Kubernetes performance monitoring: Clusters, Pods and more

Get telemetry from across your Kubernetes Cluster, Nodes and Pod deployments, along with code-level visibility of applications running inside your containers. eG Enterprise correlates performance metrics from your IT infrastructure and applications to pin-point the root-cause of slowdowns and bottlenecks.

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The challenges of Kubernetes monitoring

Kubernetes offers power and flexibility, but its dynamic and ephemeral nature breaks traditional monitoring models. Pod restarts, resource contention, and scheduling failures can occur rapidly across distributed Nodes, making issues difficult to detect and resolve before they impact application performance and availability. Since infrastructure, orchestration, and applications are tightly coupled, faults in one layer can quickly cascade through the entire stack. For example, a missed readiness probe or slow-starting container can trigger delays far beyond its origin if not addressed promptly.

Legacy monitoring tools were built for static, long-lived servers — not for ephemeral workloads. Open-source, do-it-yourself (DIY) stacks offer flexibility but lack built-in correlation across metrics, logs, and traces. To troubleshoot issues, IT teams must rely on several consoles and use query languages to piece together root causes — this adds time and risk during triage. To operate reliably at scale, Kubernetes environments require observability that is full-stack, unified, and out of the box.

Next generation monitoring solution for your Kubernetes ecosystem

issues, IT teams must rely on several consoles and use query languages to piece together root causes — this adds time and risk during triage. To operate reliably at scale, Kubernetes environments require observability that is full-stack, unified, and out of the box.

Full-Stack observability for Kubernetes environments

eG Enterprise is an enterprise-class, converged application and IT monitoring solution that provides unified visibility into Kubernetes environments, the containers provisioned, and workloads running on them.

Ensure peak performance of Kubernetes Clusters and containerized applications.
Single pane of glass to monitor Clusters, Nodes, containers, applications and more, whether on-premises or in the cloud.
Troubleshoot fast by correlating signals across infrastructure, orchestration, and application layers.
Touch-free monitoring: Auto-discover dynamic workloads instantly across Pods, Nodes, and services.

Be proactive: Monitor control plane health including API server latency, Pod scheduling issues, and etcd slowness.
Optimize costs by right-sizing your Clusters using metrics on Pod resources, limits, utilization, and saturation trends.

eG Enterprise auto-discovers Nodes, Pods, services, and control plane components across major Kubernetes platforms such as EKS, AKS, GKE, Rancher, vSphere Kubernetes and OpenShift, enriching telemetry with contextual tags such as Pod names, labels, and namespaces.

Continuously analyze Kubernetes Cluster health

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Identify early indicators of capacity strain and application instability.

Get a unified view of your entire Kubernetes estate across diverse cloud and on-prem Clusters.
Detect early signals of saturation, memory pressure, CPU throttling, disk and network abnormalities, and Pod eviction trends.
Surface critical conditions such as disk pressure, memory pressure, PID pressure to ensure the stability of your Clusters.

Uncover hidden failures in the Kubernetes Control Plane

From API lag to scheduling delays, surface orchestration issues in real time.

Monitor and analyze latency across API server, scheduler, controller-manager, kubelet, kube-proxy, kube-dns, and etcd.
Uncover control plane anomalies by consolidating failures, evictions, volume, scheduling, and unready Node events for comprehensive operational visibility.
Visualize system events, logs, and critical metrics across the control plane.

Monitor and scale Kubernetes workloads with confidence

Spot inefficient workloads by automatically comparing CPU/memory usage vs. requests to uncover over-provisioning or saturation risks. Workload metrics are auto-baselined, with alerts triggered on anomaly detection.
Drill into workload readiness issues and inspect Pod health down to the container level — catching delays, restarts, or unready states before they escalate.
Track deviations using dynamic baselines — no custom queries or manual dashboards are required. Alerts are triggered when usage falls outside expected range, highlighting wastage or saturation.

Visually compare past throttling, eviction, or memory pressure events to spot slow-building risks.

Connect application issues to container and Kubernetes orchestration anomalies

Easily see the impact of application-level issues like memory pressure and runaway threads on container performance signals such as OOM kills and container crashes.
Detect critical issues impacting overall responsiveness, including readiness probe failures, garbage collection (GC) pauses, and thread stalls.
Visualize the cascading impact of infrastructure stress, orchestration lag, and application runtime delays on user experience.

Turnkey and enterprise-ready observability for Kubernetes

Benefit from a simple and predictable licensing model for Kubernetes deployments. Monitor the infrastructure using Node-based pricing, irrespective of Node configurations. Application workload monitoring is priced by concurrent applications.
Deployment can be on-premises, in any cloud, or as fully managed secure SaaS.
Multi-tenancy is supported for MSPs and similar use cases.

Deployment is straightforward, with support for the eG Innovations Universal Agent Operator for Kubernetes, Helm, and YAML manifests. It also supports private registries to ensure security and software integrity.
With 650+ out-of-the-box application monitoring integrations and built-in intelligence, eG Enterprise simplifies end-to-end Kubernetes observability.
Ready-to-go live and historical reports plus a GUI custom report builder. No query languages required.

Answer key performance questions about Kubernetes

How is the health and availability of the Kubernetes deployment?
Are all Master Node services running as expected?
Are there any failed Container images while pulling from the image repository?
What is the overall view of the Cluster in terms of Pod allocation, Deployment status, CPU, and memory allocation?
Are DaemonSets unavailable on any Nodes?
What is the status of Namespaces and Services? Are they properly mapped to their corresponding Pods?

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Works on cloud environments, hybrid cloud setups and on-premises deployments
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Suitable for monitoring cloud applications, digital workspaces and IT infrastructures