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Kubex is an infrastructure optimization platform for Kubernetes and AI environments. It turns telemetry and usage patterns into actionable recommendations for container CPU, memory, GPU, and ephemeral storage resources. It also provides visibility into nodes and node groups, including recommended node families in the Kubex UI, and helps teams apply configured changes through governed automation. Whether you are evaluating Kubex, connecting your first cluster, or scaling optimization across environments, this page is the best place to start.
Kubex optimization and automation value graph

Figure: Value Achieved with Kubex

Choose your starting point

Use the path that matches what you need to do next:

What Kubex helps you do

Kubex brings discovery, analysis, and action into one workflow:
  1. Collect Kubernetes and infrastructure telemetry from your connected environments.
  2. Analyze usage, capacity, cost, and risk to identify the highest-value opportunities.
  3. Recommend resource and configuration changes based on observed behavior and optimization policies.
  4. Apply changes through automation that adapts quickly to workload conditions, or update deployment templates through a GitOps workflow.
  5. Review optimization results through Kubex dashboards and monitor automation status in the cluster.
Kubex workflow from data collection through optimization and automation

Figure: How Kubex works

Core capabilities

Kubernetes optimization

  • Right-size container CPU and memory requests and limits based on workload behavior.
  • Optimize nodes and node groups to improve utilization, capacity planning, and cost efficiency.
  • Identify health and saturation risks before they become performance incidents.
  • Explore recommendations through dashboards, analysis tables, filters, and utilization charts.

AI and GPU infrastructure optimization

Improve utilization of expensive AI infrastructure by considering GPU allocations alongside CPU, memory, storage, scheduling, and workload demand. See GPU Optimization for the GPU-specific workflow.

Governed automation

Use the Kubex Automation Engine to apply container recommendations at scale. Policies define what can change and under which conditions, while safety controls evaluate constraints such as HPA, LimitRange, ResourceQuota, PodDisruptionBudget, workload readiness and node capacity. Read Automation Engine Safety and Operations before moving from recommendations to automated changes.

Shared operational context

Kubex gives SRE, platform engineering, FinOps, and application teams a common view of infrastructure decisions. Recommendations include technical context so teams can connect cost and efficiency improvements to reliability and performance goals.
Kubex Kubernetes overview dashboard

Figure: K8s Overview Dashboard

Common outcomes

Reduce waste without guessing

Identify overprovisioned workloads and right-size requests and limits to recover unused capacity while preserving application performance.

Improve reliability and headroom

Use data-driven recommendations to reduce saturation risk, improve headroom planning, and prevent avoidable performance incidents.

Operate consistently at scale

Standardize optimization across clusters and environments with policies, scheduling windows, safety checks, and auditable automation workflows.

Connect technical work to business value

Give engineering and FinOps teams a shared view of opportunities, expected impact, and results instead of relying on disconnected reports.

Who should use Kubex?

  • SRE and platform engineering: improve cluster efficiency while protecting reliability and operational control.
  • FinOps and cloud operations: identify measurable savings opportunities with the technical context needed to act on them.
  • Engineering leaders: establish repeatable optimization practices across teams and environments.
  • AI platform teams: improve the utilization and planning of GPU-backed workloads.

Explore the documentation

Kubex analyzes data from your connected environments. Start with Data Collection Overview to deploy the collection stack, or review Supported Platforms and Integrations to confirm that your environment is supported.