kubernetes-event-exporter 1.1.0

• Collects Kubernetes events: Kubernetes-event-exporter collects events from Kubernetes and stores them in a format that can be easily exported.
• Converts events to Prometheus metrics: The tool converts Kubernetes events to Prometheus metrics, allowing users to monitor and visualize them in real-time.
• Export to various monitoring systems: Kubernetes-event-exporter can export data to various monitoring systems, such as Prometheus and Grafana.
• Customizable metrics: Users can customize the metrics that are collected and exported to better suit their monitoring needs.
• Highly scalable: The tool is designed to handle large amounts of Kubernetes events and can be deployed across multiple nodes for improved scalability.
• Easy to use: Kubernetes-event-exporter is easy to set up and use, with minimal configuration required.

• Kubernetes event monitoring: Kubernetes-event-exporter is particularly useful for monitoring Kubernetes events, which can provide valuable insights into the health and performance of Kubernetes clusters. With the ability to convert events to Prometheus metrics, users can easily monitor and visualize this data in real-time.
• Alerting and troubleshooting: By exporting Kubernetes events to monitoring systems such as Prometheus, users can set up alerts to notify them of potential issues or failures. The tool can also be used to troubleshoot issues by providing detailed insights into the events occurring within the Kubernetes cluster.

To use Kubernetes-event-exporter, users can follow these basic steps:

1. Install and configure the tool on the Kubernetes cluster.
2. Configure the metrics that need to be collected and exported.
3. Export the metrics to a monitoring system such as Prometheus.
4. Set up alerts or dashboards to monitor the metrics in real-time.

• Written in Go language
• Uses the Kubernetes API to collect events
• Supports exporting to Prometheus and Grafana
• Provides a variety of customizable metrics
• Can be deployed as a Kubernetes deployment or daemonset
• Lightweight and highly scalable