As a DevOps Engineer, I need a native PRTG sensor to monitor the health and performance of my custom applications running in Kubernetes, so that I can gain immediate, centralized visibility into their operational status, proactively identify issues at the cluster, pod, and application level, and ensure the continuous availability and performance of my services.

1. Kubernetes-Aware Monitoring:

   • Ability to target and understand applications deployed via Kubernetes constructs (e.g., Deployments, Pods, Namespaces).
   • Provide insights into the overall health and status of application deployments (e.g., how many instances are running vs. expected).
   • Report on the status and lifecycle of individual application pods and containers (e.g., running, restarting, unhealthy probes).

2. Comprehensive Application Metrics:

   • Collect vital resource usage metrics for application containers (CPU, memory).
   • Monitor the responsiveness and availability of key application services or APIs exposed within Kubernetes.
   • Track internal application health indicators like queue depths, active connections, or pending tasks.
   • Gather application-specific error counts or critical event notifications.

3. Clear & Actionable Insights:

   • Present all collected data as distinct, clearly labeled channels within PRTG (e.g., "Deployment Status," "Pod Restarts," "API Latency," "Application Errors").
   • Automatically apply sensible default thresholds (warning/error) to these channels, which can be easily adjusted.
   • Provide clear, descriptive messages when an application or its underlying Kubernetes components are in a warning or error state, helping to quickly pinpoint the problem.

4. Easy Setup & Configuration:

   • Be discoverable and configurable directly within the standard PRTG web interface.
   • Allow straightforward selection of which Kubernetes namespaces, deployments, or application types to monitor.
   • Require minimal setup effort to connect to the Kubernetes cluster.

5. Reliability & Performance:

   • Operate efficiently without significantly impacting the performance of the monitored Kubernetes cluster or the PRTG server itself.
   • Provide consistent and reliable data collection to prevent monitoring blind spots.