Agents
Autonomous Resource Management for Agentic Workloads
Agents burst, sit idle, and fail in patterns standard resource policies don’t account for. ScaleOps automatically detects every agentic workload and manages the infrastructure under it in real time, without manual configuration.
What Agentic Workloads Get From ScaleOps
Agents are already in production. The infrastructure managing them isn’t ready for how they run.
ScaleOps manages agents the way they actually execute: spiky, bursty, and expensive to fail.
Built for how agents actually run
REAL-TIME RESOURCE OPTIMIZATION
Manages resources as the workload changes, not after it crashes.
No static configurations. No manual tuning.
Agentic workloads spike unpredictably. The same agent can sit near-idle between tasks, then demand a burst of CPU and memory with no warning. ScaleOps tracks live usage per pod and manages requests continuously, giving every agent exactly what it needs at each stage of execution.
AUTOMATIC AGENT DETECTION
Detected on arrival.
Optimized from day one.
Toggle from manual to automated with no redeploy.
New agentic workloads show up the moment ScaleOps detects them, already tagged for the policy that matches their behavior. Enable automation and ScaleOps takes over rightsizing and all resource management.
AGENT COST INTELLIGENCE
Costs tracked to the agent, workflow, and user
Runaway loops get killed before they drain spend.
Every agent loop carries the full conversation history forward, so cost compounds silently until the bill arrives with no attribution. ScaleOps tracks token spend in real time, routes calls between models based on task complexity, and enforces budget caps, all inside the platform already managing your infrastructure.
AGENTIC WORKLOAD OBSERVABILITY
Infrastructure and application signals in one view
Troubleshoot the cause, not the symptom.
Agents alternate between full-throttle execution and near-idle waiting. Standard resource policies treat that variation as noise and overprovision for the worst case. ScaleOps shows you what each agent is actually doing, so you’re debugging from the full picture instead of a partial one.
The infrastructure layer your agents actually need.
An agent isn’t a normal workload. It’s a chain that decides its own path.
An agent runs a loop: observe, think, act, repeat. At every step, it calls the LLM to reason about what to do next, then calls a microservice to act on that reasoning. The LLM decides which service, and whether to call it at all. One user request fans out into many steps, many calls, many pods. And every step in that chain is a workload running on your cluster.
Boot-time optimization
Agent pods need more CPU at startup than at steady state. ScaleOps raises CPU requests during the boot window and reverts to steady-state values once the workload stabilizes, per pod, without configuration.
Real-time burst reaction
When usage spikes, ScaleOps manages CPU and memory requests in real time to prevent throttling and OOM kills, keeping agent tasks performant through the burst.
Automatic pod healing
ScaleOps detects CPU throttling, memory pressure, and node stress on agent pods and resolves them in real time, before they interrupt an in-flight task.
In-place pod resize
Agent tasks lose state and fail if the pod restarts mid-execution. ScaleOps resizes CPU and memory on running agent pods in place, so resource changes never trigger a restart or eviction.
Ephemeral storage optimization
Agent pods that exceed ephemeral storage limits get evicted, taking in-flight task state with them. ScaleOps rightsizes ephemeral storage to real usage and flags out-of-storage conditions before they trigger an eviction.
Replica threshold optimization
HPA thresholds on inference workloads tend to get set conservatively once and left alone. ScaleOps analyzes how each workload’s latency responds to CPU load, finds the highest threshold it can sustain without breaching SLA, and applies it automatically.
Batch inference optimization
ScaleOps schedules async inference jobs against deadlines on the cheapest available GPU capacity at execution time, replacing always-on reservations and static schedules.
AI inference visibility
ScaleOps surfaces time-to-first-token, throughput, tail latency, cache hit rate, and request queue depth for every inference workload behind your agents, alongside GPU cost and utilization in the same view.
Here’s what our users have to say about ScaleOps
“Out of all the vendors we tested, ScaleOps’ rightsizing solution was by far the most advanced. Nothing else we evaluated matched the depth or control.”
“With a two-minute installation and zero effort, ScaleOps has provided Coralogix with a hands-free experience, improving performance while reducing cost. The automation has reduced overhead, allowing our engineering team to concentrate on what truly matters.”
“ScaleOps helps reduce cloud costs significantly without affecting performance”
“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.”
“ScaleOps makes Kubernetes resource management effortless. Its recommendations are accurate, automation is reliable, and the UI provides instant clarity on where optimization is needed. We’ve significantly reduced wasted resources and improved performance stability since adopting it.”
“ScaleOps solved the challenges we were facing with managing and scaling our Kubernetes workloads. The hands-free automation, combined with 75% cost savings, has been a real game changer for At-Bay.”
“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%”
“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.”
“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.”
“ScaleOps allows us to dramatically reduce costs and keep our cloud bill in check.”
“Out of all the vendors we tested, ScaleOps’ rightsizing solution was by far the most advanced. Nothing else we evaluated matched the depth or control.”
“With a two-minute installation and zero effort, ScaleOps has provided Coralogix with a hands-free experience, improving performance while reducing cost. The automation has reduced overhead, allowing our engineering team to concentrate on what truly matters.”
“ScaleOps helps reduce cloud costs significantly without affecting performance”
“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.”
“ScaleOps makes Kubernetes resource management effortless. Its recommendations are accurate, automation is reliable, and the UI provides instant clarity on where optimization is needed. We’ve significantly reduced wasted resources and improved performance stability since adopting it.”
“ScaleOps solved the challenges we were facing with managing and scaling our Kubernetes workloads. The hands-free automation, combined with 75% cost savings, has been a real game changer for At-Bay.”
“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%”
“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.”
“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.”
“ScaleOps allows us to dramatically reduce costs and keep our cloud bill in check.”
“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.”
“Before ScaleOps, managing workload scaling required constant tweaking and monitoring. Now, it’s completely automated. We spend less time managing infrastructure and more time building products. It’s made our Kubernetes environment far more efficient and predictable.”
“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.”
“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. The troubleshooting features are excellent and have proven invaluable when assisting assisting our app teams.”
“ScaleOps automation has improved reliability, helping us maintain consistent application performance even during periods of high demand.”
“ScaleOps drove major cloud cost savings for us. The platform is reliable, easy to deploy, and the support team is exceptional.”
“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”
“Very easy to get started and implement. Great customer support, we have a dedicated Slack channel where we get responses very quickly. ScaleOps keeps adding more and more useful features.”
“Great optimization tool for EKS, awesome team to work with, and easy deployment.”
“Out of all the vendors we tested, ScaleOps’ rightsizing solution was by far the most advanced. Nothing else we evaluated matched the depth or control.”
“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.”
“Before ScaleOps, managing workload scaling required constant tweaking and monitoring. Now, it’s completely automated. We spend less time managing infrastructure and more time building products. It’s made our Kubernetes environment far more efficient and predictable.”
“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.”
“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. The troubleshooting features are excellent and have proven invaluable when assisting assisting our app teams.”
“ScaleOps automation has improved reliability, helping us maintain consistent application performance even during periods of high demand.”
“ScaleOps drove major cloud cost savings for us. The platform is reliable, easy to deploy, and the support team is exceptional.”
“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”
“Very easy to get started and implement. Great customer support, we have a dedicated Slack channel where we get responses very quickly. ScaleOps keeps adding more and more useful features.”
“Great optimization tool for EKS, awesome team to work with, and easy deployment.”
“Out of all the vendors we tested, ScaleOps’ rightsizing solution was by far the most advanced. Nothing else we evaluated matched the depth or control.”
Fits your stack. Doesn’t change it.
Runs alongside your existing stack
Coordinates with HPA, KEDA, Karpenter, and Cluster Autoscaler. Never disables or replaces them.
Nothing leaves your cluster
Fully self-hosted, no sidecars, no data egress. RBAC and namespace boundaries respected.
Built for production
If ScaleOps components go down, your running agents continue unaffected.
Run ScaleOps on any Kubernetes environment
Instant Value with Seamless Automation