Sold by: PerfectScaleÂ
Deployed on AWS
Ensure peak Kubernetes performance at the lowest possible cost.
Overview
Effortlessly right-scale your Kubernetes environment. PerfectScale by DoiT 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 application-delivery workflows, 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
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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 |
Vendor refund policy
We do not currently offer refunds.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
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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
AI generated from product descriptions
Kubernetes Optimization
Automated right-sizing and optimization of Kubernetes resources across multi-cloud and multi-cluster environments
Performance Monitoring
Comprehensive visibility into system scalability, utilization metrics, and performance insights across Kubernetes infrastructure layers
Governance Capabilities
Advanced trending analysis and governance tools that enable cross-team alignment and operational decision-making
Automation Engine
GitOps-friendly optimization mechanism with impact-aware automation that integrates with Cluster-Autoscaler and Karpenter
Infrastructure Resilience
Autonomous optimization framework designed to enhance system reliability and maintain constant operational effectiveness
Resource Optimization
Automated continuous analysis and vertical scaling of Kubernetes pods based on real-time compute usage
Cluster Management
Proactive identification and removal of under-provisioned nodes and consolidation of pods onto more efficient compute resources
Deployment Mode
Self-hosted platform with quick two-minute installation process
Runtime Optimization
Zero-disruption automatic pod optimization during runtime
Workload Analysis
Capability to handle critical production workloads in full automation mode
Autonomous Resource Optimization
AI/ML-powered continuous optimization of Kubernetes workloads and clusters through intelligent scaling of memory, CPU, and replica sets
Machine Learning-Based Remediation
Real-time predictive issue detection and autonomous remediation actions to maintain system availability and performance
Performance Intelligence
Automated performance scoring for releases, tracking changes in latency and error rates with intelligent feedback mechanisms
SLA/SLO Management
Autonomous SLO target definition, error budget management, and performance optimization to prevent downtime and service breaches
Cloud Resource Purchasing Strategy
Intelligent identification and selection of optimal cost combinations between spot instances, on-demand, and savings plans based on predicted traffic behavior
Standard contract
Customer reviews
0 ratings
0 AWS reviews
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2 external reviews
Star ratings include only reviews from verified AWS customers. External reviews can also include a star rating, but star ratings from external reviews are not averaged in with the AWS customer star ratings.
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.Â
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.