Autonomous Kubernetes Pod Rightsizing
Maximize Performance and Cut Costs by 80%. Autonomously.
Kubernetes pods reserve significantly more CPU and memory than they consume. ScaleOps continuously rightsizes pod resource requests in real time, based on live workload behavior and cluster conditions. Production stays stable. Cloud spend drops by up to 80%.
Real-Time Pod Rightsizing
ScaleOps rightsizes pod CPU and memory requests in real time, tracking how each workload actually behaves under live cluster conditions. Your workload policies and resource guardrails stay intact. No manual YAML. No reactive firefighting.
Context-Aware Policy Detection
From stateless microservices to Spark, Kafka, and custom jobs, ScaleOps detects workload type and applies the right optimization policy automatically. It reads runtime behavior and live cluster signals. No custom rules. No tuning. No configuration.
One Helm command.
Instant savings.
Automatic Pod Healing
ScaleOps detects CPU throttling, OOM kills, stressed nodes, noisy neighbors, and failing health probes, and resolves them as they happen. Performance degradation is intercepted before it reaches production.
Real-Time Burst Reaction
When demand spikes, ScaleOps provisions additional CPU and memory based on live cluster signals. Performance, uptime, and SLAs hold under load.
Vertical Scaling Without HPA Conflicts
ScaleOps runs alongside HPA and KEDA with no configuration required. Vertical rightsizing happens underneath. Horizontal scaling stays in your control. Unlike the open-source VPA, which conflicts with HPA, ScaleOps preserves your existing scaling strategy.
Rightsize Every Pod,
Autonomously.
Autonomous Ephemeral Storage Optimization
Ephemeral storage issues silently cause pod evictions, node pressure, and wasted capacity. ScaleOps continuously rightsizes ephemeral storage based on actual usage, prevents storage exhaustion before evictions are triggered, and provides cluster-wide visibility into storage requests, limits, and capacity.
Rightsize DaemonSets for Every Node
DaemonSet resource requests are not one-size-fits-all. A single recommendation across every node size wastes capacity on larger nodes and risks throttling on smaller ones. ScaleOps rightsizes each DaemonSet per node, aligning resources to real usage across the cluster.
In-Place Pod Resize
ScaleOps natively supports Kubernetes In-Place Pod Resize. CPU and memory on running production workloads stay aligned with real demand. No restarts. No evictions. No rollouts.
GitOps-Native Control
ScaleOps integrates with GitOps workflows. All platform actions are defined and managed as code. Fine-grained control extends across workloads, namespaces, and clusters. ScaleOps works out of the box with Argo CD, Flux, and any CI/CD pipeline.
Auto-Detect Custom Workloads
ScaleOps supports workloads built in-house and operators not found in the standard ecosystem. Custom CRDs, internal job runners, and one-off deployments are detected automatically. No manual onboarding per workload type.
Cloud Resource Management Reinvented
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.
Cut Costs by 80%
Pay only for the cloud resources you need without compromising performance.
Run ScaleOps on any
Kubernetes Environment
Native deployment options across every major cloud and managed Kubernetes service, including EKS, AKS, GKE, OpenShift, on-prem, and air-gapped environments. Fully self-hosted.
Kubernetes Pod Rightsizing FAQ
What is automated pod rightsizing in Kubernetes?
Automated pod rightsizing continuously sets CPU and memory requests and limits for Kubernetes pods to match real workload demand. ScaleOps observes each workload’s actual behavior in live production and corrects over-provisioned allocations as they drift. Over-provisioning that wastes cloud spend is eliminated. Under-provisioning that causes throttling and OOM kills is prevented. Resource allocations stay aligned with actual usage as workloads change.
How is ScaleOps different from the Kubernetes Vertical Pod Autoscaler (VPA)?
The open-source Kubernetes VPA is not recommended for production by the project itself. It relies only on historical pod usage, requires manual tuning, conflicts with HPA, and does not support custom workloads. ScaleOps is built independently of the VPA codebase. It uses live cluster context, including node health, noisy neighbors, and event signals alongside historical data, to manage CPU and memory requests in real time. ScaleOps also runs alongside HPA and KEDA without conflicts and supports custom workloads out of the box.
Does ScaleOps restart pods when rightsizing?
ScaleOps does not restart running pods to apply rightsizing changes. For most workloads, optimized CPU and memory requests take effect when a new pod is created. ScaleOps also supports native Kubernetes In-Place Pod Resize, which manages CPU and memory on running pods without evictions or restarts. ScaleOps stays safe for production environments where pod restarts would disrupt traffic, break SLAs, or trigger cascading scaling events.
Does ScaleOps work with HPA and KEDA?
Yes. ScaleOps runs alongside Horizontal Pod Autoscaler (HPA) and KEDA out of the box, with no extra configuration required. ScaleOps handles vertical scaling of CPU and memory. HPA and KEDA continue to manage replica counts. The long-standing conflict between vertical and horizontal scaling in Kubernetes, the reason VPA and HPA can’t safely run together, does not apply with ScaleOps. Existing scaling strategy stays in place and becomes more efficient as pods are continuously rightsized.
How does ScaleOps handle traffic spikes and bursts in real time?
When demand surges, ScaleOps provisions additional CPU and memory based on live cluster signals rather than waiting for historical patterns to update. The same real-time awareness powers automatic pod healing for throttling, OOM kills, and node pressure, so workloads stay responsive during high-load events while the smaller resource footprint that drives cost savings holds.
Is automated pod rightsizing safe for production environments?
ScaleOps is built for production Kubernetes from the ground up. Real-time context awareness, automatic pod healing, and policy controls that respect existing guardrails keep workloads stable as ScaleOps manages resources. Companies including Salesforce, DocuSign, Wiz, and Coupa run ScaleOps in production across thousands of clusters and critical workloads. Built-in disruption monitoring lets platform teams validate stability before expanding automation across the cluster.
How much can automated pod rightsizing save on Kubernetes costs?
ScaleOps delivers up to 80% reduction in Kubernetes resource costs by continuously matching CPU and memory to real workload demand and consolidating workloads onto fewer nodes through intelligent bin-packing. Actual savings depend on cluster size, workload variability, and current provisioning practices. Customers running ScaleOps in production typically see significant reductions in cloud spend within days of automation while application performance holds or improves.
Instant Value with Seamless Automation