Significantly reduces cloud costs (up to 80%) without compromising performance.
Frees engineers from manual resource tuning, allowing them to focus on innovation.
Ensures consistent performance and uptime even during demand spikes.
Easy installation with a single Helm command for immediate value.
Provides deep visibility into Kubernetes costs and workload behavior.

Cons

No free tier or trial explicitly mentioned.
Requires existing Kubernetes infrastructure.
Specific cost savings percentages may vary based on individual environment.

What is ScaleOps?

Editorial review

ScaleOps provides an autonomous platform for optimizing Kubernetes resources, including CPU, memory, and GPU, in real-time. It aims to maximize performance and cut cloud costs by up to 80% through context-aware automation, eliminating the need for manual tuning. The platform offers a comprehensive suite of features such as automated pod rightsizing, replica optimization, smart pod placement, and specialized GPU workload rightsizing. It integrates seamlessly with existing Kubernetes setups, including HPA and KEDA, and supports GitOps workflows, allowing organizations to maintain performance and reliability while freeing engineers from repetitive configuration tasks.

Available on: Web

LCLouis CorneloupUpdated May 26, 2026 · how we evaluateSourcescaleops.com ↗

Ratings Across the Web

4.6(93 reviews)

ScaleOps holds an aggregate rating of 4.6 out of 5 from 93 reviews across G2, last checked May 4, 2026.

G293 reviews

4.6/5

Ratings aggregated from independent review platforms. Learn more

Preview

Key Features

Automated Real-Time Pod Rightsizing
Replica Optimization
Smart Pod Placement
Spot Optimization
Node Optimization
Karpenter Optimization
Autonomous GPU Workload Rightsizing
AI Replica Optimization for GPUs

Pricing Plans

Pricing checked Oct 3, 2026

ScaleOps plans and prices, checked October 2026
Plan	Price	Details
Get Started	Free	Automated Real-Time Pod Rightsizing Replica Optimization Smart Pod Placement +8 moreShow less Spot Optimization Node Optimization Karpenter Optimization Autonomous GPU Workload Rightsizing AI Replica Optimization Improved GPU Availability Cluster and Workload Troubleshooting Cost Monitoring

View full pricing

Is ScaleOps worth the price?

Great value

The 'Get Started' tier is exceptionally generous, offering a comprehensive suite of optimization and monitoring features for free.

This makes ScaleOps an incredibly attractive option for any organization looking to optimize their Kubernetes costs without an initial investment. It's best for startups and small to medium-sized businesses exploring cost optimization solutions.

Reviews

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4.6/5

Across 93 verified user reviews on G2

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Best ScaleOps Alternatives

Top alternatives based on features, pricing, and user needs.

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KubecostFreemium

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Still deciding?

Most buyers shortlist 2 or 3 tools before committing. Pull a side-by-side comparison or browse the full alternatives shortlist below.

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ScaleOps FAQ

How does ScaleOps handle resource optimization for GPU workloads?

ScaleOps maximizes GPU utilization through dynamic GPU sharing and automated workload rightsizing. It also offers AI Replica Optimization to define HPA thresholds using real pod-level GPU utilization, scaling each workload based on its actual consumption rather than device-level averages.

Can ScaleOps integrate with existing GitOps workflows?

Yes, ScaleOps integrates natively with GitOps workflows, allowing all platform actions to be defined and managed as code. It provides fine-grained control across workloads, namespaces, and clusters, and works out-of-the-box with Argo CD, Flux, and any CI/CD pipeline.

What mechanisms does ScaleOps use to prevent performance degradation and ensure application resilience?

ScaleOps includes Automatic Pod Healing, which detects and heals issues like CPU throttling, OOM kills, stressed nodes, noisy neighbors, and failing health probes in real-time. It also features Real-Time Burst Reaction to dynamically provision resources during demand surges to maintain performance and uptime.

How does ScaleOps optimize DaemonSets across different node sizes?

ScaleOps autonomously rightsizes each DaemonSet per node, aligning resources to real usage. This eliminates wasted capacity on larger nodes and prevents performance risks on smaller ones, addressing the inefficiency of a single resource recommendation across all node sizes.

Does ScaleOps support in-place pod resizing without restarts or evictions?

Yes, ScaleOps provides native support for Kubernetes In-Place Pod Resizing. It dynamically manages CPU and memory requests on production workloads without triggering restarts or evictions, ensuring continuous operation.

Source: scaleops.com

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