Fluentd 1.15.3

Fluentd 1.15.3


Fluentd is an open-source log collector designed to handle various log data types across multiple sources, allowing users to unify their logs for better analysis and troubleshooting. It can collect, process, and route logs from various sources in real-time, and has a wide range of integrations with various platforms and services.

  • Collects log data from various sources in real-time, including Docker, Kubernetes, Syslog, and more.
  • Provides a flexible and customizable logging pipeline with over 700 plugins available.
  • Can process and transform logs with built-in filters, including parsing, buffering, and formatting.
  • Enables routing of logs to various destinations, including Elasticsearch, Amazon S3, and more.
  • Offers centralized management and monitoring of logs through a web-based GUI.
  • Provides high availability and fault tolerance through clustering and load balancing.

  • Fluentd can be used to centralize and aggregate logs from multiple sources in real time, allowing users to troubleshoot issues quickly and efficiently. For example, a company running multiple microservices on a Kubernetes cluster can use Fluentd to collect and route logs to a centralized Elasticsearch cluster for analysis and troubleshooting.
  • Fluentd can be used to process and transform logs before routing them to various destinations. For example, a user can use Fluentd to parse and filter logs generated by a web server, and then route the filtered logs to Amazon S3 for long-term storage and analysis.

  1. Install Fluentd on the desired platform or operating system.
  2. Configure Fluentd to collect logs from various sources, including Docker, Kubernetes, and more.
  3. Customize the logging pipeline with various plugins and filters to process and transform logs as needed.
  4. Configure Fluentd to route logs to the desired destination, including Elasticsearch, Amazon S3, and more.
  5. Monitor and manage logs through the web-based GUI.

  • Written in Ruby and designed to be lightweight and efficient.
  • Supports various log formats, including JSON, CSV, and Apache.
  • Offers a variety of input and output plugins to collect and route logs to various sources and destinations.
  • Provides buffering mechanisms to handle high-volume log data.
  • Offers a scalable architecture for high availability and fault tolerance.

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