# Best Auto Scaling Software

## How Many Auto Scaling Software Products Does G2 Track?

**Total Products under this Category:** 19

### Category Stats (Aug 2026)

- **Average Rating:** 4.55/5 The average rating of products in this category, based on all submitted ratings

_Last updated: August 01, 2026_

## How Does G2 Rank Auto Scaling Software Products?

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 1,600+ Authentic Reviews
- 19+ Products
- Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

## G2 Grid® for Auto Scaling Software
 ![G2 Grid® for Auto Scaling Software plotting products by satisfaction and market presence](https://www.g2.com/categories/auto-scaling/grids.png?focus%5B%5D=6599&focus%5B%5D=136001&focus%5B%5D=20186&focus%5B%5D=1386881&focus%5B%5D=67005&focus%5B%5D=70656&focus%5B%5D=145092)

Highlighted products: Google Compute Engine, Cast AI, AWS Auto Scaling, ScaleOps, Amazon EC2 Auto Scaling, Pepperdata Capacity Optimizer, and Xosphere Instance Orchestrator.

Underlying data: [Grid® JSON](https://www.g2.com/categories/auto-scaling/grids.json?focus%5B%5D=google-compute-engine&focus%5B%5D=cast-ai&focus%5B%5D=aws-auto-scaling&focus%5B%5D=scaleops-cloud-native-optimization-scaleops&focus%5B%5D=amazon-ec2-auto-scaling&focus%5B%5D=pepperdata-capacity-optimizer&focus%5B%5D=xosphere-instance-orchestrator)

**Sponsored**

### Google Compute Engine

Compute Engine is Google's infrastructure as a service (IaaS) platform for organizations to create and run cloud-based virtual machines.

[Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list_llm&secure%5Bcategory_id%5D=1004993&secure%5Bchosen_at%5D=2026-08-02T12%3A34%3A07Z&secure%5Bdisplayable_resource_id%5D=1004993&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1004993&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=6599&secure%5Bresource_id%5D=1004993&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fauto-scaling%3Fopen_modal_url%3D%252Fproducts%252Freal-time-technology-solutions%252Fwishlists%253Fhost_path%253D%25252Fcategories%25252Fauto-scaling%2526source%253Dcategory&secure%5Btoken%5D=25611d8dc363b166a7aa7f60d2f133a33fb4290c83a768b84cc2ce1cd1f81f3c&secure%5Burl%5D=https%3A%2F%2Fcloud.google.com%2Fspeech-to-text%3Futm_source%3DG2%26utm_medium%3Ddisplay%26utm_campaign%3DCloud-SS-DR-GCP-1713658-GCP-DR-NA-US-en-G2-Display-Banner-All-%2525epid%21-%2525ecid%21-speechtotext%26utm_content%3D%257Bdevice%257D-%257Badgroupid%257D-%257Bnetwork%257D-%257Btargetid%257D-%257Bloc_physical_ms%257D-%257Bcampaignid%257D&secure%5Burl_type%5D=custom_url)

### [Google Compute Engine](https://www.g2.com/products/google-compute-engine/reviews)

Compute Engine is Google's infrastructure as a service (IaaS) platform for organizations to create and run cloud-based virtual machines.

**Average Rating:** 4.5/5.0

**Total Reviews:** 875

#### How Do G2 Users Rate Google Compute Engine?

- **Ease of Admin:** 8.6/10 (Category avg: 9.1/10)

#### Who Is the Company Behind Google Compute Engine?

- **Seller:** [Google](https://www.g2.com/sellers/google)
- **Year Founded:** 1998
- **HQ Location:** Mountain View, CA
- **Twitter:** @google  
31,899,995 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fe4a5936665c9702418dd53c477fef5a7baea08078bb117ed67e966fc581b9ec&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1441%2F&secure%5Burl_type%5D=linkedin_company_website)  
341,888 employees on LinkedIn®
- **Ownership:** NASDAQ:GOOG

#### Who Uses This Product?

- **Who Uses This:** Software Engineer, Data Engineer
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 35% Small, 34% Large

#### What Do G2 Reviewers Say About Google Compute Engine?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of Google Compute Engine, enabling quick VM provisioning and seamless integration with GCP products.
- Users love the **scalability** of Google Compute Engine, allowing quick adjustments to resources for varying workloads.
- Users value the **flexibility and scalability** of Google Compute Engine, making it easy to customize VMs for various needs.
- Users admire the **flexibility and scalability** of Google Compute Engine, allowing customized and efficient cloud resource management.
- Users appreciate the **scalability and flexibility** of Google Compute Engine, enabling quick and reliable virtual machine provisioning.

##### Cons

- Users struggle with the **complex pricing structure** of Google Compute Engine, leading to unexpected costs and confusion.
- Users find the **pricing structure confusing** and potentially expensive, especially when scaling multiple instances without careful monitoring.
- Users find the **cost management** challenging, noting confusion over pricing and potential for quickly rising costs.
- Users find the **steep learning curve** of Google Compute Engine daunting, especially for beginners unfamiliar with cloud concepts.
- Users find the **complex pricing structure** of Google Compute Engine challenging, often leading to unexpected costs and confusion.

#### What Are Recent G2 Reviews of Google Compute Engine?

**["My experience using GCE"](https://www.g2.com/survey_responses/google-compute-engine-review-11677030)**

**Rating:** 5.0/5.0 stars

_— ANUJ J._

[Read full review](https://www.g2.com/survey_responses/google-compute-engine-review-11677030)

**["Easy Setup, Flexible Instances, and Great Value on Google Compute Engine"](https://www.g2.com/survey_responses/google-compute-engine-review-12691758)**

**Rating:** 5.0/5.0 stars

_— Matthew C._

[Read full review](https://www.g2.com/survey_responses/google-compute-engine-review-12691758)

#### What Are G2 Users Discussing About Google Compute Engine?

- [What is Google Compute Engine used for?](https://www.g2.com/discussions/what-is-google-compute-engine-used-for) - 2 comments
- [What is a compute instance?](https://www.g2.com/discussions/what-is-a-compute-instance) - 2 comments, 2 upvotes
- [Is Google Compute Engine PaaS?](https://www.g2.com/discussions/is-google-compute-engine-paas) - 1 comment, 1 upvote
- [What are the features of Compute Engine?](https://www.g2.com/discussions/what-are-the-features-of-compute-engine)
- [What does Google Compute Engine do?](https://www.g2.com/discussions/what-does-google-compute-engine-do) - 4 comments, 1 upvote

### [Cast AI](https://www.g2.com/products/cast-ai/reviews)

Cast AI is an automation platform for operating cloud-native and AI infrastructure at scale. It keeps applications fast and stable by continuously optimizing production systems and eliminating manual operations as environments scale.

**Average Rating:** 4.6/5.0

**Total Reviews:** 194

#### How Do G2 Users Rate Cast AI?

- **Ease of Admin:** 9.1/10 (Category avg: 9.1/10)

#### Who Is the Company Behind Cast AI?

- **Seller:** [Cast AI](https://www.g2.com/sellers/cast-ai)
- **Company Website:** cast.ai
- **Year Founded:** 2019
- **HQ Location:** Miami, FL
- **Twitter:** @cast\_ai  
1,826 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=b990abefe06f5b3a16e017d6d0604856349863351a00b955116637b9661f74ff&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fcast-ai&secure%5Burl_type%5D=linkedin_company_website)  
340 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** DevOps Engineer, Senior DevOps Engineer
- **Top Industries:** Financial Services, Information Technology and Services
- **Company Size:** 42% Medium, 23% Large

#### What Do G2 Reviewers Say About Cast AI?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **cost management capabilities** of CAST AI, effectively reducing cluster costs and avoiding interruptions.
- Users value the **cost-saving benefits** of CAST AI, significantly reducing cloud expenses while optimizing Kubernetes management.
- Users value the **ease of use** of CAST AI, finding it straightforward to set up and operate effectively.
- Users highlight the **significant cost reduction** achieved with CAST AI through autonomous optimization and intelligent resource management.
- Users value the **cost-effectiveness** of CAST AI for managing clusters and optimizing expenses effortlessly.

##### Cons

- Users face **scaling issues** with CAST AI when dealing with bursty workloads, affecting performance and budget management.
- Users find the **pricing high** , especially for small clusters, despite the tool paying for itself initially.
- Users face a **substantial learning curve** with advanced features, requiring time to understand and utilize effectively.
- Users report **poor documentation** leading to confusion and contradictory information from support, complicating their experience.
- Users find **pricing issues** with CAST AI, highlighting a need for improved clarity and transparency in cost reporting.

#### What Are Recent G2 Reviews of Cast AI?

**["A Powerful Platform for Reducing Kubernetes Cloud Costs"](https://www.g2.com/survey_responses/cast-ai-review-13181004)**

**Rating:** 4.0/5.0 stars

_— Jeni J._

[Read full review](https://www.g2.com/survey_responses/cast-ai-review-13181004)

**["Set-and-Forget Kubernetes Autoscaling With Major Cloud Cost Savings"](https://www.g2.com/survey_responses/cast-ai-review-13181645)**

**Rating:** 4.0/5.0 stars

_— Arjun D._

[Read full review](https://www.g2.com/survey_responses/cast-ai-review-13181645)

#### What Are G2 Users Discussing About Cast AI?

- [What is CAST AI used for?](https://www.g2.com/discussions/what-is-cast-ai-used-for) - 1 comment, 1 upvote

### [AWS Auto Scaling](https://www.g2.com/products/aws-auto-scaling/reviews)

Amazon EC2 Auto Scaling helps you maintain application availability and allows you to dynamically scale your Amazon EC2 capacity up or down automatically according to conditions you define. You can use Amazon EC2 Auto Scaling for fleet management of EC2 instances to help maintain the health and availability of your fleet and ensure that you are running your desired number of Amazon EC2 instances. You can also use Amazon EC2 Auto Scaling for dynamic scaling of EC2 instances in order to automatically increase the number of Amazon EC2 instances during demand spikes to maintain performance and decrease capacity during lulls to reduce costs. Amazon EC2 Auto Scaling is well suited both to applications that have stable demand patterns or that experience hourly, daily, or weekly variability in usage.

**Average Rating:** 4.5/5.0

**Total Reviews:** 230

#### How Do G2 Users Rate AWS Auto Scaling?

- **Ease of Admin:** 8.9/10 (Category avg: 9.1/10)

#### Who Is the Company Behind AWS Auto Scaling?

- **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd)
- **Year Founded:** 2006
- **HQ Location:** Seattle, WA
- **Twitter:** @awscloud  
2,232,483 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=072881eee28a2afe24f8d1bda9f20e3e146b9fb4b214f216411ce2ed6898b31e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Famazon-web-services%2F&secure%5Burl_type%5D=linkedin_company_website)  
147,094 employees on LinkedIn®
- **Ownership:** NASDAQ: AMZN

#### Who Uses This Product?

- **Who Uses This:** Software Engineer, DevOps Engineer
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 40% Large, 35% Medium

#### What Do G2 Reviewers Say About AWS Auto Scaling?

_AI-generated summary from verified user reviews_

##### Pros

- Users find AWS Auto Scaling offers **cost efficiency and reliable elasticity** , effectively managing server capacity during traffic fluctuations.
- Users value the **seamless scalability** of AWS Auto Scaling, optimizing costs while maintaining performance during demand fluctuations.
- Users value the **cost-effective scaling** of AWS Auto Scaling, ensuring optimal resource use and minimizing expenses.
- Users appreciate the **unified management interface** of AWS Auto Scaling for streamlined resource management across services.
- Users value the **automated resource management** of AWS Auto Scaling, ensuring optimal performance during varying traffic conditions.

##### Cons

- Users experience **scaling issues** due to configuration complexity and delays in instance initialization affecting performance during traffic spikes.
- Users find the **complex configuration** of AWS Auto Scaling overwhelming, requiring expertise and ongoing adjustments for optimal setup.
- Users find the **difficulty in usage** of AWS Auto Scaling challenging, especially during initial setup and configuration.
- Users experience **slow performance** with AWS Auto Scaling, requiring manual intervention for issues like high CPU usage.
- Users find the **configuration complexity** of AWS Auto Scaling daunting, requiring extensive knowledge and continuous adjustments.

#### What Are Recent G2 Reviews of AWS Auto Scaling?

**["Effortless Performance and Cost Optimization with AWS Auto Scaling"](https://www.g2.com/survey_responses/aws-auto-scaling-review-12719854)**

**Rating:** 4.0/5.0 stars

_— Ruby G._

[Read full review](https://www.g2.com/survey_responses/aws-auto-scaling-review-12719854)

**["Effortlessly Manages Traffic Spikes with AWS Auto Scaling"](https://www.g2.com/survey_responses/aws-auto-scaling-review-12030712)**

**Rating:** 4.5/5.0 stars

_— aswath k._

[Read full review](https://www.g2.com/survey_responses/aws-auto-scaling-review-12030712)

#### What Are G2 Users Discussing About AWS Auto Scaling?

- [What is AWS Auto Scaling used for?](https://www.g2.com/discussions/what-is-aws-auto-scaling-used-for)
- [What are the two main components of AWS Auto Scaling?](https://www.g2.com/discussions/aws-auto-scaling-what-are-the-two-main-components-of-aws-auto-scaling) - 1 comment
- [Which of the following auto scaling can do using AWS?](https://www.g2.com/discussions/which-of-the-following-auto-scaling-can-do-using-aws)
- [Which AWS services may be scaled using AWS Auto Scaling?](https://www.g2.com/discussions/which-aws-services-may-be-scaled-using-aws-auto-scaling) - 1 comment
- [What is AWS Auto Scaling?](https://www.g2.com/discussions/what-is-aws-auto-scaling)

### [ScaleOps](https://www.g2.com/products/scaleops-cloud-native-optimization-scaleops/reviews)

ScaleOps is a cloud resource management platform designed to automate resource optimization in real-time based on application context-awareness. This innovative solution continuously monitors live application behavior and dynamically adjusts Kubernetes workload resources according to actual usage and contextual demands. By leveraging ScaleOps, organizations can achieve significant cost reductions, of up to 80%, while ensuring that availability, performance, and compliance with production constraints are maintained. The primary target audience for ScaleOps includes DevOps teams, cloud architects, and IT administrators who manage Kubernetes environments. These professionals often face challenges related to resource allocation, cost management, and application performance. ScaleOps addresses these issues by providing a solution that operates autonomously, eliminating the need for manual intervention or code modifications. This allows teams to focus on higher-level strategic initiatives rather than getting bogged down in the minutiae of resource management. Key features of ScaleOps include automated pod-level resource management, which encompasses CPU, memory, replicas, and scheduling. This capability allows the platform to adapt in real-time to the changing behavior of workloads, ensuring optimal resource utilization. Additionally, ScaleOps employs application context-aware optimization, taking into account factors such as burstiness, Pod Disruption Budgets (PDBs), statefulness, and the presence of noisy neighbors. This level of sophistication enables organizations to maintain performance and availability even in complex environments. ScaleOps also offers flexible deployment options, making it suitable for various infrastructures, including air-gapped, on-premises, hybrid, and cloud-native environments. Its compatibility with existing Kubernetes scaling tools, such as Horizontal Pod Autoscaler (HPA), KEDA, and Karpenter, allows for a gradual rollout without disrupting current systems. Furthermore, the platform provides granular policy control, enabling teams to define performance, cost, or availability priorities at the namespace, workload, or environment level. This feature empowers organizations to tailor their resource management strategies to meet specific operational goals and constraints. By integrating seamlessly into existing workflows and providing continuous, context-aware resource optimization, ScaleOps stands out as a comprehensive solution for organizations looking to enhance their Kubernetes resource management. Its unique approach not only drives cost efficiency but also ensures that applications run smoothly and reliably, regardless of the underlying infrastructure.

**Average Rating:** 4.6/5.0

**Total Reviews:** 96

#### How Do G2 Users Rate ScaleOps?

- **Ease of Admin:** 8.9/10 (Category avg: 9.1/10)

#### Who Is the Company Behind ScaleOps?

- **Seller:** [ScaleOps - Cloud-Native Optimization](https://www.g2.com/sellers/scaleops-cloud-native-optimization)
- **Company Website:** scaleops.com
- **Year Founded:** 2022
- **HQ Location:** New York, US
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=c8f87063552faa18534f329837bdc6e777241445c98241c22a53dd58979d6baf&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fscaleops-sh&secure%5Burl_type%5D=linkedin_company_website)  
140 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** DevOps Engineer
- **Top Industries:** Computer Software, Financial Services
- **Company Size:** 53% Medium, 36% Large

#### What Do G2 Reviewers Say About ScaleOps?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **exceptional customer support** from ScaleOps, enhancing their satisfaction and experience with the product.
- Users appreciate the **ease of use** of ScaleOps, simplifying installation and enhancing workflow management effectively.
- Users experience significant **cost savings of 30-40%** with ScaleOps, enhancing efficiency and reducing infrastructure expenses.
- Users highlight the **substantial cost savings** achieved with ScaleOps, reducing infrastructure costs by 30-40% effectively.
- Users appreciate the **easy setup** of ScaleOps, facilitating quick integration and efficient management of workloads.

##### Cons

- Users face **scaling issues** with ScaleOps, especially in large clusters, affecting efficiency and support interactions.
- Users experience **slow performance** with ScaleOps, particularly in large environments, impacting trust and usability.
- Users face **difficulty in usage** with ScaleOps due to onboarding challenges, a non-intuitive UI, and limited documentation.
- Users note the **missing features** in ScaleOps, particularly the lack of cross-cluster support and export options.
- Users find ScaleOps' **poor documentation** hinders onboarding and troubleshooting, making it challenging to utilize its features effectively.

#### What Are Recent G2 Reviews of ScaleOps?

**["Dynamic Resource Optimization That Cuts Costs and Keeps Workloads Stable"](https://www.g2.com/survey_responses/scaleops-review-12342100)**

**Rating:** 4.5/5.0 stars

_— Murugan U._

[Read full review](https://www.g2.com/survey_responses/scaleops-review-12342100)

**["ScaleOps Makes Kubernetes Cost Optimization Effortless with Smart Right-Sizing"](https://www.g2.com/survey_responses/scaleops-review-12668282)**

**Rating:** 4.5/5.0 stars

_— Ashish Y._

[Read full review](https://www.g2.com/survey_responses/scaleops-review-12668282)

### [Amazon EC2 Auto Scaling](https://www.g2.com/products/amazon-ec2-auto-scaling/reviews)

Amazon EC2 Auto Scaling is a service that helps maintain application availability by automatically adjusting Amazon EC2 instance capacity to meet changing demand. It enables users to define scaling policies that dynamically add or remove instances based on real-time metrics or predictable schedules, ensuring optimal performance and cost efficiency. Key Features and Functionality: - Automatic Scaling: Seamlessly launches new EC2 instances when demand increases and terminates unneeded instances when demand decreases, optimizing resource utilization. - Dynamic and Predictive Scaling: Adjusts capacity based on Amazon CloudWatch metrics or predefined schedules, allowing for proactive scaling in anticipation of traffic changes. - Health Monitoring and Replacement: Continuously monitors instance health and automatically replaces impaired instances to maintain desired capacity and application availability. - Multi-AZ Deployment: Distributes instances across multiple Availability Zones to enhance fault tolerance and resilience against localized failures. - Support for Multiple Instance Types and Purchase Options: Allows provisioning of various instance types and purchase options, including On-Demand and Spot Instances, to optimize performance and cost. - Integration with Load Balancing: Works with Elastic Load Balancing to distribute incoming traffic evenly across healthy instances, ensuring consistent application performance. Primary Value and Problem Solved: Amazon EC2 Auto Scaling addresses the challenge of fluctuating application demand by automatically adjusting compute capacity, ensuring applications remain responsive and cost-effective. By automating the scaling process, it reduces the need for manual intervention, minimizes the risk of over-provisioning or under-provisioning resources, and enhances overall application reliability and performance.

**Average Rating:** 4.6/5.0

**Total Reviews:** 29

#### How Do G2 Users Rate Amazon EC2 Auto Scaling?

- **Ease of Admin:** 8.6/10 (Category avg: 9.1/10)

#### Who Is the Company Behind Amazon EC2 Auto Scaling?

- **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd)
- **Year Founded:** 2006
- **HQ Location:** Seattle, WA
- **Twitter:** @awscloud  
2,232,483 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=072881eee28a2afe24f8d1bda9f20e3e146b9fb4b214f216411ce2ed6898b31e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Famazon-web-services%2F&secure%5Burl_type%5D=linkedin_company_website)  
147,094 employees on LinkedIn®
- **Ownership:** NASDAQ: AMZN

#### Who Uses This Product?

- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 45% Small, 45% Large

#### What Do G2 Reviewers Say About Amazon EC2 Auto Scaling?

_AI-generated summary from verified user reviews_

##### Cons

- Users find the **complex configuration** of EC2 Auto Scaling challenging and often overwhelming for newcomers to AWS.
- Users find the **steep initial learning curve** of EC2 Auto Scaling challenging, complicating optimal configuration for newcomers.
- Users face a **steep initial learning curve** with EC2 Auto Scaling, making optimal setup complex for beginners.

#### What Are Recent G2 Reviews of Amazon EC2 Auto Scaling?

**["Indispensable feature for EC2 management and high traffic requirements"](https://www.g2.com/survey_responses/amazon-ec2-auto-scaling-review-11618679)**

**Rating:** 4.5/5.0 stars

_— Luca P._

[Read full review](https://www.g2.com/survey_responses/amazon-ec2-auto-scaling-review-11618679)

**["Excellent Performance and Cost Optimisation with Amazon EC2 Auto Scaling"](https://www.g2.com/survey_responses/amazon-ec2-auto-scaling-review-13185631)**

**Rating:** 5.0/5.0 stars

_— Atharva P._

[Read full review](https://www.g2.com/survey_responses/amazon-ec2-auto-scaling-review-13185631)

#### What Are G2 Users Discussing About Amazon EC2 Auto Scaling?

- [What are the two main components of AWS Auto Scaling?](https://www.g2.com/discussions/what-are-the-two-main-components-of-aws-auto-scaling)
- [What are the benefits of Amazon EC2 Auto Scaling?](https://www.g2.com/discussions/what-are-the-benefits-of-amazon-ec2-auto-scaling)
- [What are the three components of EC2 Auto Scaling?](https://www.g2.com/discussions/what-are-the-three-components-of-ec2-auto-scaling)
- [What are the characteristics of Amazon EC2 Auto Scaling?](https://www.g2.com/discussions/what-are-the-characteristics-of-amazon-ec2-auto-scaling)

### [Pepperdata Capacity Optimizer](https://www.g2.com/products/pepperdata-capacity-optimizer/reviews)

Pepperdata Capacity Optimizer is the only real-time, automated cost optimization solution for Spark workloads that can immediately save you up to 47%. By instructing the scheduler to consider the actual resource utilization instead of allocated resources, Capacity Optimizer reclaims waste, maximizes resources utilization, and optimizes autoscaling in the cloud. It operates autonomously, continuously, and in real time to reclaim application waste.

**Average Rating:** 4.6/5.0

**Total Reviews:** 39

#### How Do G2 Users Rate Pepperdata Capacity Optimizer?

- **Ease of Admin:** 9.0/10 (Category avg: 9.1/10)

#### Who Is the Company Behind Pepperdata Capacity Optimizer?

- **Seller:** [Pepperdata](https://www.g2.com/sellers/pepperdata)
- **Year Founded:** 2012
- **HQ Location:** Sunnyvale, US
- **Twitter:** @pepperdata  
704 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=854f4d97b0a966ae1e58a430a0a7c21da2d969fb15c251c1c09422fd1306657a&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F2703086%2F&secure%5Burl_type%5D=linkedin_company_website)  
36 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Computer Software, Banking
- **Company Size:** 72% Large, 15% Medium

#### What Do G2 Reviewers Say About Pepperdata Capacity Optimizer?

_AI-generated summary from verified user reviews_

##### Pros

- Users enjoy the **enhanced performance** of Pepperdata Capacity Optimizer, achieving significant cost savings and efficiency improvements.
- Users benefit from significant **cost savings** with the Capacity Optimizer, often recouping expenses within months.
- Users value the **resource management efficiency** of Pepperdata Capacity Optimizer, achieving significant savings and optimized cluster performance.
- Users benefit from **substantial cost savings** with Pepperdata Capacity Optimizer, achieving up to 75% savings on clusters.
- Users love the **analytics capabilities** of Pepperdata Capacity Optimizer, enhancing job performance through insightful dashboards and reports.

##### Cons

- Users find the **lack of automation** frustrating, desiring automated feedback for optimal settings based on workloads.
- Users express concern over a **steep learning curve** , as many developers struggle with advanced tuning recommendations.
- Users find a **learning difficulty** with Pepperdata, as many developers struggle to utilize spark tuning recommendations effectively.
- Users find the **limited availability** of supported tools/products a drawback despite excellent cloud performance.
- Users note that the **limited number of supported tools** in Pepperdata Capacity Optimizer restricts its overall functionality.

#### What Are Recent G2 Reviews of Pepperdata Capacity Optimizer?

**["Great Easy to use Product. A must for ETL and Big Data"](https://www.g2.com/survey_responses/pepperdata-capacity-optimizer-review-9993736)**

**Rating:** 4.5/5.0 stars

_— Verified User in Banking_

[Read full review](https://www.g2.com/survey_responses/pepperdata-capacity-optimizer-review-9993736)

**["PepperData- a tool for performance"](https://www.g2.com/survey_responses/pepperdata-capacity-optimizer-review-4607489)**

**Rating:** 5.0/5.0 stars

_— akash v._

[Read full review](https://www.g2.com/survey_responses/pepperdata-capacity-optimizer-review-4607489)

#### What Are G2 Users Discussing About Pepperdata Capacity Optimizer?

- [What is Pepperdata Cloud Performance used for?](https://www.g2.com/discussions/what-is-pepperdata-cloud-performance-used-for)

### [Xosphere Instance Orchestrator](https://www.g2.com/products/xosphere-instance-orchestrator/reviews)

Xosphere's super power is reducing AWS EC2 expense by up to 80%. Xosphere is the world's only intelligent cloud orchestration company empowering enterprises to seamlessly move applications to the right place at the right time to reduce cloud expense and increase reliability. Xosphere's intelligent cloud software transforms unreliable Spot instances into robust resources that have the same reliability as On-Demand but at a fraction of the cost, yielding unparalleled savings. For enterprises that want to reduce cloud costs, Xosphere's optimization engine maximizes savings with the fastest speed of implementation in the industry. Xosphere Instance Orchestrator is a cloud-native, self-hosted subscription software application. It installs into your Amazon Web Services (AWS) account using either a CloudFormation stack or a Terraform module and runs using Lambda functions. Instance Orchestrator uses an opt-in design; it only executes on Auto-Scaling groups or individual instances that have explicitly been enabled via an AWS tag. Tags can be applied using any method or tool that is used within the organization to manage tags (for example, AWS Console, AWS CLI, AWS APIs, infrastructure-as-code platforms such as CloudFormation or Terraform, cloud management platforms, etc.). Once this enabling tag has been applied, Instance Orchestrator will automatically perform its management duties on an ongoing basis.

**Average Rating:** 5.0/5.0

**Total Reviews:** 17

#### How Do G2 Users Rate Xosphere Instance Orchestrator?

- **Ease of Admin:** 10.0/10 (Category avg: 9.1/10)

#### Who Is the Company Behind Xosphere Instance Orchestrator?

- **Seller:** [Xosphere](https://www.g2.com/sellers/xosphere)
- **Year Founded:** 2017
- **HQ Location:** Woodland Hills, US
- **Twitter:** @XosphereInc  
74 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=e4fe4fd9855628e3545eb82c4d1ce58799bcdcd9c70e203f3ed3ed51c3303bc4&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fxosphereinc%2F&secure%5Burl_type%5D=linkedin_company_website)  
6 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 41% Large, 24% Medium

#### What Are Recent G2 Reviews of Xosphere Instance Orchestrator?

**["Great solution"](https://www.g2.com/survey_responses/xosphere-instance-orchestrator-review-7723082)**

**Rating:** 5.0/5.0 stars

_— Alistair G._

[Read full review](https://www.g2.com/survey_responses/xosphere-instance-orchestrator-review-7723082)

**["Well worth the investment"](https://www.g2.com/survey_responses/xosphere-instance-orchestrator-review-7806392)**

**Rating:** 5.0/5.0 stars

_— I.Josh G._

[Read full review](https://www.g2.com/survey_responses/xosphere-instance-orchestrator-review-7806392)

### [Real-Time Technology Solutions](https://www.g2.com/products/real-time-technology-solutions/reviews)

Avi Networks enables public-cloud-like simplicity and flexibility for application services such as load balancing, application analytics, and security in any data center or cloud.

**Average Rating:** 4.8/5.0

**Total Reviews:** 9

#### How Do G2 Users Rate Real-Time Technology Solutions?

- **Ease of Admin:** 8.3/10 (Category avg: 9.1/10)

#### Who Is the Company Behind Real-Time Technology Solutions?

- **Seller:** [Broadcom](https://www.g2.com/sellers/broadcom-ab3091cd-4724-46a8-ac89-219d6bc8e166)
- **Year Founded:** 1991
- **HQ Location:** San Jose, CA
- **Twitter:** @broadcom  
63,909 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=093adce8015fea9ef126312884b465dc8e3c20e17dcb12fbb77a7bd82577e7a5&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fbroadcom%2F&secure%5Burl_type%5D=linkedin_company_website)  
55,094 employees on LinkedIn®
- **Ownership:** NASDAQ: CA

#### Who Uses This Product?

- **Company Size:** 56% Large, 33% Small

#### What Are Recent G2 Reviews of Real-Time Technology Solutions?

**["Security and performance of Avi Vantage"](https://www.g2.com/survey_responses/real-time-technology-solutions-review-8765626)**

**Rating:** 5.0/5.0 stars

_— Antônio A._

[Read full review](https://www.g2.com/survey_responses/real-time-technology-solutions-review-8765626)

**["Avi Vantage Support"](https://www.g2.com/survey_responses/real-time-technology-solutions-review-9900482)**

**Rating:** 4.5/5.0 stars

_— Ankit C._

[Read full review](https://www.g2.com/survey_responses/real-time-technology-solutions-review-9900482)

#### What Are G2 Users Discussing About Real-Time Technology Solutions?

- [What is Avi Networks used for?](https://www.g2.com/discussions/what-is-avi-networks-used-for)

### [Alibaba Auto Scaling](https://www.g2.com/products/alibaba-auto-scaling/reviews)

Auto Scaling is a service to automatically adjust computing resources based on your volume of user requests. When demand for computing resources increase, Auto Scaling automatically adds ECS instances to serve additional user requests, or alternatively removes instances in the case of decreased user requests.

**Average Rating:** 3.8/5.0

**Total Reviews:** 2

#### Who Is the Company Behind Alibaba Auto Scaling?

- **Seller:** [Alibaba](https://www.g2.com/sellers/alibaba)
- **HQ Location:** Hangzhou
- **Twitter:** @alibaba\_cloud  
1,189,812 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=04233a035f0a002519b0cdb9979126540aa93dd4a9519e658a93e9e729f58be9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1218665%2F&secure%5Burl_type%5D=linkedin_company_website)  
5,110 employees on LinkedIn®
- **Ownership:** BABA
- **Total Revenue (USD mm):** $509,711

#### Who Uses This Product?

- **Company Size:** 100% Medium

#### What Do G2 Reviewers Say About Alibaba Auto Scaling?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **dynamic scaling mode** of Alibaba Auto Scaling for efficiently adjusting resources based on utilization.
- Users value the **differentiated scaling modes** of Alibaba Auto Scaling, especially dynamic scaling for optimal resource utilization.

##### Cons

- Users find the **poor documentation** frustrating, making it difficult to use Alibaba Auto Scaling with AWS/GCP.

#### What Are Recent G2 Reviews of Alibaba Auto Scaling?

**["Powerful solution for good management of computing resources"](https://www.g2.com/survey_responses/alibaba-auto-scaling-review-3434880)**

**Rating:** 5.0/5.0 stars

_— Alexa T._

[Read full review](https://www.g2.com/survey_responses/alibaba-auto-scaling-review-3434880)

#### What Are G2 Users Discussing About Alibaba Auto Scaling?

- [What is Alibaba Auto Scaling used for?](https://www.g2.com/discussions/alibaba-auto-scaling-what-is-alibaba-auto-scaling-used-for)
- [What is Alibaba Auto Scaling used for?](https://www.g2.com/discussions/what-is-alibaba-auto-scaling-used-for)

### [Amazon Aurora Serverless V2](https://www.g2.com/products/amazon-aurora-serverless-v2/reviews)

Product Description: Amazon Aurora Serverless v2 is an on-demand, auto-scaling configuration for Amazon Aurora that automatically adjusts database capacity based on application needs. It scales instantly to handle hundreds of thousands of transactions in a fraction of a second, providing the right amount of resources without manual intervention. This service supports both the MySQL-Compatible and PostgreSQL-Compatible editions of Aurora, offering high availability, performance, and resiliency. By paying only for the capacity consumed, users can achieve up to 90% cost savings compared to provisioning for peak loads. Key Features and Functionality: - Instant Auto-Scaling: Adjusts database capacity in fine-grained increments to match application demands without disrupting connections or transactions. - High Availability: Supports Multi-AZ deployments, read replicas, and global databases to ensure continuous operation and data durability. - Cost Efficiency: Charges are based on actual capacity usage, leading to significant cost savings by avoiding over-provisioning. - Feature Parity with Provisioned Aurora: Includes capabilities like cloning, Performance Insights, and IAM authentication, aligning with the full suite of Aurora features. - Seamless Integration: Allows mixing of serverless and provisioned instances within the same cluster, providing flexibility in database management. Primary Value and Problem Solved: Amazon Aurora Serverless v2 simplifies database management by eliminating the need for manual capacity planning and scaling. It addresses challenges associated with variable and unpredictable workloads by providing automatic, near-instantaneous scaling, ensuring optimal performance without over-provisioning. This approach not only enhances application responsiveness but also significantly reduces operational costs, making it ideal for a wide range of applications, from development and testing environments to business-critical systems.

**Average Rating:** 3.5/5.0

**Total Reviews:** 1

#### How Do G2 Users Rate Amazon Aurora Serverless V2?

- **Ease of Admin:** 8.3/10 (Category avg: 9.1/10)

#### Who Is the Company Behind Amazon Aurora Serverless V2?

- **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd)
- **Year Founded:** 2006
- **HQ Location:** Seattle, WA
- **Twitter:** @awscloud  
2,232,483 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=072881eee28a2afe24f8d1bda9f20e3e146b9fb4b214f216411ce2ed6898b31e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Famazon-web-services%2F&secure%5Burl_type%5D=linkedin_company_website)  
147,094 employees on LinkedIn®
- **Ownership:** NASDAQ: AMZN

#### Who Uses This Product?

- **Company Size:** 100% Small

#### What Do G2 Reviewers Say About Amazon Aurora Serverless V2?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **quick support** provided by Amazon Aurora Serverless V2, enhancing their overall experience with the product.
- Users commend the **ease of use** of Amazon Aurora Serverless V2, appreciating its user-friendly interface and quick support.
- Users appreciate the **implementation ease** of Amazon Aurora Serverless V2, noting its user-friendly design and quick support.

### [AutoSpotting](https://www.g2.com/products/autospotting/reviews)

AutoSpotting allows you to safely and reliably cut your AWS EC2 costs by up to 90% (usually 50-80%) without long term commitments or upfront payments, by replacing EC2 instances in autoscaling groups with identically configured Spot instances. It installs in minutes using CloudFormation and Terraform, and can be configured using tags and even taking over all the groups from your account, without requiring launch template or launch configuration changes, and without causing IaC drift. For maximum compatibility, it supports most applications backed by on-demand autoscaling groups, including for AWS services such as Beanstalk, EKS and ECS that use ASGs under the hood. The main requirement is for the instances to be replaceable without noticeable impact to your users, which is usually the case for autoscaling groups out of the box. For maximum security, privacy and reduced runtime costs it is a fully self-hosted, serverless, pay as you go software that runs entirely in your account with minimalist IAM permissions. Once enabled on your on-demand ASGs by tagging them(you can use any tool for tagging, but we also have a GUI to make it easier and reduce the chance of human errors), it gradually replaces their instances with diversified Spot instances. Under the hood we use attach API calls, then terminate the initial instances, leaving you with up to 90% cheaper but identically configured Spot instances. To minimize capacity churn as much as possible, any new instances are also replaced with the same approach within seconds of being launched, and we use a capacity optimized allocation strategy that gives us instances with lower probability of interruption. To ensure you always get the capacity you need for your application, Spot instances are launched with widest possible diversification, and we also have failover to on-demand instances with the same level of diversification we use for Spot instances. This makes the groups managed by AutoSpotting more resilient to Insufficient Capacity Events that may occasionally impact OnDemand ASGs usually configured with a single instance type. For increased performance and reduced carbon emissions, it always provisions the newest available instance types.

**Average Rating:** 5.0/5.0

**Total Reviews:** 1

#### Who Is the Company Behind AutoSpotting?

- **Seller:** [LeanerCloud](https://www.g2.com/sellers/leanercloud)
- **Year Founded:** 2022
- **HQ Location:** Berlin, DE
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=afdb06e0da96ca03638eac41115509ab7cf0c7a141e93d7bd0df2b4aabdc07c3&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fleanercloud%2F&secure%5Burl_type%5D=linkedin_company_website)  
2 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 100% Medium

#### What Are Recent G2 Reviews of AutoSpotting?

**["Something that isn't too good to be true!"](https://www.g2.com/survey_responses/autospotting-review-9941154)**

**Rating:** 5.0/5.0 stars

_— Lloyd W._

[Read full review](https://www.g2.com/survey_responses/autospotting-review-9941154)

### [Thoras AI](https://www.g2.com/products/thoras-ai/reviews)

Meet your infrastructure Al toolkit: Thoras leverages bleeding-edge Al to predict and scale your GPU and CPU resources, prevent downtime, and optimize Kubernetes workloads—saving you money and keeping your systems running smoothly. Modern autoscalers react too late, forcing you to over provision compute or risk downtime. Thoras forecasts workload demand with precision using bleeding-edge ML modeling, so your infrastructure is always one step ahead.

**Average Rating:** 5.0/5.0

**Total Reviews:** 3

#### How Do G2 Users Rate Thoras AI?

- **Ease of Admin:** 10.0/10 (Category avg: 9.1/10)

#### Who Is the Company Behind Thoras AI?

- **Seller:** [Thoras AI](https://www.g2.com/sellers/thoras-ai)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=bbdf2891ec5dbfa78f78cd050a4484033f7dca5a7fbcfc49dedd1e6b9f87edb7&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fthoras%2F&secure%5Burl_type%5D=linkedin_company_website)  
17 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 100% Medium

#### What Do G2 Reviewers Say About Thoras AI?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **automation** in Thoras AI, streamlining pod re-sizing effortlessly without manual intervention.
- Users appreciate the **auto scaling** feature of Thoras AI, enabling effortless pod resizing without manual intervention.
- Users commend Thoras AI's team for their **exceptional customer support** and dedication in optimizing Kubernetes environments.
- Users value the **easy integrations** with Thoras AI, enhancing support and optimization for their Kubernetes environments.
- Users value the **exceptional support** from the Thoras team in optimizing and integrating their Kubernetes environments.

##### Cons

- Users find the **complex configuration** of Thoras AI a bit time-consuming, especially for their unique pipelines.
- Users find the **complexity of onboarding** Thoras challenging, as it adds significant time to pipeline configuration efforts.
- Users feel that the **configuration complexity** requires too much manual effort instead of being fully automated.
- Users find **onboarding time consuming** due to complex pipeline configurations despite helpful initial support from the account manager.

#### What Are Recent G2 Reviews of Thoras AI?

**["Thoras Helped Us Optimize Kubernetes Usage, Reliability, and Cloud Spend"](https://www.g2.com/survey_responses/thoras-ai-review-12415840)**

**Rating:** 5.0/5.0 stars

_— Ryan W._

[Read full review](https://www.g2.com/survey_responses/thoras-ai-review-12415840)

**["Effortless Pod Resizing Without Manual Intervention"](https://www.g2.com/survey_responses/thoras-ai-review-12417980)**

**Rating:** 5.0/5.0 stars

_— Ali S._

[Read full review](https://www.g2.com/survey_responses/thoras-ai-review-12417980)

### [UbiOps](https://www.g2.com/products/ubiops/reviews)

If you are a data scientist or engineer, at some point you want to bring your algorithm to production. And that means installing libraries, managing dependencies, deploying your scrips and models, versioning, serving, and running out of compute. Let’s be honest: deployment is hard. The tools we use are not as helpful as they could be, because they are not designed for our specific needs. And we lose ourselves in time-consuming model deployments and infrastructure management. That is not what we are meant for. We want to make sure that our time is best spent where we are needed, developing algorithms and code to create impact. That’s why we’re building UbiOps.

**Average Rating:** 4.7/5.0

**Total Reviews:** 5

#### Who Is the Company Behind UbiOps?

- **Seller:** [UbiOps](https://www.g2.com/sellers/ubiops)
- **Year Founded:** 2020
- **HQ Location:** The Hague, NL
- **Twitter:** @UbiOps\_  
109 Twitter followers
- **LinkedIn® Page:** [linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=d461027edb7469f50c506ac7d5c6bc95145d3c20bc236f8716c00edb0ca3e41f&secure%5Burl%5D=https%3A%2F%2Flinkedin.com%2Fcompany%2Fubiops&secure%5Burl_type%5D=linkedin_company_website)  
23 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 60% Medium, 40% Small

#### What Are Recent G2 Reviews of UbiOps?

**["UbiOps - Makes Machine Learning Models Scalable"](https://www.g2.com/survey_responses/ubiops-review-6608586)**

**Rating:** 4.5/5.0 stars

_— Priyanshu K._

[Read full review](https://www.g2.com/survey_responses/ubiops-review-6608586)

**["Highly Recommend"](https://www.g2.com/survey_responses/ubiops-review-6771317)**

**Rating:** 5.0/5.0 stars

_— Abhyuday T._

[Read full review](https://www.g2.com/survey_responses/ubiops-review-6771317)

#### What Are G2 Users Discussing About UbiOps?

- [What is UbiOps used for?](https://www.g2.com/discussions/what-is-ubiops-used-for)

### [F5 BIG-IP WAF AWS Deployment & Integration](https://www.g2.com/products/f5-big-ip-waf-aws-deployment-integration/reviews)

Vandis engineers will work with your network and security teams to integrate F5 Network BIG-IP WAFs into your private network design on AWS. We will assist with the design and configuration of the VPC, subnets, DMZ, Security Groups, Route Tables, and EC2 Auto Scaling Groups as needed, and then deliver those in a detailed design and implementation document.

**Average Rating:** 4.5/5.0

**Total Reviews:** 2

#### How Do G2 Users Rate F5 BIG-IP WAF AWS Deployment & Integration?

- **Ease of Admin:** 8.3/10 (Category avg: 9.1/10)

#### Who Is the Company Behind F5 BIG-IP WAF AWS Deployment & Integration?

- **Seller:** [F5](https://www.g2.com/sellers/f5-f6451ada-8c47-43f5-b017-58663a045bc5)
- **HQ Location:** Seattle, Washington
- **Twitter:** @F5Networks  
1,385 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=c7f11d476d00d2f94515d8841a7c9d683a4303902a44318177a444690ba1c225&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F4841%2F&secure%5Burl_type%5D=linkedin_company_website)  
6,165 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 50% Small

#### What Do G2 Reviewers Say About F5 BIG-IP WAF AWS Deployment & Integration?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **easy configurability** of F5 BIG-IP WAF, enabling tailored security for applications and APIs.
- Users value the **ease of configuration** with F5 BIG-IP WAF, enhancing their application security experience effortlessly.
- Users value the **granular policy customization** of F5 BIG-IP WAF, enhancing security for diverse application threats effectively.
- Users appreciate the **strong security and visibility** offered by F5 BIG-IP WAF, enhancing protection for applications and APIs.
- Users value the **quick setup** of F5 BIG-IP WAF AWS, finding it straightforward and efficient for enhanced security.

##### Cons

- Users feel that the **GUI could be improved** , impacting ease of use and overall experience.

#### What Are Recent G2 Reviews of F5 BIG-IP WAF AWS Deployment & Integration?

**["Unmatched Security with Easy Integration"](https://www.g2.com/survey_responses/f5-big-ip-waf-aws-deployment-integration-review-12092764)**

**Rating:** 4.5/5.0 stars

_— Sanjay G._

[Read full review](https://www.g2.com/survey_responses/f5-big-ip-waf-aws-deployment-integration-review-12092764)

**["Deployed WAF at AWS Cloud"](https://www.g2.com/survey_responses/f5-big-ip-waf-aws-deployment-integration-review-5345840)**

**Rating:** 4.5/5.0 stars

_— Verified User in Information Technology and Services_

[Read full review](https://www.g2.com/survey_responses/f5-big-ip-waf-aws-deployment-integration-review-5345840)

#### What Are G2 Users Discussing About F5 BIG-IP WAF AWS Deployment & Integration?

- [What is F5 BIG-IP WAF AWS Deployment & Integration used for?](https://www.g2.com/discussions/what-is-f5-big-ip-waf-aws-deployment-integration-used-for)

### [InfraGraf Network Traffic Forecasting](https://www.g2.com/products/infragraf-network-traffic-forecasting/reviews)

InfraGraf Network Traffic Forecasting helps businesses get a future forecast of the network traffic based on historic data. Benefits offered by this solution includes accurate forecast of network traffic which enables better planning for network infrastructure, application scalability and auto scaling. It uses ensemble ML algorithms with automatic model selection algorithms. This solution provides consistent and better results due to its ensemble learning approach. This solution performs automated model selection to apply the right model based on the input data.

#### Who Is the Company Behind InfraGraf Network Traffic Forecasting?

- **Seller:** [Mphasis](https://www.g2.com/sellers/mphasis-5a2b4772-cd1c-4cbd-bf88-54fc79a85d25)
- **Year Founded:** 2007
- **HQ Location:** Reston, VA
- **Twitter:** @Stelligent  
1,106 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ace0aa7310e9fd4ef0facca25c9ef8b08d319acab135d8d95d5c03e74d84f199&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F220927&secure%5Burl_type%5D=linkedin_company_website)  
14 employees on LinkedIn®

- ‹ Prev‹ Prev
- 1
- [2](/categories/auto-scaling?open_modal_url=%2Fproducts%2Freal-time-technology-solutions%2Fwishlists%3Fhost_path%3D%252Fcategories%252Fauto-scaling%26source%3Dcategory&order=g2_score&page=2#product-list)
- [Next ›Next ›](/categories/auto-scaling?open_modal_url=%2Fproducts%2Freal-time-technology-solutions%2Fwishlists%3Fhost_path%3D%252Fcategories%252Fauto-scaling%26source%3Dcategory&order=g2_score&page=2#product-list)

Spotlight Categories

[Application Performance Monitoring (APM) Tools](https://www.g2.com/categories/application-performance-monitoring-apm)

[Core HR Software](https://www.g2.com/categories/core-hr)

[Digital Asset Management Software](https://www.g2.com/categories/digital-asset-management)

[Restaurant POS Systems](https://www.g2.com/categories/restaurant-pos)

[Knowledge Base Software](https://www.g2.com/categories/knowledge-base-software)

Similar Categories

- [Application Portfolio Management](/categories/application-portfolio-management)
- [Cloud Cost Management](/categories/cloud-cost-management)
- [Cloud Management Platforms](/categories/cloud-management-platforms)
- [Cloud Migration Assessment Tools](/categories/cloud-migration-assessment-tools)
- [Columnar Databases](/categories/columnar-databases)

- [Data as a Service (DaaS)](/categories/data-as-a-service-daas)
- [Data Destruction](/categories/data-destruction)
- [Data Extraction](/categories/data-extraction-tools)
- [Data Governance](/categories/data-governance-tools)
- [Data Observability](/categories/data-observability)

- [Data Recovery](/categories/data-recovery)
- [Digital Employee Experience (DEX) Management](/categories/digital-employee-experience-dex-management)
- [Digital Experience Monitoring (DEM)](/categories/digital-experience-monitoring-dem)
- [Digital Governance](/categories/digital-governance)
- [Disk Cleanup](/categories/disk-cleanup)

[Browse Auto Scaling Themes](/categories/auto-scaling/themes)

 ![Rachana Hasyagar](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Rachana Hasyagar")
RH

Researched and written by [Rachana Hasyagar](https://research.g2.com/insights/author/rachana-hasyagar)

Updated October 3, 2024

Auto Scaling software dynamically allocates or deallocates computing resources based on an application’s requirement. This type of software can automatically scale up resources during high traffic and scale down when there is less traffic. IT administrators use auto scaling software to ensure the availability of cloud systems by adding more computing resources when needed and optimizing costs by automatically decommissioning instances when capacity requirement reduces.

Auto scaling has some features of [cloud infrastructure monitoring software](https://www.g2.com/categories/cloud-infrastructure-monitoring) as it continuously monitors systems to check for resource usage. However, auto scaling software, in addition to monitoring, can also increase or decrease capacity allocation. It also has features that overlap with [load balancing software](https://www.g2.com/categories/load-balancing), a tool that distributes traffic to healthy server instances to ensure continuous availability. Load balancing and auto scaling software working in tandem provide efficient management of resources. Auto scaling software provides new instances for which load balancing software can provide connections.

To qualify for inclusion in the Auto Scaling category, a product must:

- Continuously monitor the cloud environment to identify capacity needs and free resources
- Allocate and deallocate new instances if an application requires more or fewer resources
- Anticipate demand fluctuations based on regular resource consumption patterns
- Provide visibility into resource consumption across the system through a single dashboard or portal

Show More