Comparison of ELK, EFK, and PLG Logging Systems and Their Architectural Differences

The author, a senior architect, introduces three popular logging solutions—ELK, EFK, and PLG—and compares their architectures and use cases.

1. ELK Logging System

The classic Elastic Stack consists of Elasticsearch, Logstash, Kibana, and Beats. Beats collect logs, Logstash aggregates and processes them, Elasticsearch stores and indexes the logs, and Kibana provides a visual front‑end.

Beats – log collection

Logstash – log aggregation and processing

Elasticsearch – storage and search

Kibana – visualization

2. EFK Logging System

In containerized (especially Kubernetes) environments, the EFK stack replaces Logstash with Fluent Bit. Fluent Bit is a lightweight, multi‑platform log processor and forwarder that can collect data from various sources, forward to multiple destinations, and works seamlessly with Docker and k8s.

Collect logs from different sources

Forward to multiple destinations

Fully compatible with Docker and Kubernetes

3. PLG Logging System

Grafana Labs promotes the PLG stack—Promtail, Loki, and Grafana—as a modern alternative. Loki stores only log labels (metadata) and does not index full log messages, reducing storage cost and improving efficiency. Promtail collects logs and attaches labels, while Grafana visualizes both metrics and logs.

4. PLG vs ELK

1. ES vs Loki

Elasticsearch stores logs as unstructured JSON objects and indexes every field, enabling powerful full‑text search. Loki, inspired by Prometheus, stores logs with a set of labels only; the raw log content is not indexed, which lowers operational cost but requires LogQL for content queries.

2. Fluentd vs Promtail

Promtail is purpose‑built for Loki. It discovers Kubernetes pods, reads local log files, and attaches the same label scheme used by Prometheus, allowing unified metric and log tagging.

3. Grafana vs Kibana

Kibana offers rich visualizations and machine‑learning features for log analysis. Grafana focuses on time‑series data and can display both metrics (from Prometheus) and logs (from Loki) on the same dashboard.

The article also contains promotional material for a ChatGPT‑related community, private accounts, and various paid services, but the core technical content remains a comparative guide to modern logging stacks.