Alternatives to Beats logo

Alternatives to Beats

Logstash, Wireshark, LibreNMS, PRTG, and Riemann are the most popular alternatives and competitors to Beats.
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What is Beats and what are its top alternatives?

Beats is a data shipper tool that helps collect, process, and send data from different sources to Elasticsearch or Logstash for analysis and visualization. It is part of the Elastic Stack and offers modules for various purposes like Filebeat for log files and Metricbeat for metric data. However, Beats can be limited in terms of complex data processing capabilities and lack of advanced monitoring features.

  1. Logstash: Logstash is another tool in the Elastic Stack that serves as a data processing pipeline. It allows for more advanced data transformations and filtering compared to Beats. Pros include powerful data processing capabilities, but it can be more resource-intensive than Beats.
  2. Fluentd: Fluentd is an open-source data collector that enables unified logging layers. It supports a wide range of inputs and outputs and has a plugin ecosystem for extending functionality. Pros include flexibility in data collection, but configuration can be complex compared to Beats.
  3. Syslog-ng: Syslog-ng is a log management solution that focuses on collecting and processing log data. It offers advanced routing and filtering capabilities, making it suitable for complex logging environments. Pros include robust log management features, but it may require more setup compared to Beats.
  4. Splunk: Splunk is a popular platform for analyzing machine-generated data, including logs. It offers powerful search and visualization tools for monitoring and troubleshooting. Pros include rich data analysis capabilities, but it can be costly compared to open-source solutions like Beats.
  5. Graylog: Graylog is an open-source log management platform that allows for centralized log collection, processing, and analysis. It offers dashboards for visualization and alerting features for monitoring. Pros include cost-effective log management, but it may not scale as easily as Beats in some scenarios.
  6. Prometheus: Prometheus is an open-source monitoring and alerting toolkit designed for cloud-native environments. It collects time-series data for metrics monitoring and offers query capabilities for analysis. Pros include a strong focus on monitoring, but it may require additional setup for log collection compared to Beats.
  7. Grafana: Grafana is a visualization tool commonly used with metrics and logs data. It offers flexible dashboards for monitoring and visualization purposes, making it a popular choice for data visualization. Pros include rich visualization options, but it may require integration with other tools for data collection like Beats.
  8. Rsyslog: Rsyslog is a high-performance logging system that offers real-time log processing capabilities. It supports various protocols and formats for log collection and forwarding. Pros include efficient log processing, but it may have a steeper learning curve compared to Beats.
  9. Papertrail: Papertrail is a cloud-based log management solution that offers real-time log tailing and searching capabilities. It simplifies log management for small to medium-sized environments. Pros include ease of setup and use, but it may lack the customization options of Beats.
  10. Loggly: Loggly is a cloud-based log management service that focuses on log aggregation and analysis. It offers search and visualization features for monitoring log data in real-time. Pros include ease of use for log analysis, but it may have limitations in terms of data retention compared to storing data locally with Beats.

Top Alternatives to Beats

  • 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. ...

  • Wireshark
    Wireshark

    It is the world’s foremost and widely-used network protocol analyzer. It lets you see what’s happening on your network at a microscopic level and is the de facto standard across many commercial and non-profit enterprises, government agencies, and educational institutions. ...

  • LibreNMS
    LibreNMS

    It is an auto-discovering PHP/MySQL/SNMP based network monitoring which includes support for a wide range of network hardware and operating systems including Cisco, Linux, FreeBSD, Juniper, Brocade, Foundry, HP and many more. ...

  • PRTG
    PRTG

    It can monitor and classify system conditions like bandwidth usage or uptime and collect statistics from miscellaneous hosts as switches, routers, servers and other devices and applications. ...

  • Riemann
    Riemann

    Riemann aggregates events from your servers and applications with a powerful stream processing language. Send an email for every exception in your app. Track the latency distribution of your web app. See the top processes on any host, by memory and CPU. ...

  • Nagios XI
    Nagios XI

    It is the most powerful and trusted network monitoring software on the market. It extends on proven, enterprise-class Open Source components to deliver the best network, server and application monitoring solution for today's demanding organizational requirements. ...

  • Snort
    Snort

    It is an open-source, free and lightweight network intrusion detection system (NIDS) software for Linux and Windows to detect emerging threats. ...

  • Tailscale
    Tailscale

    It connect all your devices using WireGuard, without the hassle. Create a secure network between your servers, computers, and cloud instances. Even when separated by firewalls or subnets, Tailscale just works. It makes it as easy as installing an app and signing in. ...

Beats alternatives & related posts

Logstash logo

Logstash

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Collect, Parse, & Enrich Data
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PROS OF LOGSTASH
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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
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    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.

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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.

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Wireshark

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A free and open-source protocol analyzer
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      LibreNMS

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          PRTG

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              Riemann

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                Nagios XI

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                Enterprise Server and Network Monitoring Software
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                            Bryan Dady
                            SRE Manager at Subsplash · | 6 upvotes · 44.5K views
                            Shared insights
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                            TailscaleTailscaleOpenVPNOpenVPN

                            Do you know of a 'commercial' WireGuard packages that might be usable for startup/corporate VPN solution as an alternative to OpenVPN or Tailscale? So far, I've found Perimeter 81 and AppGate. If you have any real-world experience with a WireGuard solution for a business setting, I'd greatly appreciate hearing from you.

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