Not all Kubernetes cost optimizations
solutions are built the same
Why 
?
Fully auton
mous in production.
Trusted by the world’s leading companies.
“We came in looking to save costs, but not at the expense of performance. With ScaleOps’ automated resource optimization, we got both, and saw dramatically high cost savings without compromising on reliability.”
“ScaleOps’ automation optimizes our production apps in real time, cutting cloud costs and eliminating repetitive manual work so our teams can focus on core projects. The quick setup delivered immediate value.”
Here’s What People Are Saying About Us
“I appreciate how easy it was to install ScaleOps and how it instantly reduced the cognitive load on our application teams, making it much simpler for them to deploy their workloads effectively.”
“ScaleOps’ automation optimizes our production apps in real time, cutting cloud costs and eliminating repetitive manual work so our teams can focus on core projects. The quick setup delivered immediate value.”
“The impact of ScaleOps is measurable: roughly $30k/month in compute savings since deployment, fewer OOM kills, and less manual effort to keep sizing appropriate at scale.”
“ScaleOps automatically optimizes Wiz’s containers in production according to our real-time needs, improving performance even during demand spikes. While dramatically reducing our K8s costs, the hands-free automation freed our teams from dealing with ongoing configurations, which is critical in our rapidly ever-growing environment”
“Before ScaleOps, optimizing workloads was a manual, error-prone process that often led to wasted compute and noisy alerts. Now, resource tuning is automated, data-driven, and always aligned with real usage patterns.”
“I appreciate how easy it was to install ScaleOps and how it instantly reduced the cognitive load on our application teams, making it much simpler for them to deploy their workloads effectively.”
“ScaleOps’ automation optimizes our production apps in real time, cutting cloud costs and eliminating repetitive manual work so our teams can focus on core projects. The quick setup delivered immediate value.”
“The impact of ScaleOps is measurable: roughly $30k/month in compute savings since deployment, fewer OOM kills, and less manual effort to keep sizing appropriate at scale.”
“ScaleOps automatically optimizes Wiz’s containers in production according to our real-time needs, improving performance even during demand spikes. While dramatically reducing our K8s costs, the hands-free automation freed our teams from dealing with ongoing configurations, which is critical in our rapidly ever-growing environment”
“Before ScaleOps, optimizing workloads was a manual, error-prone process that often led to wasted compute and noisy alerts. Now, resource tuning is automated, data-driven, and always aligned with real usage patterns.”
“ScaleOps drove major cloud cost savings for us. The platform is reliable, easy to deploy, and the support team is exceptional.”
“ScaleOps eliminates the manual effort of constantly tuning resource requests and limits in our Kubernetes clusters. It automatically adjusts workloads to the right size, helping us reduce over-provisioning and keep our cloud costs low.”
“Manually tuning CPU and memory requests or limits across workloads was eating up our engineers’ time. With ScaleOps automating resource optimization at the pod level, we’ve eliminated constant config changes and cut cloud costs significantly.”
“We manage over 200 Kubernetes clusters across our enterprise and ScaleOps has made it significantly easier to optimize resource utilization across all of them. ScaleOps helps keep both infrastructure usage and overall costs well under control.”
“I appreciate how easy it was to install ScaleOps and how it instantly reduced the cognitive load on our application teams, making it much simpler for them to deploy their workloads effectively.”
“ScaleOps drove major cloud cost savings for us. The platform is reliable, easy to deploy, and the support team is exceptional.”
“ScaleOps eliminates the manual effort of constantly tuning resource requests and limits in our Kubernetes clusters. It automatically adjusts workloads to the right size, helping us reduce over-provisioning and keep our cloud costs low.”
“Manually tuning CPU and memory requests or limits across workloads was eating up our engineers’ time. With ScaleOps automating resource optimization at the pod level, we’ve eliminated constant config changes and cut cloud costs significantly.”
“We manage over 200 Kubernetes clusters across our enterprise and ScaleOps has made it significantly easier to optimize resource utilization across all of them. ScaleOps helps keep both infrastructure usage and overall costs well under control.”
“I appreciate how easy it was to install ScaleOps and how it instantly reduced the cognitive load on our application teams, making it much simpler for them to deploy their workloads effectively.”
Customers Rank ScaleOps
as the Market Leader in
Autonomous Cloud
Infrastructure Optimization
Cloud Resource Management Reinvented
Cut Costs by 80%
Pay only for the cloud resources you need without compromising performance.
Boost Performance & Reliability
Ensure consistent performance and uptime, even in the most dynamic environments.
Free Your Engineers
Eliminate repeated manual tuning forever, allowing you to focus on innovation.
Frequently Asked Questions
What makes ScaleOps different from other cloud resource management solutions?
ScaleOps differentiates itself by automating the optimization of Kubernetes and cloud resources at the pod level using real-time workload and cluster signals. It continuously reacts to traffic changes, CPU throttling, OOM events, and liveness failures, rather than relying on schedules or static rules. ScaleOps preserves manifest integrity and is fully GitOps-compatible, operating transparently through a custom admission controller. It automatically applies workload-aware policies, incorporates node state to avoid risky optimizations, and provides deep observability and cost insights without disrupting production workloads.
Is ScaleOps safe to run on production workloads?
Yes. ScaleOps is designed to be safe for production workloads and includes multiple built-in safety mechanisms. It respects Pod Disruption Budgets and eviction annotations, ensuring critical pods are never disrupted. ScaleOps preserves existing manifests and GitOps workflows by operating transparently at the pod level. If ScaleOps components experience downtime, running workloads continue unaffected. The platform continuously monitors real-time signals such as OOM events, CPU throttling, and node pressure, applies production-ready policies with built-in headroom, and includes automated healing to maintain workload stability.
Does ScaleOps replace HPA, KEDA, or Cluster Autoscaler?
No. ScaleOps works with existing Kubernetes autoscaling components, including HPA, KEDA, Cluster Autoscaler, and Karpenter. It does not disable, override, or replace them. This allows teams to adopt ScaleOps without re-architecting their clusters or changing existing scaling strategies.
What types of workloads does ScaleOps support?
ScaleOps supports all Kubernetes workloads, including stateless services, stateful workloads, batch jobs, custom controllers, and JVM-based applications. It is not limited to Kubernetes-native resource types or predefined workload categories.
How does ScaleOps optimize Java and JVM-based workloads?
ScaleOps is JVM-aware and optimizes Java workloads using real-time visibility into heap usage, garbage collection behavior, and memory pressure. This enables accurate pod-level memory optimization that traditional Kubernetes tools cannot achieve due to lack of JVM context.
Can ScaleOps be used with GitOps and RBAC?
Yes. ScaleOps is fully compatible with GitOps workflows and supports CRD-based configuration and namespace-level RBAC. This allows teams to manage policies declaratively and control optimization scope without introducing operational risk.
Is ScaleOps self-hosted?
Yes. ScaleOps is fully self-hosted and runs entirely inside your Kubernetes cluster. It does not rely on an external SaaS control plane and does not require access to your cloud account or IAM permissions. This architecture minimizes security risk, keeps all optimization logic within your environment, and ensures full control over data, policies, and operational boundaries.
What Kubernetes environments and configurations does ScaleOps support?
ScaleOps supports all major Kubernetes environments, including Amazon EKS, Google GKE, Azure AKS, and self-managed or on-prem clusters. It works natively with HPA, KEDA, VPA, Cluster Autoscaler, and Karpenter, and supports GitOps workflows, namespace-level RBAC, and all workload types, including custom controllers and JVM-based applications.
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