Fluent Bit
Fluent Bit is an open source log processor and forwarder which allows you to collect, parse and route logs from different sources. It is lightweight, fast and flexible making it well-suited for embedded systems and edge computing.
logging
log-collector
log-parser
log-forwarder
Fluent Bit: Open Source Log Processor and Forwarder
Fluent Bit is an open source log processor and forwarder which allows you to collect, parse and route logs from different sources. It is lightweight, fast and flexible making it well-suited for embedded systems and edge computing.
What is Fluent Bit?
Fluent Bit is an open source log processor and forwarder designed to be lightweight, flexible and fast for collecting, parsing and routing logs from different sources. Some key features of Fluent Bit include:
- Lightweight with no external dependencies, runs on Linux, macOS, Windows and embedded systems like Raspberry Pi.
- Real-time log processing and forwarding to backends like Elasticsearch, Splunk, Kafka etc.
- Plugin architecture allowing custom inputs, filters, parsers and outputs.
- Support for structured and unstructured logs from files, stdout, databases and message queues.
- Simple JSON based configuration for routing logs and derivatives to different outputs.
- Built-in parsers for common log formats like CSV, Regex, JSON, Syslog etc.
Fluent Bit is well-suited for containerized environments like Kubernetes which require collecting logs from multiple containers and nodes. The small resource footprint makes it usable for edge computing use cases. It can handle high log volumes with little overhead.
Fluent Bit Features
Features
- Lightweight and high-performance log processor
- Supports parsing different log formats like JSON, CSV, Regex, etc
- Can collect logs from multiple sources like files, stdin, Kafka, etc
- Built-in filtering to route logs based on content
- Pluggable architecture to extend functionality via plugins
- Output plugins allow forwarding logs to databases, S3, Elasticsearch, etc
- Written in C making it suitable for edge computing use cases
Pricing
- Open Source
Pros
Lightweight resource usage
Fast processing of high volume log data
Flexible data pipeline configuration
Easy to deploy, no external dependencies
Good for Kubernetes logging
Active open source community
Cons
Less out-of-box functionality compared to heavier log aggregators
Steeper learning curve than competing solutions
Limited native data visualization capabilities
Need to write custom plugins for complex data processing
Official Links
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