Alternatives to EC2 Spot
Compare EC2 Spot alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to EC2 Spot in 2026. Compare features, ratings, user reviews, pricing, and more from EC2 Spot competitors and alternatives in order to make an informed decision for your business.
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AWS Auto Scaling
Amazon
AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost. Using AWS Auto Scaling, it’s easy to setup application scaling for multiple resources across multiple services in minutes. The service provides a simple, powerful user interface that lets you build scaling plans for resources including Amazon EC2 instances and Spot Fleets, Amazon ECS tasks, Amazon DynamoDB tables and indexes, and Amazon Aurora Replicas. AWS Auto Scaling makes scaling simple with recommendations that allow you to optimize performance, costs, or balance between them. If you’re already using Amazon EC2 Auto Scaling to dynamically scale your Amazon EC2 instances, you can now combine it with AWS Auto Scaling to scale additional resources for other AWS services. With AWS Auto Scaling, your applications always have the right resources at the right time. -
2
Xosphere
Xosphere
Xosphere Instance Orchestrator automatically performs spot optimization by leveraging AWS Spot instances to optimize the cost of your infrastructure while maintaining the same level of reliability as on-demand instances. Spot instances are diversified amongst family, size, and availability zones to minimize any impact when Spot instances are reclaimed. Instances utilizing reservations will not be replaced by Spot instances. Automatically respond to Spot termination notifications and fast-track replacement on-demand instances. EBS volumes can be configured to be attached to new replacement instances enabling stateful applications to work seamlessly. -
3
Spot Ocean
Spot by NetApp
Spot Ocean lets you reap the benefits of Kubernetes without worrying about infrastructure while gaining deep cluster visibility and dramatically reducing costs. The key question is how to use containers without the operational overhead of managing the underlying VMs while also take advantage of the cost benefits associated with Spot Instances and multi-cloud. Spot Ocean is built to solve this problem by managing containers in a “Serverless” environment. Ocean provides an abstraction on top of virtual machines allowing to deploy Kubernetes clusters without the need to manage the underlying VMs. Ocean takes advantage of multiple compute purchasing options like Reserved and Spot instance pricing and failover to On-Demand instances whenever necessary, providing 80% reduction in infrastructure costs. Spot Ocean is a Serverless Compute Engine that abstracts the provisioning (launching), auto-scaling, and management of worker nodes in Kubernetes clusters. -
4
Lightwing
Lightwing
Save up to 90% on monthly cloud bills. Lightwing helps you go from sign up to cost optimized in under 60mins. Optimize the compute of all your production resources using AWS Spot instances or Azure Spot instances. Achieve stable and reliable high availability, while still fully benefitting from spot instance pricing. Go from sign up to fully cost-optimized in under 60mins. Use Smart Advisor to bucket your cloud resources based on usage (production or non-production) and nature (state and fault tolerance). Get an immediate estimate on exactly how much you can save on your cloud compute bills using Lightwing. Implement the required cost optimization automation and start saving on your cloud costs instantly. Helping our customers cost-optimize their cloud infrastructure is all we do, all day every day. -
5
Elastigroup
Spot by NetApp
Provision, manage and scale compute infrastructure on any cloud. Save up to 80% on your costs while ensuring SLA and high-availability. Elastigroup is a cluster software, designed to optimize performance and costs. It enables companies of all sizes and verticals to reliably leverage Cloud Excess Capacity to optimize and accelerate workloads and save up to 90% on infrastructure compute costs. Elastigroup makes use of proprietary price prediction technology to deploy reliably onto Spot Instances. By predicting interruptions and fluctuations Elastigroup is able to offensively rebalance clusters to prevent interruption. Elastigroup reliably leverages excess capacity across all major cloud providers such as EC2 Spot Instances (AWS), Low-priority VMs (Microsoft Azure) and Preemptible VMs (Google Cloud), while removing risk and complexity, providing simple orchestration and management at scale. -
6
nOps
nOps.io
FinOps on nOps We only charge for what we save. ✓Continuous Cloud waste reduction ✓Continuous Container cluster optimization ✓Continuous RI management to save up to 40% over on-demand resources ✓Spot Orchestrator to reduce cost over on-demand resources Most organizations don’t have the resources to focus on reducing cloud spend. nOps is your ML-powered FinOps team. nOps reduces cloud waste, helps you run workloads on spot instances, automatically manages reservations, and helps optimize your containers. Everything is automated and data-driven.Starting Price: $99 per month -
7
Uniskai by Profisea Labs
Profisea Labs
Uniskai by Profisea Labs is an AI-driven multi-cloud cost optimization platform designed to help DevOps and FinOps teams gain full control over their cloud spending and reduce costs by up to 75%. It offers an intuitive billing dashboard with detailed cost show-back and future cost predictions, enabling users to monitor and manage expenses across AWS, Azure, and GCP. The platform provides personalized rightsizing recommendations to select the ideal instance size and type aligned with actual workload demands and features a distinctive strategy to transform instances into cost-effective spots, seamlessly managing Spot Instances to minimize downtime through proactive system actions. Uniskai's Waste Manager swiftly identifies unutilized, duplicated, or improperly sized resources and backups, allowing users to eliminate cloud waste with a single click.Starting Price: $10 per month -
8
Vast.ai
Vast.ai
Vast.ai is the market leader in low-cost cloud GPU rental. Use one simple interface to save 5-6X on GPU compute. Use on-demand rentals for convenience and consistent pricing. Or save a further 50% or more with interruptible instances using spot auction based pricing. Vast has an array of providers that offer different levels of security: from hobbyists up to Tier-4 data centers. Vast.ai helps you find the best pricing for the level of security and reliability you need. Use our command line interface to search the entire marketplace for offers while utilizing scriptable filters and sort options. Launch instances quickly right from the CLI and easily automate your deployment. Save an additional 50% or more by using interruptible instances and auction pricing. The highest bidding instances run; other conflicting instances are stopped.Starting Price: $0.20 per hour -
9
xtype
xtype
xtype empowers ServiceNow platform teams to innovate faster, govern multiple instances, shrink the backlog, ensure compliance, and reduce operational risk. xtype is a cutting-edge product that revolutionizes the backup and restores activities for cloning ServiceNow instances. It drastically reduces the preparation time and improves accuracy by automatically identifying what needs to be backed up and restored. Gain unparalleled visibility into your ServiceNow environment with xtype. It provides a live shared view of backup and restore plans, enabling real-time collaboration and visibility of work-in-progress. This ensures all team members are aligned and informed about their responsibilities and the clone status, fostering collaboration and efficiency. xtype provides a multi-instance of your ServiceNow landscape with a purpose-built visibility product native to ServiceNow, giving you, in minutes, the ability to spot and remediate any version inconsistencies. -
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Exafunction
Exafunction
Exafunction optimizes your deep learning inference workload, delivering up to a 10x improvement in resource utilization and cost. Focus on building your deep learning application, not on managing clusters and fine-tuning performance. In most deep learning applications, CPU, I/O, and network bottlenecks lead to poor utilization of GPU hardware. Exafunction moves any GPU code to highly utilized remote resources, even spot instances. Your core logic remains an inexpensive CPU instance. Exafunction is battle-tested on applications like large-scale autonomous vehicle simulation. These workloads have complex custom models, require numerical reproducibility, and use thousands of GPUs concurrently. Exafunction supports models from major deep learning frameworks and inference runtimes. Models and dependencies like custom operators are versioned so you can always be confident you’re getting the right results. -
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Ori GPU Cloud
Ori
Launch GPU-accelerated instances highly configurable to your AI workload & budget. Reserve thousands of GPUs in a next-gen AI data center for training and inference at scale. The AI world is shifting to GPU clouds for building and launching groundbreaking models without the pain of managing infrastructure and scarcity of resources. AI-centric cloud providers outpace traditional hyperscalers on availability, compute costs and scaling GPU utilization to fit complex AI workloads. Ori houses a large pool of various GPU types tailored for different processing needs. This ensures a higher concentration of more powerful GPUs readily available for allocation compared to general-purpose clouds. Ori is able to offer more competitive pricing year-on-year, across on-demand instances or dedicated servers. When compared to per-hour or per-usage pricing of legacy clouds, our GPU compute costs are unequivocally cheaper to run large-scale AI workloads.Starting Price: $3.24 per month -
12
Spot by NetApp
NetApp
Spot by NetApp is a suite of cloud operations solutions designed to optimize and automate cloud infrastructure, ensuring applications receive continuously optimized resources that balance performance, availability, and cost. By leveraging advanced analytics and machine learning, Spot enables organizations to achieve up to 90% cost reduction on cloud compute expenses by dynamically utilizing a mix of spot, reserved, and on-demand instances. The platform offers comprehensive tools for cloud financial management (FinOps), Kubernetes infrastructure optimization, and cloud commitment management, providing full visibility into cloud environments and automating operations for maximum efficiency. With Spot by NetApp, businesses can accelerate their cloud adoption, improve operational agility, and maintain robust security across multi-cloud and hybrid environments. -
13
GPU Trader
GPU Trader
GPU Trader is a secure, enterprise-class marketplace that connects organizations with high-performance GPUs in on-demand and reserved instance models. It offers instant access to powerful GPUs tailored for AI, machine learning, data analytics, and high-performance compute workloads. With flexible pricing options and instance templates, users can scale effortlessly and pay only for what they use. It ensures complete security with a zero-trust architecture, transparent billing, and real-time performance monitoring. GPU Trader's decentralized architecture maximizes GPU efficiency and scalability with secure workload management across distributed networks. GPU Trader manages workload dispatch and real-time monitoring, while containerized agents on GPUs autonomously execute tasks. AI-driven validation ensures all GPUs meet high-performance standards, providing reliable resources for renters.Starting Price: $0.99 per hour -
14
Eco
Spot by NetApp
Automated Optimization for AWS Savings Plans and Reserved Instances. Simplify the planning, purchasing and optimization of your cloud commitments portfolio. Eco automates reserved instance lifecycle management, creating a high-ROI, low-risk cloud commitment portfolio that matches your current and projected needs. By identifying and selling off unused capacity and buying appropriate short-term, third-party reservations on the AWS Marketplace, Eco delivers all the benefits of long-term pricing without financial lock-in. Ensure maximum ROI on cloud commitment purchases with analysis, modification and mapping of unused reserved instances and Savings Plans to resource demands. Automate purchasing strategies for reserved instances in the AWS Marketplace throughout their lifecycle to ensure workloads are always running at optimal pricing. Enable collaboration between Finance and DevOps teams with full visibility into compute consumption and automation of optimal reserved instances. -
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AWS Thinkbox Deadline
Amazon
Automatically sync on-premises asset files to Amazon Simple Storage Service (S3), ensuring availability in the cloud. Synchronize with local servers, manage data transfers before rendering begins, and tag accounts and instances for bill allocation. Purchase usage-based software licenses, bring your own licenses, or use a combination of both to create third-party digital content. Leverage Amazon Elastic Compute Cloud (EC2) Spot Instances to save up to 90% compared to on-demand pricing. Set up a render farm in minutes, run more projects in parallel, and improve cost control. Generate a hybrid or cloud-based render farm and scale to thousands of cores in minutes with the AWS Portal. Build, tailor, and deploy render farms with the Render Farm Deployment Kit (RFDK) using familiar programming languages, such as Python. Use the Jigsaw tool to render very high-resolution images faster by distributing them across multiple machines. -
16
BidElastic
BidElastic
It isn’t always straightforward to benefit from the rich features of cloud services. To make it easier for businesses to use the cloud, we developed BidElastic as a resource provisioning tool with two components: BidElastic BidServer cuts computational costs; BidElastic Intelligent Auto Scaler (IAS) streamlines management and monitoring of your cloud provider. The BidServer uses simulation and advanced optimization routines to anticipate market movements and to design a robust infrastructure for cloud providers’ spot instances. To match demand in volatile workloads, you need to scale your cloud infrastructure dynamically. But that’s easier said than done. There’s a traffic spike and only 10 minutes later are new servers online. In the meantime you’ve lost customers who may never come back. To scale your resources properly you need to be able to predict computational workloads. CloudPredict does exactly that; it uses machine learning to predict computational workloads. -
17
AWS Batch
Amazon
AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. AWS Batch dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. With AWS Batch, there is no need to install and manage batch computing software or server clusters that you use to run your jobs, allowing you to focus on analyzing results and solving problems. AWS Batch plans, schedules, and executes your batch computing workloads across the full range of AWS compute services and features, such as AWS Fargate, Amazon EC2 and Spot Instances. There is no additional charge for AWS Batch. You only pay for the AWS resources (e.g. EC2 instances or Fargate jobs) you create to store and run your batch jobs. -
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Tencent Cloud Virtual Machine
Tencent
To meet your ever-changing business needs, you can quickly add or delete CVMs in minutes. By defining relevant policies, you can ensure that your CVM instances will be seamlessly scaled up during periods of higher demand to ensure application availability and scaled down during periods of lower demand to save costs. CVM offers a wide variety of instances, operating systems and software packages. You can flexibly adjust each instance’s CPU, memory, disk and bandwidth configuration to match your applications. CVM supports multiple Linux distribution versions and Windows Server versions. You can access Tencent Cloud CVM as an administrator with full control. Using various tools such as the Tencent Cloud console and APIs, you can connect to your CVM instances and perform operations like restarting and modifying your network configurations. -
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AWS CloudFormation
Amazon
AWS CloudFormation is a infrastructure provisioning and management tool that provides you the ability to create resource templates that specifies a set of AWS resources to provision. The templates allow you to version control your infrastructure, and also easily replicate your infrastructure stack quickly and with repeatability. Define an Amazon Virtual Private Cloud (VPC) subnet or provisioning services like AWS OpsWorks or Amazon Elastic Container Service (ECS) with ease. Run anything from a single Amazon Elastic Compute Cloud (EC2) instance to a complex multi-region application. Automate, test, and deploy infrastructure templates with continuous integration and delivery (CI/CD) automation. AWS CloudFormation lets you model, provision, and manage AWS and third-party resources by treating infrastructure as code. Speed up cloud provisioning with infrastructure as code.Starting Price: $0.0009 per handler operation -
20
Trellix Cloud Workload Security
Trellix
A single-pane view helps consolidate management across physical, virtual, and hybrid-cloud environments. Benefit from secure workloads all the way from on-prem to cloud, across the board. Automates the defense of elastic workloads to eliminate blind spots and deliver advanced threat defense. Leverage advanced host-based workload defense optimized specifically for virtual instances to avoid straining overall infrastructure. Avail virtual machine-optimized threat defenses that help deliver multilayer countermeasures. Gain awareness and protect your virtualized environment and network from external malicious sources. Comprehensive countermeasures, including machine learning, application containment, virtual machine-optimized anti-malware, whitelisting, file integrity monitoring, and micro-segmentation, to protect your workloads. Helps assign and manage all workloads automatically with the ability to import AWS and Microsoft Azure tag information into Trellix ePO. -
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Cost-effectively run mission-critical workloads at scale with Azure Managed Instance for Apache Cassandra. Easily manage changing demands with multiple resource and data replication options. Ensure business continuity with zero downtime scalability for hybrid and cloud deployments. Develop applications faster using familiar and fully compatible Cassandra tools and languages. Free yourself from infrastructure management without compromising security. Run your workloads on a managed, secure service to streamline operations with automated repairs, patches, and updates. Make your database more durable and resilient with automatic backups and disaster recovery. Retain the flexibility and control of your hardware configuration with turnkey scaling services and hybrid deployment options. An instance-based pricing model enables you to define the number of CPU cores, virtual machines SKU, and memory/disk space needs.Starting Price: $0.911 per hour
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AWS Elastic Fabric Adapter (EFA)
United States
Elastic Fabric Adapter (EFA) is a network interface for Amazon EC2 instances that enables customers to run applications requiring high levels of inter-node communications at scale on AWS. Its custom-built operating system (OS) bypass hardware interface enhances the performance of inter-instance communications, which is critical to scaling these applications. With EFA, High-Performance Computing (HPC) applications using the Message Passing Interface (MPI) and Machine Learning (ML) applications using NVIDIA Collective Communications Library (NCCL) can scale to thousands of CPUs or GPUs. As a result, you get the application performance of on-premises HPC clusters with the on-demand elasticity and flexibility of the AWS cloud. EFA is available as an optional EC2 networking feature that you can enable on any supported EC2 instance at no additional cost. Plus, it works with the most commonly used interfaces, APIs, and libraries for inter-node communications. -
23
Amazon EC2 P4 Instances
Amazon
Amazon EC2 P4d instances deliver high performance for machine learning training and high-performance computing applications in the cloud. Powered by NVIDIA A100 Tensor Core GPUs, they offer industry-leading throughput and low-latency networking, supporting 400 Gbps instance networking. P4d instances provide up to 60% lower cost to train ML models, with an average of 2.5x better performance for deep learning models compared to previous-generation P3 and P3dn instances. Deployed in hyperscale clusters called Amazon EC2 UltraClusters, P4d instances combine high-performance computing, networking, and storage, enabling users to scale from a few to thousands of NVIDIA A100 GPUs based on project needs. Researchers, data scientists, and developers can utilize P4d instances to train ML models for use cases such as natural language processing, object detection and classification, and recommendation engines, as well as to run HPC applications like pharmaceutical discovery and more.Starting Price: $11.57 per hour -
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Amazon EC2 Capacity Blocks for ML enable you to reserve accelerated compute instances in Amazon EC2 UltraClusters for your machine learning workloads. This service supports Amazon EC2 P5en, P5e, P5, and P4d instances, powered by NVIDIA H200, H100, and A100 Tensor Core GPUs, respectively, as well as Trn2 and Trn1 instances powered by AWS Trainium. You can reserve these instances for up to six months in cluster sizes ranging from one to 64 instances (512 GPUs or 1,024 Trainium chips), providing flexibility for various ML workloads. Reservations can be made up to eight weeks in advance. By colocating in Amazon EC2 UltraClusters, Capacity Blocks offer low-latency, high-throughput network connectivity, facilitating efficient distributed training. This setup ensures predictable access to high-performance computing resources, allowing you to plan ML development confidently, run experiments, build prototypes, and accommodate future surges in demand for ML applications.
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25
Oracle Bare Metal Servers
Oracle
Oracle bare metal servers provide customers with isolation, visibility, and control with a dedicated server. The servers support applications that require high core counts, large amounts of memory, and high bandwidth - scaling up to 128 cores (the largest in the industry), 2 TB of RAM, and up to 1 PB of block storage. Customers can build cloud environments in Oracle bare metal servers with significant performance improvements over other public clouds and on-premises data centers. The E4 family of compute instances includes the industry’s largest bare metal option, with 128 OCPUs and 2TB of memory. Most enterprise applications can be run on a single AMD-based compute instance. Bare metal servers enable customers to run high performance, latency-sensitive, specialized, and traditional workloads directly on dedicated server hardware—just as they would on-premises. Bare metal instances are ideal for workloads that need to run in nonvirtualized environments. -
26
Shadeform
Shadeform
Shadeform is a GPU cloud marketplace that provides a single platform, unified console, and API for finding, comparing, launching, and managing on-demand GPU instances across numerous cloud providers, making it easier to develop, train, and deploy AI models without juggling multiple accounts or provider interfaces. It lets users view live pricing and availability for GPUs across clouds, launch instances in either their own cloud accounts or in Shadeform-managed accounts, and manage a cross-cloud fleet from one place with standardized tooling such as curl, Python, or Terraform. It aggregates GPU capacity and pricing data so teams can optimize compute spend, deploy containerized workloads with consistent interfaces, centralize billing and account management, and avoid vendor-specific complexity by using a unified API that supports multiple providers. Shadeform also offers scheduling and automated provisioning so that users can secure resources when they become available.Starting Price: $0.15 per hour -
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Anyscale
Anyscale
Anyscale is a unified AI platform built around Ray, the world’s leading AI compute engine, designed to help teams build, deploy, and scale AI and Python applications efficiently. The platform offers RayTurbo, an optimized version of Ray that delivers up to 4.5x faster data workloads, 6.1x cost savings on large language model inference, and up to 90% lower costs through elastic training and spot instances. Anyscale provides a seamless developer experience with integrated tools like VSCode and Jupyter, automated dependency management, and expert-built app templates. Deployment options are flexible, supporting public clouds, on-premises clusters, and Kubernetes environments. Anyscale Jobs and Services enable reliable production-grade batch processing and scalable web services with features like job queuing, retries, observability, and zero-downtime upgrades. Security and compliance are ensured with private data environments, auditing, access controls, and SOC 2 Type II attestation.Starting Price: $0.00006 per minute -
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Thunder Compute
Thunder Compute
Thunder Compute is a GPU cloud platform built for teams searching for cheap cloud GPUs without sacrificing performance, reliability, or ease of use. Developers, startups, and enterprises use Thunder Compute to launch H100, A100, and RTX A6000 GPU instances for AI training, LLM inference, fine-tuning, deep learning, PyTorch, CUDA, ComfyUI, Stable Diffusion, batch inference, and high-performance GPU workloads. With fast GPU provisioning, transparent pricing, persistent storage, and simple deployment, Thunder Compute makes cloud GPU hosting more accessible and cost-effective than traditional hyperscalers. Whether you need affordable GPUs for machine learning, a GPU server for AI, or a low-cost alternative to expensive GPU cloud providers, Thunder Compute helps you scale quickly with reliable on-demand GPU infrastructure designed for modern AI workloads. Thunder Compute is ideal for startups, ML engineers, and research teams that want cheap cloud GPUs with fast setup and predictable costs.Starting Price: $0.27 per hour -
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Amazon EC2 P5 Instances
Amazon
Amazon Elastic Compute Cloud (Amazon EC2) P5 instances, powered by NVIDIA H100 Tensor Core GPUs, and P5e and P5en instances powered by NVIDIA H200 Tensor Core GPUs deliver the highest performance in Amazon EC2 for deep learning and high-performance computing applications. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce the cost to train ML models by up to 40%. These instances help you iterate on your solutions at a faster pace and get to market more quickly. You can use P5, P5e, and P5en instances for training and deploying increasingly complex large language models and diffusion models powering the most demanding generative artificial intelligence applications. These applications include question-answering, code generation, video and image generation, and speech recognition. You can also use these instances to deploy demanding HPC applications at scale for pharmaceutical discovery. -
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Zesty
Zesty
Zesty’s cloud infrastructure optimization platform helps companies efficiently allocate resources and reduce cloud spend, with solutions for containers, compute, storage, and databases. Zesty Kompass automatically reduces K8s costs by up to 70% with no compromise on SLA. The platform enables nodes deployment in 30s, eliminating the need for node headroom, and expanding the confident usage of Spot Instances. Zesty Commitment Manager automatically optimizes EC2 and RDS discount plans, ensuring maximum coverage and deeper savings with minimal financial risk and no manual effort. Zesty Disk automatically scales up or down PVCs to match real-time application needs, optimizing storage utilization, eliminating the risk of downtime, and reducing costs by up to 70%. Zesty Insights provides a clear overview of potential savings and unused resources, and actionable recommendations that help you focus on the most efficient savings opportunities. -
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AceCloud
AceCloud
AceCloud is a comprehensive public cloud and cybersecurity platform designed to support businesses with scalable, secure, and high-performance infrastructure. Its public cloud services include compute options tailored for RAM-intensive, CPU-intensive, and spot instances, as well as cloud GPU offerings featuring NVIDIA A2, A30, A100, L4, L40S, RTX A6000, RTX 8000, and H100 GPUs. It provides Infrastructure as a Service (IaaS), enabling users to deploy virtual machines, storage, and networking resources on demand. Storage solutions encompass object storage, block storage, volume snapshots, and instance backups, ensuring data integrity and accessibility. AceCloud also offers managed Kubernetes services for container orchestration and supports private cloud deployments, including fully managed cloud, one-time deployment, hosted private cloud, and virtual private servers.Starting Price: $0.0073 per hour -
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HPE Ezmeral Data Fabric
Hewlett Packard Enterprise
Access HPE Ezmeral Data Fabric Software as a fully managed service. Register now for a 300GB instance to try out the latest features and capabilities. Increasingly enterprise data is being distributed across a growing number of locations while at the same time, the demand for insights continues to grow as users expect richer, high-quality data insights. Hybrid cloud solutions offer the best outcomes in terms of cost, data placement, workload control, and user experience. The upside of hybrid is the ability to better match applications with the appropriate services across the application lifecycle. The downside of hybrid is that it adds a new dimension of complexity such as limited data visibility, the need to use multiple analytic formats, and the potential for organizational risk and increased costs. -
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Amazon EC2 Auto Scaling
Amazon
Amazon EC2 Auto Scaling helps you maintain application availability and lets you automatically add or remove EC2 instances using scaling policies that you define. Dynamic or predictive scaling policies let you add or remove EC2 instance capacity to service established or real-time demand patterns. The fleet management features of Amazon EC2 Auto Scaling help maintain the health and availability of your fleet. Automation is vital to efficient DevOps, and getting your fleets of Amazon EC2 instances to launch, provision software, and self-heal automatically is a key challenge. Amazon EC2 Auto Scaling provides essential features for each of these instance lifecycle automation steps. Use machine learning to predict and schedule the right number of EC2 instances to anticipate approaching traffic changes. -
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Azure Virtual Machines
Microsoft
Migrate your business- and mission-critical workloads to Azure infrastructure and improve operational efficiency. Run SQL Server, SAP, Oracle® software and high-performance computing applications on Azure Virtual Machines. Choose your favorite Linux distribution or Windows Server. Deploy virtual machines featuring up to 416 vCPUs and 12 TB of memory. Get up to 3.7 million local storage IOPS per VM. Take advantage of up to 30 Gbps Ethernet and cloud’s first deployment of 200 Gbps InfiniBand. Select the underlying processors – AMD, Ampere (Arm-based), or Intel - that best meet your requirements. Encrypt sensitive data, protect VMs from malicious threats, secure network traffic, and meet regulatory and compliance requirements. Use Virtual Machine Scale Sets to build scalable applications. Reduce your cloud spend with Azure Spot Virtual Machines and reserved instances. Build your private cloud with Azure Dedicated Host. Run mission-critical applications in Azure to increase resiliency. -
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Segmind
Segmind
Segmind provides simplified access to large computing. You can use it to run your high-performance workloads such as Deep learning training or other complex processing jobs. Segmind offers zero-setup environments within minutes and lets your share access with your team members. Segmind's MLOps platform can also be used to manage deep learning projects end-to-end with integrated data storage and experiment tracking. ML engineers are not cloud engineers and cloud infrastructure management is a pain. So, we abstracted away all of it so that your ML team can focus on what they do best, and build models better and faster. Training ML/DL models take time and can get expensive quickly. But with Segmind, you can scale up your compute seamlessly while also reducing your costs by up to 70%, with our managed spot instances. ML managers today don't have a bird's eye view of ML development activities and cost.Starting Price: $5 -
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Amazon EC2 G4 Instances
Amazon
Amazon EC2 G4 instances are optimized for machine learning inference and graphics-intensive applications. It offers a choice between NVIDIA T4 GPUs (G4dn) and AMD Radeon Pro V520 GPUs (G4ad). G4dn instances combine NVIDIA T4 GPUs with custom Intel Cascade Lake CPUs, providing a balance of compute, memory, and networking resources. These instances are ideal for deploying machine learning models, video transcoding, game streaming, and graphics rendering. G4ad instances, featuring AMD Radeon Pro V520 GPUs and 2nd-generation AMD EPYC processors, deliver cost-effective solutions for graphics workloads. Both G4dn and G4ad instances support Amazon Elastic Inference, allowing users to attach low-cost GPU-powered inference acceleration to Amazon EC2 and reduce deep learning inference costs. They are available in various sizes to accommodate different performance needs and are integrated with AWS services such as Amazon SageMaker, Amazon ECS, and Amazon EKS. -
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Azure Virtual Machine Scale Sets
Microsoft
Build, on your terms, large-scale services for batch, big data, and container workloads using Azure Virtual Machine Scale Sets, which let you create and manage a group of heterogeneous load-balanced virtual machines (VMs). Increase or decrease the number of VMs automatically in response to demand or based on a schedule you define. Centrally manage, configure, and update thousands of VMs and provide higher availability and security for your applications. Increase application uptime by using availability zones and availability sets to automatically distribute VMs in a scale set within a single data center or across multiple data centers. Scale sets run multiple VM instances of your application. Therefore, if one of these instances has a problem, your customers will continue to access your application with minimal disruption. Virtual machine scale sets guarantee up to 99.99 percent service-level agreements (SLAs) for your VMs.Starting Price: $6.1320 per month -
38
Amazon EMR
Amazon
Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data using open-source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. With EMR you can run Petabyte-scale analysis at less than half of the cost of traditional on-premises solutions and over 3x faster than standard Apache Spark. For short-running jobs, you can spin up and spin down clusters and pay per second for the instances used. For long-running workloads, you can create highly available clusters that automatically scale to meet demand. If you have existing on-premises deployments of open-source tools such as Apache Spark and Apache Hive, you can also run EMR clusters on AWS Outposts. Analyze data using open-source ML frameworks such as Apache Spark MLlib, TensorFlow, and Apache MXNet. Connect to Amazon SageMaker Studio for large-scale model training, analysis, and reporting. -
39
Cloudxray
Cloudnosys
CloudXray is a cloud workload scanning solution that operates in two deployment modes; basic for misconfiguration detection and advanced for full malware, OS vulnerability, and misconfiguration scanning. The architecture consists of an orchestrator deployed in a single region and distributed scanners covering all discovered regions, making it fully compatible with both AWS and GCP environments. It uses an agentless approach to inspect workloads and volumes across your cloud account for malware, CVEs, and policy deviations. The solution provisions scanning instances on demand, integrates via roles and APIs, and provides continuous coverage of cloud resources without requiring persistent agents. CloudXray supports rapid deployment and is optimized for scalable, multi-region cloud workloads. It is designed to help organizations maintain a secure posture across compute instances, storage volumes, and OS layers by combining configuration assessment, vulnerability detection, and more. -
40
Massed Compute
Massed Compute
Massed Compute offers high-performance GPU computing solutions tailored for AI, machine learning, scientific simulations, and data analytics. As an NVIDIA Preferred Partner, it provides access to a comprehensive catalog of enterprise-grade NVIDIA GPUs, including A100, H100, L40, and A6000, ensuring optimal performance for various workloads. Users can choose between bare metal servers for maximum control and performance or on-demand compute instances for flexibility and scalability. Massed Compute's Inventory API allows seamless integration of GPU resources into existing business platforms, enabling provisioning, rebooting, and management of instances with ease. Massed Compute's infrastructure is housed in Tier III data centers, offering consistent uptime, advanced redundancy, and efficient cooling systems. With SOC 2 Type II compliance, the platform ensures high standards of security and data protection.Starting Price: $21.60 per hour -
41
Amazon EC2 UltraClusters
Amazon
Amazon EC2 UltraClusters enable you to scale to thousands of GPUs or purpose-built machine learning accelerators, such as AWS Trainium, providing on-demand access to supercomputing-class performance. They democratize supercomputing for ML, generative AI, and high-performance computing developers through a simple pay-as-you-go model without setup or maintenance costs. UltraClusters consist of thousands of accelerated EC2 instances co-located in a given AWS Availability Zone, interconnected using Elastic Fabric Adapter (EFA) networking in a petabit-scale nonblocking network. This architecture offers high-performance networking and access to Amazon FSx for Lustre, a fully managed shared storage built on a high-performance parallel file system, enabling rapid processing of massive datasets with sub-millisecond latencies. EC2 UltraClusters provide scale-out capabilities for distributed ML training and tightly coupled HPC workloads, reducing training times. -
42
Tencent Cloud Block Storage
Tencent
Tencent Cloud Cloud Block Storage (CBS) provides a persistent block storage service for CVM instances. The lifecycle of an Elastic Cloud Disk is independent of CVM instances. You can mount multiple cloud disks to a CVM instance and unmount them in order to mount them to another CVM instance. CBS offers cloud disks of multiple types and specifications to achieve stable and low-latency storage performance. CBS supports mounting and unmounting to instances in the same availability zone. You can use it to adjust storage capacity in minutes to satisfy elastic demands and pay for only what you use. When disk space becomes insufficient during use, you can purchase one or more cloud disks to satisfy storage capacity requirements. Purchase cloud disks to meet storage demands you did not plan for when buying the CVM instance. Store data on a cloud disk, unmount it, then mount it to another CVM instance to transfer data. -
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VESSL AI
VESSL AI
Build, train, and deploy models faster at scale with fully managed infrastructure, tools, and workflows. Deploy custom AI & LLMs on any infrastructure in seconds and scale inference with ease. Handle your most demanding tasks with batch job scheduling, only paying with per-second billing. Optimize costs with GPU usage, spot instances, and built-in automatic failover. Train with a single command with YAML, simplifying complex infrastructure setups. Automatically scale up workers during high traffic and scale down to zero during inactivity. Deploy cutting-edge models with persistent endpoints in a serverless environment, optimizing resource usage. Monitor system and inference metrics in real-time, including worker count, GPU utilization, latency, and throughput. Efficiently conduct A/B testing by splitting traffic among multiple models for evaluation.Starting Price: $100 + compute/month -
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Parquantix
Parquantix
Custom-tailored for AWS Partners and AWS Customers, Parquantix is one of the leading strategic partners for businesses looking to do the following: Monitor, analyze and optimize your AWS usage in real-time with our AI-driven tool to ensure an efficient AWS deployment at all times. Optimize cloud compute and database utilization through active procurement and management of reserved Instances and savings plans. Save up to 60% compared to on-demand rates with our AI-driven software. For qualified partners, we will pay the upfront fees for RIs and Savings Plans and amortize the cost over their lifetime. Keep RIs for only as long as needed, instead of being locked into 1 or 3-year contracts. Sell unused RIs in the AWS Marketplace and upgrade to latest generation instances for better price performance. Whether you are a technology company, online retailer or in media, you are overspending in the cloud without an automated optimization solution. -
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Apache Solr
Apache Software Foundation
Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites. Solr enables powerful matching capabilities including phrases, wildcards, joins, grouping and much more across any data type. Solr is proven at extremely large scales the world over. Solr uses the tools you use to make application building a snap. Solr ships with a built-in, responsive administrative user interface to make it easy to control your Solr instances. Need more insight into your instances? Solr publishes loads of metric data via JMX. Built on the battle-tested Apache Zookeeper, Solr makes it easy to scale up and down. Solr bakes in replication, distribution, rebalancing and fault tolerance out of the box. -
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Falcon Cloud Workload Protection
CrowdStrike
Falcon Cloud Workload Protection provides complete visibility into workload and container events and instance metadata enabling faster and more accurate detection, response, threat hunting and investigation, to ensure that nothing goes unseen in your cloud environment. Falcon Cloud Workload Protection secures your entire cloud-native stack, on any cloud, across all workloads, containers and Kubernetes applications. Automate security and detect and stop suspicious activity, zero-day attacks, risky behavior to stay ahead of threats and reduce the attack surface. Falcon Cloud Workload Protection key integrations support continuous integration/continuous delivery (CI/CD) workflows allowing you to secure workloads at the speed of DevOps without sacrificing performance -
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Akamai Cloud
Akamai
Akamai Cloud (formerly Linode) is the world’s most distributed cloud computing platform, designed to help businesses deploy low-latency, high-performance applications anywhere. It delivers GPU acceleration, managed Kubernetes, object storage, and compute instances optimized for AI, media, and SaaS workloads. With flat, predictable pricing and low egress fees, Akamai Cloud offers a transparent and cost-effective alternative to traditional hyperscalers. Its global infrastructure ensures faster response times, improved reliability, and data sovereignty across key regions. Developers can scale securely using Akamai’s firewall, database, and networking solutions, all managed through an intuitive interface or API. Backed by enterprise-grade support and compliance, Akamai Cloud empowers organizations to innovate confidently at the edge. -
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Yandex Cloud Functions
Yandex
Run code as a function in a secure, fault-tolerant, and automatically scalable environment without creating or maintaining VMs. As the number of function calls increases, the service automatically creates additional instances of your function. All functions run in parallel. The runtime environment is hosted in three availability zones, ensuring availability even if one zone fails. Configure and prepare instances of functions always ready to process loads. This mode allows you to avoid cold starts and quickly process loads of any size. Give functions access to your VPC to accelerate interactions with private resources, database clusters, virtual machines, Kubernetes nodes, etc. Serverless Functions tracks and logs information about function calls and analyzes execution flow and performance. You can also describe logging mechanisms in your function code. Launch cloud functions in synchronized mode and delayed execution mode.Starting Price: $0.012240 per GB -
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Elucidata Polly
Elucidata
Harness the power of biomedical data with Polly. The Polly Platform helps to scale batch jobs, workflows, coding environments and visualization applications. Polly allows resource pooling and provides optimal resource allocation based on your usage requirements and makes use of spot instances whenever possible. All this leads to optimization, efficiency, faster response time and lower costs for the resources. Get access to a dashboard to monitor resource usage and cost real time and minimize overhead of resource management by your IT team. Version control is integral to Polly’s infrastructure. Polly ensures version control for your workflows and analyses through a combination of dockers and interactive notebooks. We have built a mechanism that allows the data, code and the environment co-exist. This coupled with data storage on the cloud and the ability to share projects ensures reproducibility of every analysis you perform. -
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Amazon EC2 Inf1 Instances
Amazon
Amazon EC2 Inf1 instances are purpose-built to deliver high-performance and cost-effective machine learning inference. They provide up to 2.3 times higher throughput and up to 70% lower cost per inference compared to other Amazon EC2 instances. Powered by up to 16 AWS Inferentia chips, ML inference accelerators designed by AWS, Inf1 instances also feature 2nd generation Intel Xeon Scalable processors and offer up to 100 Gbps networking bandwidth to support large-scale ML applications. These instances are ideal for deploying applications such as search engines, recommendation systems, computer vision, speech recognition, natural language processing, personalization, and fraud detection. Developers can deploy their ML models on Inf1 instances using the AWS Neuron SDK, which integrates with popular ML frameworks like TensorFlow, PyTorch, and Apache MXNet, allowing for seamless migration with minimal code changes.Starting Price: $0.228 per hour
