Compare the Top Free Auto Scaling Software as of August 2025

What is Free Auto Scaling Software?

Auto scaling software helps to optimize the performance of cloud applications. It works by automatically increasing or decreasing the number of underlying resources such as virtual machines, server capacity and storage upon detecting changes in workloads. It allows applications to dynamically scale up or down depending on traffic patterns while keeping costs minimized. Auto scaling is particularly useful when there are predictable changes in application demand over time and for applications with negative elasticity, where additional load can cause a decrease in performance. It has become an essential tool for many organizations utilizing cloud service platforms due to its ability to manage application availability, scalability and performance. Compare and read user reviews of the best Free Auto Scaling software currently available using the table below. This list is updated regularly.

  • 1
    Google Compute Engine
    Google Compute Engine's auto scaling feature automatically adjusts the number of virtual machine instances in response to fluctuations in traffic or workload demands. This ensures that applications maintain optimal performance without manual intervention and helps to reduce unnecessary costs by scaling down when demand is low. Users can configure scaling policies based on specific criteria, such as CPU utilization or request rate, to further customize how resources are allocated. New customers receive $300 in free credits, enabling them to test and fine-tune auto scaling for their unique workloads.
    Starting Price: Free ($300 in free credits)
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  • 2
    StarTree

    StarTree

    StarTree

    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. • Gain critical real-time insights to run your business • Seamlessly integrate data streaming and batch data • High performance in throughput and low-latency at petabyte scale • Fully-managed cloud service • Tiered storage to optimize cloud performance & spend • Fully-secure & enterprise-ready
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  • 3
    AWS Auto Scaling
    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.
  • 4
    StormForge

    StormForge

    StormForge

    StormForge Optimize Live continuously rightsizes Kubernetes workloads to ensure cloud-native applications are both cost effective and performant while removing developer toil. As a vertical rightsizing solution, Optimize Live is autonomous, tunable, and works seamlessly with the Kubernetes horizontal pod autoscaler (HPA) at enterprise scale. Optimize Live addresses both over- and under-provisioned workloads by analyzing usage data with advanced machine learning 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. Organizations see immediate benefits from the reduction of wasted resources — leading to cost savings of 40-60% along with performance and reliability improvements across the entire estate.
    Starting Price: Free
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