Run your K8s workloads
on auto-pilot
The ScaleOps platform simplifies Kubernetes resource management by automatically adjusting nodes and pods to match real-time demand.
Automated Real-Time Pod Rightsizing
ScaleOps automates resource requests and limits per pod based on real-time demand, freeing engineers from repeated manual tuning of CPU and memory allocation across the cluster. This results in up to 80% cloud cost savings.
- •Workload Policy Auto Detection
ScaleOps automatically applies the most suitable scaling policy for every workload based on real-time requirements, eliminating manual work. This ensures compliance and effective resource management across environments with zero onboarding time.
- •Auto-Healing and Fast Reaction
Proactive and reactive mechanisms automatically mitigate issues caused by sudden, unexpected bursts and stressed nodes, ensuring stability and performance.
- •Supports any Workload Type
ScaleOps offers flexible compatibility with diverse workloads, including Jobs, CronJobs, GitHub runners, Argo Rollouts, Spark, Flink batch jobs, and more.
- •Automatic Integration with HPA, KEDA and GitOps
Optimize vertical scaling for workloads with horizontal scaler without manual intervention and integrate effortlessly with any GitOps workflow, including popular tools like ArgoCD and Flux.
Start saving in minutes, not days
Automated Smart Pod Placement
ScaleOps automates and optimizes the placement of unevictable pods by ensuring pods are correctly allocated on the best nodes to allow underutilized nodes to scale down, resulting in dramatic cloud cost savings by up to 50% without sacrificing performance.
- •Bin-Pack Unsafe-to-Evict and PDB Restricted Workloads
ScaleOps places pods that can’t be moved to other nodes due to limitations, which may prevent the cluster autoscaler or Karpenter from bin-packing your cluster efficiently.
- •Bin-Pack Ownerless and Kube-System Pods
These pods often pose scheduling challenges, but ScaleOps manages their placement to ensure everything runs smoothly. This feature helps reduce Kubernetes resource waste, maintaining optimal utilization across clusters without manually tracking these pods.
- •Seamless Respecting Taints & Affinities
ScaleOps respects any restrictions or affinities and doesn’t override any settings. You can simply automate the optimization for pod placement and no longer have any blockers from scaling your nodes down.
Here’s what people are saying about us
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
ScaleOps’ automation optimizes our online applications in production to efficiently meet real-time demand. The significant reduction in cloud costs and elimination of repeated manual work have freed our teams, enabling them to focus on core projects. The fast time to value, particularly after the quick installation, has been immediately beneficial. Additionally, the availability of a 24/7 responsive team of experts is extremely valuable.
Engineers should prioritize working on business logic instead of continually monitoring and configuring infrastructure settings, such as CPU and Memory requests/limits adjustments. Automation of this aspect is essential, and ScaleOps aids in achieving that, resulting in substantial cost savings on cloud instances and significant time savings
ScaleOps automatically manages our resources and continuously optimizes our production workloads in response to demand. This platform has resulted in significant savings, all through a hands-free experience.
ScaleOps’ automation continuously optimizes our containers on production to meet real-time demand. The 2-minute installation was straightforward, and the immediate value was clear. It’s significantly reduced operational overhead, freeing our teams to focus on more strategic initiatives, while reducing our cloud cost by over 50%
Cluster Level & Workload Level Troubleshooting
ScaleOps provides dashboards and tools for diagnosing issues from cluster-level to specific workloads, enhancing visibility and enabling proactive management.
- •Performance-Related Monitoring
Real-time monitoring for OOM (out-of-memory) events, CPU throttling, and other performance-critical metrics enables proactive workload management.
- •Cost-Related Insights
ScaleOps tracks resource allocation inefficiencies, helping teams identify and adjust costly workloads. It highlights resource over-provisioning and idle resources, essential for cost-conscious environments.
- •Alerts and Insights
Quickly identify and catch issues before they become a real problem
Your workloads, for 80% less
K8s Cost Monitoring
ScaleOps offers a comprehensive view of compute, network, and GPU costs, enabling better cloud spend management and significant saving
- •Compute Costs
Costs are aggregated across clusters, namespaces, labels, and annotations and can display potential savings at each level.
- •Network Costs
Monitors network costs across different traffic types, including cross-zone traffic, with customizable filters by workload property and time period.
- •GPU Costs
Reports on GPU allocation, identifying inefficient GPU usage and idle time, with detailed views on GPU memory usage, ensuring cost-effectiveness for GPU-heavy workloads.
