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README.md

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file.d

Overview

Maintenance CI Code coverage GitHub go.mod Go version of a Go module GoReportCard example

file.d is a blazing fast tool for building data pipelines: read, process, and output events. Primarily developed to read from files, but also supports numerous input/action/output plugins.

⚠ Although we use it in production, it still isn't v1.0.0. Please, test your pipelines carefully on dev/stage environments.

Contributing

file.d is an open-source project and contributions are very welcome! Please make sure to read our contributing guide before creating an issue and opening a PR!

Motivation

Well, we already have several similar tools: vector, filebeat, logstash, fluend-d, fluent-bit, etc.

Performance tests state that best ones achieve a throughput of roughly 100MB/sec. Guys, it's 2023 now. HDDs and NICs can handle the throughput of a few GB/sec and CPUs processes dozens of GB/sec. Are you sure 100MB/sec is what we deserve? Are you sure it is fast?

Main features

  • Fast: more than 10x faster compared to similar tools
  • Predictable: it uses pooling, so memory consumption is limited
  • Reliable: doesn't lose data due to commitment mechanism
  • Container / cloud / kubernetes native
  • Simply configurable with YAML
  • Prometheus-friendly: transform your events into metrics on any pipeline stage
  • Vault-friendly: store sensitive info and get it for any pipeline parameter
  • Well-tested and used in production to collect logs from Kubernetes cluster with 3000+ total CPU cores

Performance

On MacBook Pro 2017 with two physical cores file.d can achieve the following throughput:

  • 1.7GB/s in files > devnull case
  • 1.0GB/s in files > json decode > devnull case

TBD: throughput on production servers.

Plugins

Input: dmesg, fake, file, http, journalctl, k8s, kafka

Action: add_file_name, add_host, convert_date, convert_log_level, convert_utf8_bytes, debug, decode, discard, flatten, join, join_template, json_decode, json_encode, json_extract, keep_fields, mask, modify, move, parse_es, parse_re2, remove_fields, rename, set_time, split, throttle

Output: clickhouse, devnull, elasticsearch, file, gelf, kafka, postgres, s3, splunk, stdout

What's next

Join our community in Telegram: https://t.me/file_d_community
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