Fluentd
Fluentd is an open source data collector for unified logging layer. It allows you to flexibly collect, transform and distribute logs and events from various sources to different destinations.
logging
data-collection
open-source
Fluentd: Open Source Data Collector for Unified Logging Layer
Fluentd is an open source data collector for unified logging layer. It allows you to flexibly collect, transform and distribute logs and events from various sources to different destinations.
What is Fluentd?
Fluentd is an open source data collector designed for processing data streams. It works by having input plugins that collect data from various sources, processing plugins that transform the data, and output plugins that send the data to various destinations.
Some key features of Fluentd include:
- Unified logging layer - It allows you to routing and processing logs and events from different sources using a simple configuration file.
- Pluggable architecture - There is a vibrant ecosystem of input, filter, parser and output plugins allowing you to customize it to your use case.
- Reliable and scalable - Fluentd uses an asynchronous design and buffering mechanisms to prevent data loss and ensure reliable delivery.
- Cloud native - It is designed for modern containerized and microservices based infrastructure and integrates well with Kubernetes and Docker.
- Large community - Fluentd is used by many major technology companies and has an active open source community behind it.
Some common use cases of Fluentd include application logging, infrastructure monitoring, clickstream analysis, sensor data processing and more. It aims to provide a flexible platform for dealing with streaming data.
Fluentd Features
Features
- Real-time log collection and processing
- Plugin ecosystem for extensibility
- Data routing and distribution
- Data buffering and reliability
- JSON processing
- Timeseries data optimized
- Kubernetes integration
Pricing
- Open Source
Pros
Open source and free
Simple and flexible architecture
Rich plugin ecosystem
High performance and scalability
Easy to get started
Cons
Complex configuration
Plugin quality varies
Limited native data transformations
Steep learning curve
Official Links
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