EFKP Stack on Kubernetes

Overview

This project provides the necessary configuration files and instructions to deploy a bare-metal Elastic, Fluentd, Kibana, and Prometheus (EFKP) stack on Kubernetes. This stack is designed to offer a comprehensive monitoring and logging solution that can be used for gathering insights from your Kubernetes clusters.

Features

• Elasticsearch: A distributed, RESTful search and analytics engine capable of addressing a growing number of use cases.
• Fluentd: An open-source data collector for unified logging layer, allowing you to unify data collection and consumption for better use and understanding of data.
• Kibana: A data visualization and exploration tool used for log and time-series analytics, application monitoring, and operational intelligence use cases.
• Prometheus: An open-source monitoring system with a dimensional data model, flexible query language, efficient time series database, and modern alerting approach.

Prerequisites

• A Kubernetes cluster
• kubectl access configured for your cluster
• Basic knowledge of Kubernetes resource and network configurations
• Metrics/telemetry visualizer (to point at prometheus), I used Grafana for my testing

Installation and Configuration

The setup process involves several steps, from initializing your cluster to deploying each component of the EFKP stack.

Usage

Once deployed, you can access Kibana and Prometheus web UIs to explore logs, metrics, and data visualizations.

Contributing

Contributions to the project are welcome!

License

This project is licensed under the MIT License.

Acknowledgements

• Kubernetes and CNCF Projects
• Elastic.co for Elasticsearch and Kibana
• Fluentd contributors
• Prometheus project contributors