Best Auto Scaling Software of 2025

Find and compare the best Auto Scaling software in 2025

Use the comparison tool below to compare the top Auto Scaling software on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Google Compute Engine Reviews

    Google Compute Engine

    Google

    Free ($300 in free credits)
    1,064 Ratings
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    The auto scaling capability of Google Compute Engine dynamically modifies the number of virtual machine instances based on varying traffic or workload requirements. This functionality guarantees that applications operate efficiently without the need for manual adjustments and minimizes costs by reducing resources when demand decreases. Users have the flexibility to set scaling guidelines according to particular metrics, like CPU usage or request frequency, allowing for tailored resource distribution. New users are also offered $300 in free credits, giving them the opportunity to experiment with and optimize auto scaling for their specific needs.
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    StarTree Reviews
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    StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.
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    RunPod Reviews

    RunPod

    RunPod

    $0.40 per hour
    113 Ratings
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    RunPod provides a cloud infrastructure that enables seamless deployment and scaling of AI workloads with GPU-powered pods. By offering access to a wide array of NVIDIA GPUs, such as the A100 and H100, RunPod supports training and deploying machine learning models with minimal latency and high performance. The platform emphasizes ease of use, allowing users to spin up pods in seconds and scale them dynamically to meet demand. With features like autoscaling, real-time analytics, and serverless scaling, RunPod is an ideal solution for startups, academic institutions, and enterprises seeking a flexible, powerful, and affordable platform for AI development and inference.
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    VMware Avi Load Balancer Reviews
    Streamline the process of application delivery by utilizing software-defined load balancers, web application firewalls, and container ingress services that can be deployed across any application in various data centers and cloud environments. Enhance management efficiency through unified policies and consistent operations across on-premises data centers as well as hybrid and public cloud platforms, which include VMware Cloud (such as VMC on AWS, OCVS, AVS, and GCVE), AWS, Azure, Google Cloud, and Oracle Cloud. Empower infrastructure teams by alleviating them from manual tasks and provide DevOps teams with self-service capabilities. The automation toolkits for application delivery encompass a variety of resources, including Python SDK, RESTful APIs, and integrations with Ansible and Terraform. Additionally, achieve unparalleled insights into network performance, user experience, and security through real-time application performance monitoring, closed-loop analytics, and advanced machine learning techniques that continuously enhance system efficiency. This holistic approach not only improves performance but also fosters a culture of agility and responsiveness within the organization.
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    AWS Auto Scaling Reviews
    AWS Auto Scaling continuously monitors your applications and adjusts resource capacity automatically to ensure consistent performance while minimizing costs. The platform allows for quick and straightforward application scaling across various resources and services in just a few minutes. It features an intuitive user interface that enables users to create scaling plans for a range of resources, including Amazon EC2 instances, Spot Fleets, Amazon ECS tasks, Amazon DynamoDB tables and indexes, as well as Amazon Aurora Replicas. By offering tailored recommendations, AWS Auto Scaling streamlines the process of optimizing performance and cost, or finding a balance between the two. Moreover, if you are utilizing Amazon EC2 Auto Scaling for your EC2 instances, you can seamlessly integrate it with AWS Auto Scaling to extend scalability to additional AWS services. This ensures that your applications are consistently equipped with the necessary resources precisely when they are needed. Ultimately, AWS Auto Scaling empowers developers to focus on building their applications rather than worrying about managing infrastructure demands.
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    StormForge Reviews
    StormForge drives immediate benefits for organization through its continuous Kubernetes workload rightsizing capabilities — leading to cost savings of 40-60% along with performance and reliability improvements across the entire estate. As a vertical rightsizing solution, Optimize Live is autonomous, tunable, and works seamlessly with the HPA at enterprise scale. Optimize Live addresses both over- and under-provisioned workloads by analyzing usage data with advanced ML algorithms to recommend optimal resource requests and limits. Recommendations can be deployed automatically on a flexible schedule, accounting for changes in traffic patterns or application resource requirements, ensuring that workloads are always right-sized, and freeing developers from the toil and cognitive load of infrastructure sizing.
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    CAST AI Reviews

    CAST AI

    CAST AI

    $200 per month
    CAST AI significantly reduces your compute costs with automated cost management and optimization. Within minutes, you can quickly optimize your GKE clusters thanks to real-time autoscaling up and down, rightsizing, spot instance automation, selection of most cost-efficient instances, and more. What you see is what you get – you can find out what your savings will look like with the Savings Report available in the free plan with K8s cost monitoring. Enabling the automation will deliver reported savings to you within minutes and keep the cluster optimized. The platform understands what your application needs at any given time and uses that to implement real-time changes for best cost and performance. It isn’t just a recommendation engine. CAST AI uses automation to reduce the operational costs of cloud services and enables you to focus on building great products instead of worrying about the cloud infrastructure. Companies that use CAST AI benefit from higher profit margins without any additional work thanks to the efficient use of engineering resources and greater control of cloud environments. As a direct result of optimization, CAST AI clients save an average of 63% on their Kubernetes cloud bills.
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    Pepperdata Reviews

    Pepperdata

    Pepperdata, Inc.

    Pepperdata autonomous, application-level cost optimization delivers 30-47% greater cost savings for data-intensive workloads such as Apache Spark on Amazon EMR and Amazon EKS with no application changes. Using patented algorithms, Pepperdata Capacity Optimizer autonomously optimizes CPU and memory in real time with no application code changes. Pepperdata automatically analyzes resource usage in real time, identifying where more work can be done, enabling the scheduler to add tasks to nodes with available resources and spin up new nodes only when existing nodes are fully utilized. The result: CPU and memory are autonomously and continuously optimized, without delay and without the need for recommendations to be applied, and the need for ongoing manual tuning is safely eliminated. Pepperdata pays for itself, immediately decreasing instance hours/waste, increasing Spark utilization, and freeing developers from manual tuning to focus on innovation.
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    Xosphere Reviews
    The Xosphere Instance Orchestrator enhances cost efficiency through automated spot optimization by utilizing AWS Spot instances, ensuring that the infrastructure remains as reliable as on-demand instances. By diversifying Spot instances across different families, sizes, and availability zones, it minimizes potential disruptions caused by the reclamation of these instances. Instances that are backed by reservations will not be substituted with Spot instances, preserving their intended use. Additionally, the system is designed to automatically respond to Spot termination notifications, allowing for expedited replacement of on-demand instances. Furthermore, EBS volumes can be configured to attach seamlessly to newly provisioned replacement instances, facilitating uninterrupted operation of stateful applications. This orchestration ensures a robust infrastructure while optimizing costs effectively.
  • 10
    Zerops Reviews
    Zerops.io serves as a cloud solution tailored for developers focused on creating contemporary applications, providing features such as automatic vertical and horizontal autoscaling, precise resource management, and freedom from vendor lock-in. The platform enhances infrastructure management through capabilities like automated backups, failover options, CI/CD integration, and comprehensive observability. Zerops.io adapts effortlessly to the evolving requirements of your project, guaranteeing maximum performance and cost-effectiveness throughout the development lifecycle, while also accommodating microservices and intricate architectures. It is particularly beneficial for developers seeking a combination of flexibility, scalability, and robust automation without the hassle of complex setups. This ensures a streamlined experience that empowers developers to focus on innovation rather than infrastructure.
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    Amazon EC2 Auto Scaling Reviews
    Amazon EC2 Auto Scaling ensures that your applications remain available by allowing for the automatic addition or removal of EC2 instances based on scaling policies that you set. By utilizing dynamic or predictive scaling policies, you can adjust the capacity of EC2 instances to meet both historical and real-time demand fluctuations. The fleet management capabilities within Amazon EC2 Auto Scaling are designed to sustain the health and availability of your instance fleet effectively. In the realm of efficient DevOps, automation plays a crucial role, and one of the primary challenges lies in ensuring that your fleets of Amazon EC2 instances can automatically launch, provision software, and recover from failures. Amazon EC2 Auto Scaling offers vital functionalities for each phase of instance lifecycle automation. Furthermore, employing machine learning algorithms can aid in forecasting and optimizing the number of EC2 instances needed to proactively manage anticipated changes in traffic patterns. By leveraging these advanced features, organizations can enhance their operational efficiency and responsiveness to varying workload demands.
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    UbiOps Reviews
    UbiOps serves as a robust AI infrastructure platform designed to enable teams to efficiently execute their AI and ML workloads as dependable and secure microservices, all while maintaining their current workflows. In just a few minutes, you can integrate UbiOps effortlessly into your data science environment, thereby eliminating the tedious task of establishing and overseeing costly cloud infrastructure. Whether you're a start-up aiming to develop an AI product or part of a larger organization's data science unit, UbiOps provides a solid foundation for any AI or ML service you wish to implement. The platform allows you to scale your AI workloads in response to usage patterns, ensuring you only pay for what you use without incurring costs for time spent idle. Additionally, it accelerates both model training and inference by offering immediate access to powerful GPUs, complemented by serverless, multi-cloud workload distribution that enhances operational efficiency. By choosing UbiOps, teams can focus on innovation rather than infrastructure management, paving the way for groundbreaking AI solutions.
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    Syself Reviews

    Syself

    Syself

    €299/month
    No expertise required! Our Kubernetes Management platform allows you to create clusters in minutes. Every feature of our platform has been designed to automate DevOps. We ensure that every component is tightly interconnected by building everything from scratch. This allows us to achieve the best performance and reduce complexity. Syself Autopilot supports declarative configurations. This is an approach where configuration files are used to define the desired states of your infrastructure and application. Instead of issuing commands that change the current state, the system will automatically make the necessary adjustments in order to achieve the desired state.
  • 14
    Lucidity Reviews
    Lucidity serves as a versatile multi-cloud storage management solution, adept at dynamically adjusting block storage across major platforms like AWS, Azure, and Google Cloud while ensuring zero downtime, which can lead to savings of up to 70% on storage expenses. This innovative platform automates the process of resizing storage volumes in response to real-time data demands, maintaining optimal disk usage levels between 75-80%. Additionally, Lucidity is designed to function independently of specific applications, integrating effortlessly into existing systems without necessitating code alterations or manual provisioning. The AutoScaler feature of Lucidity, accessible via the AWS Marketplace, provides businesses with an automated method to manage live EBS volumes, allowing for expansion or reduction based on workload requirements, all without any interruptions. By enhancing operational efficiency, Lucidity empowers IT and DevOps teams to recover countless hours of work, which can then be redirected towards more impactful projects that foster innovation and improve overall effectiveness. This capability ultimately positions enterprises to better adapt to changing storage needs and optimize resource utilization.
  • 15
    Alibaba Auto Scaling Reviews
    Auto Scaling is a service designed to dynamically modify computing resources in response to the fluctuation of user requests. As demand rises for computing power, Auto Scaling seamlessly incorporates additional ECS instances to accommodate the surge in user activity, while also removing instances when there is a decline in requests. It adjusts resources automatically based on a variety of scaling policies, and it also allows for manual scaling, giving users the option to control resources as needed. In times of high demand, it ensures that extra computing resources are added to the available pool. Conversely, when there is a reduction in user requests, Auto Scaling effectively releases ECS resources, helping to minimize costs. This service plays a crucial role in optimizing resource management and enhancing operational efficiency.
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Overview of Auto Scaling Software

Auto scaling software is a type of application that monitors and adjusts the resources of an application or server in order to optimize performance. It's typically used in computing environments such as cloud computing, hosting, or distributed applications, where the need for consistent and reliable performance is high.

Auto scaling helps organizations adjust their system resources on-the-fly as required to ensure that they're always running optimally in terms of cost and performance. This type of software can automatically scale up (add more servers) or down (remove servers) based on conditions such as availability, traffic volumes, and other factors. Auto scaling works by using metrics from your environment to optimize the deployment and configuration of cloud services.

One way auto scaling works is through predictive analysis. It uses algorithms to anticipate future usage patterns based on historical data and provide preemptive resource allocation and optimization solutions accordingly. Additionally, with auto scaling you can create automation rules which will automatically respond to pre-defined thresholds like CPU usage or memory utilization allowing for quick response times without manual intervention.

The main benefit of auto scaling is that it lets you have an elastic approach when dealing with system resource requirements since you don't need to manually size your resources ahead of time based on making assumptions about future needs. Instead, you can deploy additional resources when needed without having to go through a manual provisioning process every time there’s an increase in demand. As a result, this saves money by avoiding overprovisioning while at the same time providing good performance levels since no matter how much traffic comes into your system it will always be able to deliver excellent user experience due to its ability to quickly adjust according to the changing needs.

Auto scaling is an essential tool for any organization that needs to maintain a high level of performance and availability while keeping costs low. With its ability to quickly adjust resources in response to changing demands, it can help organizations reduce costs as well as provide users with better service. This makes it an invaluable tool for any company looking to optimize their operations and ensure peak performance in the face of variable workloads.

Why Use Auto Scaling Software?

  1. Cost Savings: Auto scaling software can be used to automatically scale up or down the amount of computing resources consumed according to the needs of an application, allowing businesses to save costs by only consuming the resources when needed.
  2. Efficiency and Agility: Auto scaling software allows applications to instantly adapt and adjust their resource consumption in real-time according to workloads or user demands, providing flexibility and scalability for applications that may require more power at certain points in time without manual intervention from a technician.
  3. Improved Reliability: By utilizing auto scaling, application performance is optimized as resources are added or removed according to current demand. This prevents any single server from becoming overloaded with requests due to unexpected spikes in usage which could result in downtime and reliability issues for users accessing the application.
  4. Simplified Maintenance: With auto scaling software determining when extra computing power is required, teams no longer have to manually allocate additional servers for peak periods of usage, removing manual labor intensive steps from maintenance tasks which simplifies development processes and makes it easier for systems administrators manage their infrastructure during unpredictable traffic loads or surges in data requests.

Why Is Auto Scaling Software Important?

Auto scaling software is an important tool for businesses of all sizes. It allows organizations to quickly and easily adjust their IT infrastructure in response to changing demands, helping them remain competitive in an ever-evolving digitally driven world.

The most common application of auto scaling software is its ability to scale up or down from the existing capacity of the computing resources based on certain triggers or conditions. This allows companies to add resources only when needed and remove them when they become unnecessary. Doing so helps businesses reduce costs by allowing them to allocate resources where they are most needed and minimize the use of excess capacity that incurs higher costs and leads to greater waste.

In addition, auto scaling can help companies respond quickly during unexpected spikes in demand due to business events such as promotions, product launches, or customer influxes. By automatically adjusting their computing resources according to changes in demand, organizations can ensure that customers always have access to the services they need and avoid disruptions caused by slow loading times or unresponsive websites.

Finally, auto scaling offers a more sustainable way of running cloud applications since it works together with other cloud services like virtualization solutions and load balancers that allow users to increase scalability without having make major investments upfront into infrastructure hardware or architecture upgrades. This gives organizations better control over their IT expenses while still being able to maintain peak performance levels whenever necessary.

In summary, auto scaling software is an important tool for businesses of all sizes due to its ability to quickly and easily adjust their IT infrastructure in response to changing demands, helping them become more agile and competitive organizations. It also helps them reduce costs by only using the computing resources they need when needed while maintaining scalability without making large upfront investments.

What Features Does Auto Scaling Software Provide?

  1. Automated Scaling: This feature allows auto scaling software to automatically scale up or down a virtual server's resources in reaction to changes in network traffic or application performance. It ensures that the right amount of resources is available at all times for maximum efficiency and cost savings, allowing applications to stay online even during times of high demand.
  2. Elastic Load Balancing: Auto scaling software can also include an elastic load balancer which distributes incoming requests across multiple virtual servers, ensuring that each server only handles as much load as it can manage without overloading. This helps keep performance levels stable while optimizing resource usage and minimizing response time for end users.
  3. Metric Collection: The auto scaling software will collect metrics from the hosted applications such as memory and CPU usage, network bandwidth consumption, etc., allowing DevOps teams to quickly identify any performance issues or spikes in demand before they become a problem.
  4. Health Check Service: Auto scaling solutions provide a health check service which monitors the status of individual virtual servers on your infrastructure and notifies administrators if any become unhealthy due to errors or downtime so corrective action can be taken quickly before it affects user experience on the platform.
  5. Resource Scheduling: Auto scaling software also includes scheduling capabilities which allow administrators to define periodic events such as when resources should ramp up or down depending on expected traffic patterns over time. This helps free up capacity when it is no longer needed while ensuring enough capacity is ready when needed most by users.
  6. Customizable Thresholds: Auto scaling software lets you customize the thresholds at which resources are scaled up or down, allowing administrators to adjust them to match their application’s specific performance requirements in order to maintain peak performance and avoid downtime.

What Types of Users Can Benefit From Auto Scaling Software?

  • Developer Teams: Auto scaling software allows developers to quickly deploy applications across multiple cloud environments and scale them up or down based on demand, eliminating the need for manual intervention.
  • System Administrators: System administrators can use auto scaling software to automate routine tasks such as server provisioning, patching, deployment of new applications or services, and more.
  • DevOps Professionals: Auto scaling makes it easier for DevOps professionals to detect and respond to urgent changes in workloads without having to manually adjust the settings every time. It also enables them to optimize capacity resources while reducing operation costs.
  • Business Owners: Automated scaling solutions provide business owners with an efficient way of managing their IT infrastructure and ensuring high availability of applications at all times - all while keeping operational costs low.
  • Cloud Providers: Auto scaling software helps cloud providers accommodate varying levels of customer demands by providing a fully automated solution that scales computing resources accordingly. This helps providers offer better performance and cost savings to their customers.

How Much Does Auto Scaling Software Cost?

The cost of auto scaling software depends on a variety of factors, such as the size of the user's organization, the number of users, range and complexity of functionality needed, etc. Prices can range from free at the lower end for open source or community supported auto-scaling software to tens or even hundreds of thousands of dollars for enterprise grade solutions with extensive features. Generally speaking, businesses tend to opt for more expensive enterprise grade solutions if scalability is an essential requirement and resources available are not restricted. The exact cost will also depend on how many users you plan to support, cloud hosting vendor being used (if applicable), any customization needed and whether you require advanced features like multi-region deployments that may add up costs. Moreover most vendors offer pricing per request or instance rather than a one-time license fee, which can make it difficult to estimate total costs in advance. For these reasons it's important that you speak with your provider directly in order to get a good understanding about how much their solution will cost you.

Risks To Consider With Auto Scaling Software

  • Cost: Auto scaling software can be expensive to set up and maintain. Additionally, there may be additional charges if the system needs to scale up beyond its initial capacity, or if you need access to additional features or resources.
  • Security: The security of an auto scaling system depends on how well it is configured in order to ensure that only the right users can access the sensitive data. If not properly configured, then malicious actors could gain unauthorized access to your infrastructure.
  • Downtime: A poorly designed auto scaling system can cause unexpected downtime when scaling up or down due to incorrectly configured thresholds or issues with the hardware or software. Moreover, this could lead to lost revenue and customer dissatisfaction.
  • Configuration Errors: If there are mistakes made during configuration, such as incorrect settings for thresholds, then this could result in an inefficient auto scaling process that will cost you more in cloud computing costs than necessary.
  • Complexity: As a complex system, setting up an auto scaling software requires tech savvy personnel who understand how all of the components work together and have experience troubleshooting any problems that arise from misconfiguration errors or unforeseen use cases.

What Does Auto Scaling Software Integrate With?

Auto scaling software can integrate with multiple types of software to enhance its capabilities. This includes monitoring and alerting services, such as Nagios and Zabbix, which provide real-time alerts about system performance so that auto scaling can respond quickly to changes in the environment. Database systems can be used in conjunction with auto scaling software to ensure access to large datasets without downtimes when scaling up or down. Load balancers can help maintain service stability by automatically distributing requests across multiple instances when the number of incoming connections increases beyond a certain threshold. Finally, management and automation tools enable automated deployment and configuration of servers for auto scaling purposes.

Questions To Ask Related To Auto Scaling Software

  1. Does the auto scaling software integrate with other essential IT systems and services, such as monitoring tools, orchestration software, or virtualization solutions?
  2. How quickly can the system scale up and down in response to changing workloads?
  3. Does the auto scaling solution provide insight into usage trends so that you can optimize resource allocation over time?
  4. What are the setup requirements for using the auto scaling software? Is it easy to install and configure?
  5. Does the auto scaling software offer predictive capabilities that allow you to predict potential increases or decreases in customer demand in order to proactively adjust resources accordingly?
  6. Are there any artificial intelligence features within the software that can help reduce manual intervention when adjusting resources based on user demand or activity patterns?
  7. What type of support does the provider offer with their auto-scaling solution (e.g., phone, chat, email)? Are there additional fees for certain levels of technical support?
  8. Does the auto-scaling solution have built-in security features such as identity management and authentication, encryption, and role-based access control?
  9. What types of analytics are available with the auto scaling software, if any? can you track key performance indicators (KPIs), generate reports, or get real-time insights into system activity?
  10. Are there any additional costs for additional features or services with the auto scaling solution?