What is filebeat?

Filebeat is a lightweight program (called a “shipper”) that runs on your servers and watches log files. Whenever new lines are added to those files, Filebeat reads them and sends the data to a central place, such as Elasticsearch or Logstash, for storage and analysis.

Let's break it down

  • Lightweight agent: It uses very little CPU and memory, so it can run on many machines without slowing them down.
  • Tail‑like behavior: Like the Unix tail -f command, it continuously follows the end of a file and picks up new entries as they appear.
  • Modules: Pre‑built configurations for common log sources (e.g., Apache, Nginx, MySQL) that automatically parse and structure the data.
  • Outputs: Sends logs to destinations like Elasticsearch, Logstash, Kafka, or a file.
  • Registry: Keeps track of which part of each file it has already sent, so it never loses data even after a restart.

Why does it matter?

  • Centralized logging: Makes it easy to collect logs from many servers in one place, which is essential for troubleshooting and security monitoring.
  • Scalable: Because it’s tiny, you can deploy thousands of Filebeat agents without heavy resource costs.
  • Structured data: Modules turn raw text into structured fields, enabling powerful search and visualization in tools like Kibana.
  • Reliability: The registry ensures no log lines are missed or duplicated, even if the agent crashes or the server reboots.

Where is it used?

  • In DevOps pipelines to gather application and system logs from web servers, containers, and virtual machines.
  • In security operations centers (SOC) to feed logs into SIEM systems for threat detection.
  • In cloud environments (AWS, Azure, GCP) to collect logs from instances, Kubernetes pods, and serverless functions.
  • In any organization that needs a simple, low‑overhead way to ship logs to the Elastic Stack or other log‑processing platforms.

Good things about it

  • Very low resource consumption.
  • Easy to install and configure, especially with ready‑made modules.
  • Works well with the Elastic Stack, providing seamless integration.
  • Handles log rotation and file renames automatically.
  • Supports backpressure handling, so it won’t overwhelm the destination when traffic spikes.

Not-so-good things

  • Limited processing power: It can’t do complex transformations; for that you need Logstash or another processor.
  • Primarily designed for the Elastic ecosystem; using it with non‑Elastic destinations may require extra setup.
  • Configuration can become cumbersome when managing many custom log formats.
  • No built‑in UI; you need external tools (Kibana, Grafana, etc.) to view and analyze the data.