Difference Between Fluentd vs Logstash
- Log files record all the relevant information and events that occur in a computing system. They are vital for any computing system as they throw light on all the changes that have occurred in a system or an environment. This helps the users analyze and understand the situation, and if there is a problem, it can be used to backtrack to the root cause. When dealing with scalable systems, it is always required to have a protocol for log management.
- One such approach is centralized Log management, where the logs generated by various subsystems are sorted, parsed and stored in a central repository at the system level. This will essentially reduce the effort in identifying issues. There are a lot of tools in the market that does the job. Let’s discuss about fluentd and logstash.
- Fluentd is an open-source big data tool used to parse, analyze and store data. It is developed by Treasure data and is a part of the CNCF (Cloud Native Computing Foundation). It is completely developed in CRuby.
- Logstash is an open-source tool used to parse, analyze and store data to the Elasticsearch engine. The L in ELK stack stands for Logstash. It is developed in JRuby. It is very flexible with the inputs; it has over 50 plugins to connect to various databases, systems, platforms to collect data.
Head to Head Comparisons Between Fluentd vs Logstash (Infographics)
Below are the top comparisons between Fluentd and Logstash:
Key Differences Between Fluentd vs Logstash
Let us discuss some of the major key differences between Fluentd and Logstash:
- Fluentd is developed in CRuby, whereas logstash is developed in JRuby; therefore, it should have a Java JVM running.
- Logstash, as it is a part of ELK stash, has an inbuilt visualizing tool, kibana. It can be used to view the logs, search results, events etc.… Fluentd provides better integration with CNCF projects like Prometheus etc.… as it is also a part of CNCF. Fluentd also provides support for Elastic.
- Linux, as well as Windows OS, supports both the tools.
- Fluentd supports way more third party plugins for inputs than logstash, but logstash has a central repo of all the plugins it supports in github.
- Logstash consumes more memory than that of fluentd, but otherwise, both the tools’ performance is similar.
- Event routing is a key role in log collection. Logstash uses a procedural approach of if-else statements in routing the events. It is easier for programmers well versed in procedure programming. Eg: If <condition> then <action>. Fluentd uses tags. There is an action defined for every tag; if the event matches its tag, it follows its appropriate action.
Eg: <match tag> type action…</match>. Fluentd’s approach is more descriptive and it is useful in complex routing. - Logstash is limited to a fixed size on-memory queue that can hold on 20 events. It needs an external queue to maintain continuity across restarts. This can be overcome by using Kafka or Redis as a centralized buffer to increase data reliability. Failure models should be taken care incase the applications cannot afford any data loss. Fluentd has a buffering system that is highly configurable as it has high in-memory.
- Logstash offers a metrics filter to track certain events or specific procedures. It returns the logs that are related to the metrics search, and the search results can be visualized in
- a third party configurable plugin such as graphite. Fluentd has an in-built monitoring agent that can be queried to return status on certain tags. It also allows monitoring plugins to be integrated with the monitoring stack.
- A data forwarder is a unit that carries data from an origin point to a destination point. A shipper is a unit that automates the process of backing up a database, log files, data from the main(primary) server to a secondary server. Both tools have forwarders that are capable of detecting failures in shippers. When a forwarder detects a failure, it switches to another shipper.
Comparison Table
Let’s look at the top comparisons between Fluentd vs Logstash.
|
Fluentd |
Logstash |
| Event Routing is done using algorithmic if-then statements. | Event Routing is based on tags. |
| Has a fully functional enterprise support | Enterprise support is not available. |
| All the plugins are decentralized. | All the plugins supported are centralized in Github. |
| Built-in reliability is offered for transportation, but it isn’t easy to configure. | In-built reliability is not offered, but Redis can be integrated along for reliability. |
| It uses less memory when it comes to performance. | It uses more memory. |
| Developed in CRuby | Developed in JRuby, it is mandatory to have java running in the system. |
| Fluentd does not support multithreading as it is restricted by GIL (Global interpreter lock) | Logstash supports multithreading |
| Fluentd has built-in parsers like json, csv, XML, regex, and it also supports third-party parsers. | Logstash supports more plugin based parsers and filters like aggregate etc. |
| Fluentd has a simple design, robust and high reliability. | Logstash is modular, interoperable, and has high scalability. |
Overall, both the tools have their own pros and cons, as we have seen earlier. Selecting a tool is completely based on the system and its requirements. Logstash is best suited for monolithic applications, whereas for applications/services hosted on docker, fluentd suits the best. There are hybrid applications in which both can be used.
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