Sold by: PerfectScale
Deployed on AWS
Ensure peak Kubernetes performance at the lowest possible cost.
4.7
Overview
Effortlessly right-scale your Kubernetes environment. PerfectScale by DoiT autonomously optimizes system scalability, strengthens resilience, and slashes your cloud bill, ensuring peak K8s performance at the lowest possible cost.
Highlights
- One solution for complete multi-cloud, multi-cluster visibility providing cost, utilization, and performance metrics and optimization insight across every layer of your K8s stack.
- GitOps-friendly, autonomous Kubernetes optimization built for production environments. Our flexible automation engine is impact-aware, works seamlessly with Cluster-Autoscaler and Karpenter, and integrates directly into your workflows, aligning continuous optimization with continuous delivery, and ensuring constant resilience and cost-effectiveness.
- Detailed trending analysis and governance capabilities that align development, DevOps, and FinOps teams with the information needed to make important decisions and improve operations.
Details
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month | Overage cost |
|---|---|---|---|
Community | For up to 300k vCPU hours per month. | $0.00 | - |
Advanced (equivalent to $2.00 per monthly vCPU, with usage metered hourly and billed in 1 vCPU-hour increments) | Including CUR and InfraFit | $0.001 | |
Expert (equivalent to $4.00 per monthly vCPU, with usage metered hourly and billed in 1 vCPU-hour increments) | Including Automation, Public API and SSO | $0.002 |
Dimensions summary
You pick from three tiers based on your Kubernetes vCPU usage. The Community tier is free and covers up to 300,000 vCPU-hours per month. The Advanced and Expert tiers are contract-based, priced per monthly vCPU and metered hourly in 1 vCPU-hour increments. Advanced includes CUR and InfraFit. Expert adds Automation, Public API, and SSO. Pricing scales with your average monthly vCPU consumption across your clusters. If you pass the Community limit, you move to Advanced or Expert. Advanced and Expert include a 5% grace buffer above purchased licensing, with extra usage prorated.
Top-of-mind questions for buyers
Billing is based on your environment's average monthly vCPU consumption. The platform totals the vCPU cores used each month across any cloud or self-hosted Kubernetes clusters. Usage is metered hourly and billed in 1 vCPU-hour increments, so your bill reflects actual core consumption over the month.
The Advanced and Expert packages include a 5% grace buffer above your purchased vCPU licensing. You get a notice as you approach this limit. Any extra licenses beyond it are priced at a prorated rate matching your current billing cycle, rather than triggering an automatic tier jump.
Advanced includes CUR and InfraFit. Expert costs more per monthly vCPU and adds Automation, Public API, and SSO on top of the Advanced capabilities. Both meter usage hourly in 1 vCPU-hour increments, so the choice depends on whether you need autonomous actions, API access, and single sign-on.
www.perfectscale.io
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Vendor refund policy
We do not currently offer refunds.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
We offer professional support options and SLAs with our Expert plan. support@perfectscale.io Or
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By ScaleOps
By Kedify
AI generated from product descriptions
Multi-Cloud and Multi-Cluster Visibility
Provides unified visibility across multiple cloud providers and Kubernetes clusters with cost, utilization, and performance metrics across all layers of the Kubernetes stack.
GitOps-Based Autonomous Optimization
Implements GitOps-friendly autonomous optimization engine that integrates with Cluster-Autoscaler and Karpenter for production environments with impact-aware automation.
Resource Right-Scaling
Optimizes Kubernetes environment through intelligent right-scaling of compute resources to reduce cloud infrastructure costs while maintaining performance.
Trending Analysis and Governance
Delivers detailed trending analysis and governance capabilities to align development, DevOps, and FinOps teams with operational insights and decision-making data.
Resilience and Performance Optimization
Strengthens Kubernetes resilience and system scalability through continuous optimization integrated into application-delivery workflows.
Automated Pod Resource Optimization
Continuously analyzes container compute usage and vertically scales Kubernetes pods to meet demand during runtime with zero disruption
Node Cost Optimization
Identifies opportunities to remove under-provisioned nodes, replace expensive nodes with cheaper alternatives, and consolidate pods onto more efficient compute resources
Real-Time Resource Adjustment
Automatically adjusts compute resources in response to real-time changes in workload demand
Read-Only to Automated Scaling Progression
Supports graduated deployment model starting from read-only recommendations and progressing to continuous automatic optimization
Event-Driven Autoscaling
Supports 65+ event sources including HTTP events for triggering autoscaling decisions based on real-time demand signals
Multi-Cluster Management
Enables management and monitoring of autoscaling configurations across multiple Kubernetes clusters and cloud environments
Zero-Based Scaling
Capability to scale workloads down to zero instances during low demand periods and scale up seamlessly when demand increases
Security and Compliance
Maintains KEDA framework with up-to-date security patches, CVE-free status, and role-based access controls for autoscaling configurations
Kubernetes Integration
Enterprise-grade autoscaling service built on KEDA (Kubernetes Event-Driven Autoscaling) framework for seamless Kubernetes cluster integration
Standard contract
Customer reviews
reviewer2774151
Has reduced resource waste and improved cluster performance through automation
Reviewed on Oct 31, 2025
Review from a verified AWS customer
What is our primary use case?
Kubernetes Optimisation
How has it helped my organization?
PerfectScale made our Kubernetes optimization effortless. It found wasted resources, lowered our cloud costs, and improved performance almost instantly. It is super easy to use and worth every penny.
What is most valuable?
I find the ability to understand spend and wastage across clusters very valuable. The automated adjustments are also great.
What needs improvement?
With their in-place optimisations, stateful set optimisation would be a great addition.
For how long have I used the solution?
Less than one year
Which solution did I use previously and why did I switch?
I did not use any previous solutions before implementing PerfectScale.
What's my experience with pricing, setup cost, and licensing?
The pricing is good, and the team is really helpful.
Which other solutions did I evaluate?
I also considered Pump and Zesty.
reviewer2750058
Gain visibility into Kubernetes clusters and optimize resource allocation based on historical data
Reviewed on Aug 14, 2025
Review provided by PeerSpot
What is our primary use case?
My primary use case with PerfectScale is having visibility on our Kubernetes clusters. It helps reduce our costs by providing recommendations to define resources for services as needed and avoid overprovisioning. There is an autoscaler that can be defined on the cluster or workload level, which allows us to control our workloads and pre-define the resources for each use case.
How has it helped my organization?
In my opinion, it has improved our organization because it gives us more control over our Kubernetes cluster. It also provides more knowledge on how to handle high-cost scenarios. I was able to break down the costs and build a solid report, which allowed us to take action against high-cost situations.
What is most valuable?
The cluster and workload autoscaler gives us the ability to have control over all the workloads' resources instead of managing them one by one. We typically start from there, and it does the job very well. The recommendations are based on historical data that PerfectScale gathers, providing us with more information on how the workload should be defined based on timeframe and revisions.
What needs improvement?
I think they should focus more on Kubernetes features that allow on-the-fly resource allocation without the need to restart services. They should implement this in their autoscaler to make it more useful in scenarios that require immediate scaling up or down. They should also offer more options for visualizing graphs in different ways, such as tabular views.
For how long have I used the solution?
I have been using the solution for approximately 1.5 years.
What other advice do I have?
Their support team consists of really good people who assist us in understanding the product. They also share upcoming and recently released features with us. They genuinely take care of their customers. I would rate it an eight out of ten.
reviewer2749209
Automated resource optimization leads to cost savings while documentation errors are addressed
Reviewed on Aug 11, 2025
Review provided by PeerSpot
What is our primary use case?
I used PerfectScale to gain insight into the workload and then optimized the resource allocation through manual configuration or automated allocation. By doing so, I was able to achieve Kubernetes cost savings.
How has it helped my organization?
Automated resource optimization using different policies based on the environment enabled the organization to achieve infrastructure cost savings.
What is most valuable?
PerfectScale provides insights into workload resource consumption and enables dynamic resource re-allocation.
What needs improvement?
At the beginning, the support was not very impressive. There were some mistakes in the documentation, such as how to exclude a workload from automation.
Which solution did I use previously and why did I switch?
I previously used Prometheus, but it is not as easy to use as PerfectScale.
What's my experience with pricing, setup cost, and licensing?
There was not really a setup cost involved.
Which other solutions did I evaluate?
I did not really consider alternate solutions.
What other advice do I have?
It is worth trying.