuring continuous optimization without manual intervention.

nOps is an all-in-one platform for:

nOps manages $2 billion in AWS spend and was recently ranked #1 with five stars in G2’s cloud cost management category —  book a demo to find out whether it might fit your organization’s needs.

Let’s briefly compare the features offered by each platform before diving into a more detailed analysis.

FeaturenOpsSpot.ioCast.ai
Spot  & EKS Management 
EKS Observability & Management✔️✔️✔️
Native integration with Karpenter or Cluster Autoscaler✔️✖️✖️
Spot Market Monitoring✔️✔️✔️
Fully Automated  Commitment (RI & SP) Management✔️✔️✖️
Intelligent Instance Selection✔️✔️✔️
Graceful Pod Rebalancing✔️✔️✔️
Real-time Workload Reconsideration✔️✔️✔️
Same reliability SLAs as AWS On-Demand✔️✖️✖️
One-click  Automated Container Rightsizing✔️✖️✔️
Deep Container & Node Efficiency Visibility✔️✖️✖️
Commitment Management 
Recommendations for Reserved Instances & Savings Plans ✔️✔️✔️
Fully automated management of RI & SP✔️✔️✖️
100% Utilization Guarantee for Commitments✔️✖️✖️
Visibility & Cloud Management
Cost Allocation✔️✔️✔️
Automated Tagging✔️✔️✔️
Budget Management✔️✖️✖️
Automated Reports & Dashboards✔️✖️✖️
Break down costs by any Kubernetes concept✔️✔️✔️
Break down costs by any finance concept✔️✖️✖️
Kubernetes Costs Unified with All Spend✔️✖️✖️
Role-Based Access Control✔️✔️✔️
Multi-cloud services✖️✔️✔️
Cloud Optimization Automation 
Automated Resource Rightsizing✔️✔️✔️
Automatically Eliminate Idle EC2✔️✖️✖️
Automated EBS Optimization✔️✖️✖️
Automated Resource Scheduling✔️✖️✖️
Automated GP2 to GP3✔️✖️✖️

For a complete comparison of cloud cost optimization platforms across the market, you can check out the full Buyer’s Guide to Cloud Optimization.

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A Buyer’s Guide to Cloud Cost Optimization
A complete comparison of cloud optimization tools
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1. Comprehensive Spot Management

nOps improves Spot instance management over traditional methods by using machine learning to monitor historical and real-time Spot market pricing and interruption trends. The result is better performance at lower costs (plus, huge time savings for engineering teams).  nOps makes it easy to adopt Spot best practices. The platform dynamically shifts workloads to the most reliable and cost-effective Spot instances available, diversifying instance types and regions to minimize the risk of sudden interruptions. Unlike typical Spot management, which often replaces instances reactively, nOps proactively rebalances workloads based on predictive insights and Spot best practices for more savings and stability. This approach drastically reduces Spot terminations to less than 1%, making it orders of magnitude easier to run on Spot.  You can see exactly what you’re saving with nOps — your effective savings, Spot termination rates, cluster cost over time, and other key performance metrics are fully transparent when you log in to the platform. The image displays a dashboard showing various metrics related to a cloud computing environment. The dashboard provides insights into instance types, availability zones, effective savings, termination rate, cost breakdown, container utilization, cluster cost over time, and average price per vCPU-hour, per GiB-hour, and per GPU-hour.

2. Comprehensive Commitment Management

Savings Plans (SP) and Reserved Instances (RI) offer discounts of up to 72% on all of your AWS compute in exchange for committing to a certain level of EC2 usage. But purchasing commitments can tricky — it’s difficult to know how much to commit to, and adding Spot into the mix makes matters even more complicated.  Many Spot management solutions risk putting your workloads onto too much Spot — which will end up costing you more in the long run because you are effectively wasting your prepaid commitments. That’s why to maximize savings, you need to optimize your Spot and your SP and RI together. The image illustrates the cost-saving benefits of using nOps. It compares cloud usage with and without nOps, showing a significant reduction in costs when using nOps. This reduction is achieved by effectively utilizing Spot Instances, maximizing Savings Plan usage, and leveraging Convertible Reserved Instances. By optimizing resource allocation and leveraging cost-effective options, nOps helps organizations significantly reduce their cloud expenses. nOps offers a fully automated commitment management solution, so you don’t have to spend time manually managing your discounts and juggling between SP, RI and Spot. Unique on the market, we offer a 100% commitment utilization guarantee (or we’ll credit you back at the end of the month) so you can be absolutely confident every dollar you spend is working for you.

3. Integration with Native EKS Autoscalers (Karpenter or Cluster Autoscaler)

Proprietary autoscalers often increase complexity and management overhead, and risk to vendor lock-in, limiting flexibility and adaptability compared to native integrations with Karpenter or Cluster Autoscaler. That’s why nOps integrates directly with your Karpenter or Cluster Autoscaler, for easy onboarding, simplicity of management, enhanced resource optimization, and no vendor lock-in.  Automation allows nOps to tune Karpenter much more frequently than a human could — translating to better results and many hours of work saved. As a result, engineering teams can focus on building and innovating rather than manual configuration. The image showcases how nOps Compute Copilot enhances Karpenter's capabilities for managing Amazon EKS clusters. It highlights key features like efficient cluster scaling, complete EKS visibility, container efficiency, rightsizing recommendations, AI-powered commitment management, and real-time workload reconsideration. The image emphasizes the synergy between Karpenter and nOps Compute Copilot in optimizing EKS clusters.

4. EKS Visibility & Optimization

Gaining visibility into Kubernetes workloads often requires multiple tools like Datadog, Cost Explorer, and Lens, complicating access to real-time insights on costs, performance, and workloads. For example, Lens provides detailed Kubernetes insights, but it is resource-intensive and requires elevated access and multiple steps to use.  With nOps, this complexity is streamlined. The nOps Kubernetes Dashboard offers the same visibility power as Lens — plus node monitoring, container rightsizing, workload troubleshooting, and binpacking — all in one tool. Monitor and trouble all your workloads in one place: gain a status overview, click into clusters, get insights, explore, and quickly understand what action to take. The image shows a list of workloads in a Kubernetes cluster. The table includes columns for workload name, nodes, labels, type, pods, events, CPU requests, memory requests, current 30-day cost, and estimated 30-day excess cost. The table shows various types of workloads, including Deployments, StatefulSets, Jobs, and CronJobs.

5. Cloud Optimization Automation

Another key piece of your EKS cost optimization is resource optimization. nOps Essentials makes it easy to tackle these time-consuming optimization tasks, with automation tools for resource rightsizing, container rightsizing, idle EC2 and EBS cleanup, resource scheduling, one-click GP2 to GP3 migration, EBS snapshot cleanup, and more.  nOps integrates with your preferred monitoring tools (Datadog, CloudWatch, etc.) for high-resolution recommendations that can be implemented in one click. The image shows a table displaying container rightsizing recommendations. The table includes columns for container name, namespace, labels, current CPU and memory requests, estimated 30-day cost, estimated 30-day waste, and a chart icon. The table shows recommendations for optimizing resource allocation for various containers, with potential cost savings highlighted.

6. Total Cost Visibility

nOps Business Contexts is a free platform that makes it easy to understand and allocate 100% of your AWS costs, from your largest resources all the way down to your individual container costs. It unifies your Kubernetes costs with the rest of your AWS spend, so you can understand and report on your shared costs without the hassle of reconciling multiple data sources. The image shows a cost analysis report for an engineering budget. The report includes a spend summary, usage chart, and filters to customize the view. The spend summary shows the total cost for the month and compares it to the previous month. The usage chart displays the cost breakdown by different cost entities. The filters allow users to refine the report by cost type, cost entity, accounts, and other parameters. BusinessContexts+ adds enhanced functionality to simplify the AWS cost reporting process for DevOps, Engineering, FinOps, and Finance teams. With custom reports and dashboards built by FinOps experts, role-based access control, and 40+ filters and views, it’s easier than ever to get the cost insights your organization needs to better understand and optimize your AWS spend, all the way down to the node or container level. The image shows a dashboard that allows you to break down costs by various Kubernetes concepts like cluster name, node, namespace, controller kind, controller, deployment, service, pod, container, and labels. This level of granularity helps you identify cost-saving opportunities and optimize resource allocation.

About nOps

nOps was recently ranked #1 with five stars in G2’s cloud cost management category, and we optimize $2 billion in cloud spend for our customers. 

At nOps, our mission is to make it easy for engineers to optimize. Join our customers using nOps to understand your cloud costs and leverage automation with complete confidence by booking a demo today!