Alternatives to Log4j logo

Alternatives to Log4j

SLF4J, Logback, Logstash, Loki, and Bunyan are the most popular alternatives and competitors to Log4j.
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What is Log4j and what are its top alternatives?

Log4j is a popular logging framework for Java that provides a flexible architecture for logging at the application level. It allows developers to log messages at different levels of severity, filter and format log messages, and control logging behavior dynamically. However, one of the limitations of Log4j is that it can be complex to configure and use for beginners.

  1. Logback: Logback is a successor to Log4j with a faster implementation and more features like automatic reloading of the configuration file. It offers a simple and flexible configuration system. Pros include performance improvements over Log4j, while a con could be the learning curve for users transitioning from Log4j.
  2. SLF4J: SLF4J serves as a simple facade or abstraction for various logging frameworks including Log4j, Logback, and java.util.logging. It allows developers to switch between different logging implementations easily. A key feature is its modularity, but some users might find it too minimalistic compared to Log4j.
  3. Tinylog: Tinylog is a lightweight logging framework with a small memory footprint and easy setup. It focuses on simplicity and performance. Pros include its minimalistic syntax, but it may lack some advanced features found in Log4j.
  4. Apache Commons Logging: Commons Logging offers a simple logging abstraction that allows for integration with various logging implementations including Log4j. It provides compatibility with older codebases using different logging frameworks. A drawback could be its lack of frequent updates compared to Log4j.
  5. Log4j2: Log4j2 is the next version of Log4j with improved performance and features. It includes asynchronous logging and support for custom log formats. Pros include better performance over Log4j, but migrating from Log4j to Log4j2 might require effort.
  6. TinyLogPlus: TinyLogPlus is an enhanced version of Tinylog with additional features like custom log levels and marker support. It maintains the simplicity and lightweight nature of Tinylog. Pros include the added features, but it may still lack the extensive feature set of Log4j.
  7. Loguru: Loguru is a Python logging library that offers performance improvements over other Python logging libraries. It provides colorful logs with structured and customizable output. Pros include ease of use and colorful output, but it is specific to Python applications.
  8. Log4perl: Log4perl is a logging framework for Perl with features like log levels, appenders, and layout customization. It offers fine-grained control over logging behavior. Pros include its feature set for Perl applications, but it may not be as widely used as Log4j.
  9. Kotlin-logging: Kotlin-logging is a lightweight logging library for Kotlin applications that simplifies logging setup and usage. It offers inline functions for logging with lazy evaluation. Pros include its Kotlin-focused design, but it may lack some advanced features present in Log4j.
  10. Scribe: Scribe is a server for aggregating log data streamed in real time from various sources for processing and storage. It can be used as part of a centralized logging infrastructure. Pros include its scalability and real-time log processing capabilities, but it requires setting up a separate server infrastructure compared to Log4j.

Top Alternatives to Log4j

  • SLF4J
    SLF4J

    It is a simple Logging Facade for Java (SLF4J) serves as a simple facade or abstraction for various logging frameworks allowing the end user to plug in the desired logging framework at deployment time. ...

  • Logback
    Logback

    It is intended as a successor to the popular log4j project. It is divided into three modules, logback-core, logback-classic and logback-access. The logback-core module lays the groundwork for the other two modules, logback-classic natively implements the SLF4J API so that you can readily switch back and forth between logback and other logging frameworks and logback-access module integrates with Servlet containers, such as Tomcat and Jetty, to provide HTTP-access log functionality. ...

  • Logstash
    Logstash

    Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana. ...

  • Loki
    Loki

    Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by Prometheus. It is designed to be very cost effective and easy to operate, as it does not index the contents of the logs, but rather a set of labels for each log stream. ...

  • Bunyan
    Bunyan

    It is a simple and fast JSON logging module for node.js services. It has extensible streams system for controlling where log records go (to a stream, to a file, log file rotation, etc.) ...

  • Seq
    Seq

    Seq is a self-hosted server for structured log search, analysis, and alerting. It can be hosted on Windows or Linux/Docker, and has integrations for most popular structured logging libraries. ...

  • Castle Core
    Castle Core

    It provides common Castle Project abstractions including logging services. It also features Castle DynamicProxy a lightweight runtime proxy generator, and Castle DictionaryAdapter. ...

  • Fluent Bit
    Fluent Bit

    It is a super fast, lightweight, and highly scalable logging and metrics processor and forwarder. It is the preferred choice for cloud and containerized environments. ...

Log4j alternatives & related posts

SLF4J logo

SLF4J

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Simple logging facade for Java
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      Logback logo

      Logback

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      A logging framework for Java applications
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          Logstash logo

          Logstash

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          Collect, Parse, & Enrich Data
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            Free
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            Easy but powerful filtering
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            Scalable
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            Kibana provides machine learning based analytics to log
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            Great to meet GDPR goals
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            Well Documented
          CONS OF LOGSTASH
          • 4
            Memory-intensive
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            Documentation difficult to use

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          Tymoteusz Paul
          Devops guy at X20X Development LTD · | 23 upvotes · 8M views

          Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

          It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

          I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

          We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

          If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

          The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

          Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

          See more

          Hi everyone. I'm trying to create my personal syslog monitoring.

          1. To get the logs, I have uncertainty to choose the way: 1.1 Use Logstash like a TCP server. 1.2 Implement a Go TCP server.

          2. To store and plot data. 2.1 Use Elasticsearch tools. 2.2 Use InfluxDB and Grafana.

          I would like to know... Which is a cheaper and scalable solution?

          Or even if there is a better way to do it.

          See more
          Loki logo

          Loki

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          Like Prometheus, but for logs (by the makers of Grafana)
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          PROS OF LOKI
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            Opensource
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            Very fast ingestion
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            Near real-time search
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            Low resource footprint
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            REST Api
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            Smart way of tagging
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            Perfect fit for k8s
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            Bunyan logo

            Bunyan

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            A logging module for node.js services
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                Seq logo

                Seq

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                Log search, analysis, and alerting server built for modern structured log data
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                PROS OF SEQ
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                  Easy to install and configure
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                  Easy to use
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                  Flexible query language
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                  Free unlimited one-person version
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                  Beautiful charts and dashboards
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                  Extensive plug-ins and integrations
                CONS OF SEQ
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                  It is not free

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                Castle Core logo

                Castle Core

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                It provides common Castle Project abstractions including logging services
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                    Fluent Bit logo

                    Fluent Bit

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                    Fast and lightweight Logs and Metrics processor
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