Less toil. Fewer incidents.
More reliable infrastructure.
Kubex uses predictive machine learning to continuously monitor resource behavior across your entire fleet, and acts to prevent resource misconfigurations before they cause incidents. By automating remediation, Kubex eliminates the work that fills your queue, keeping infrastructure running optimally.
The Problem
Many incidents are resource problems in disguise. OOMKills, pod evictions, throttled containers, and cascading failures often trace back to the same root cause: resource configurations that don’t reflect how services actually behave or what they need. Your team remediates the same classes of issues frequently because the underlying misconfigurations are never fixed at scale, or are bound by one-size-fits-all configurations coming from upstream.
Kubex eliminates the root cause. It continuously profiles real workload behavior and autonomously adjusts resource configurations across your infrastructure so the incidents don’t recur, and your team gets time back.
SOUND FAMILIAR?
“We keep fixing the same incidents. The configs are wrong but nobody has time to fix all of them properly.”
Kubex closes the loop. Instead of waiting for incidents to surface misconfigured workloads, it continuously corrects resource profiles across your fleet, governed by your policies, so reliability improves automatically, not reactively.
How It Works
Continuous autonomous optimization, governed by your policies.
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Analyze
Ingests real-time and historical metrics across all namespaces, clusters, and workload types — building predictive behavioral models for every service. Models down to the container, enabling optimization of individual components even if they are launched from the same template.
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Optimize
Calculates optimal sizing, identifies bottlenecks, and uses advanced agents to predictively recommend tuning for schedulers, autoscalers, cloud scale groups and other components.
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Automate
Applies changes autonomously within policy guardrails, predictively adjusting requests, limits, and autoscaling parameters to keep things running safely. Automation controller can mutate or in-place resize at the individual container level, taking optimization to the next level.
Capabilities
What autonomous optimization covers.
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Incident Prevention
Continuously identifies workloads at risk of OOMKill, eviction, or throttling and corrects resource configurations before they cause service degradation or outages.
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Toil Reduction
Eliminates repetitive remediation tasks from your on-call queue. Kubex handles the routine resource correction work autonomously, freeing your team for higher-value engineering.
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Rightsizing for Stability
Profiles actual CPU and memory usage per workload and continuously adjusts requests and limits to maintain safe headroom, without over-provisioning across the fleet.
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Autoscaling Reliability
Tunes HPA and node autoscaler configurations based on real traffic patterns, reducing the risk of scaling failures, cold-start latency spikes, and capacity shortfalls under load.
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Root Cause Attribution
Surfaces the resource configuration patterns driving recurring incidents, so your team can address systemic issues, not just individual alerts.
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Proactive Anomaly Detection
Detects abnormal resource consumption patterns, quota risks, and scheduling pressure before they cascade into incidents, with context to act fast.
Results
What SRE teams achieve with Kubex.
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Fewer
OOMKills, evictions & throttling incidents across the fleet
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90%
Reduction in manual resource remediation toil per sprint
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< 1 Day
To full fleet visibility and proactive risk detection
Control & Governance
Autonomous doesn’t mean uncontrolled. Human in the loop provision allows you to stay on top of automation and changes. Sensitive workloads can be placed in recommendation-only mode. Everything Kubex does is logged, auditable, and reversible.
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What you control
- Optimization scope by namespace, workload class, or service tier
- Resource bounds and headroom buffers per criticality level
- Production freeze windows and excluded workloads
- Rate and magnitude of resource changes
- Rollback triggers and automatic revert conditions
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What Kubex handles autonomously
- Continuous rightsizing to prevent OOMKills and throttling
- Autoscaler tuning for stability under variable load
- Proactive risk detection and pre-incident correction
- Routine remediation tasks removed from on-call queues
- Rollback if post-change reliability metrics degrade
See fewer incidents. Reclaim your on-call time.
See Kubex in action for yourself or talk to our team about the reliability of your environment. Most teams have proactive risk detection and autonomous remediation running within
days of deployment.
