Alternatives to Scalyr logo
Sumo Logic, Splunk, Wavefront, ELK, and Logstash are the most popular alternatives and competitors to Scalyr.
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What is Scalyr?

Scalyr is log search and management so fast you actually use it. Custom dashboards, graphs, alerts and log parsers allow you to monitor what's important to you. We're proud to serve customers like Business Insider, Opendoor, and Grab.
Scalyr is a tool in the Log Management category of a tech stack.

Scalyr alternatives & related posts

Sumo Logic logo

Sumo Logic

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Cloud Log Management for Application Logs and IT Log Data
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Sumo Logic
Sumo Logic
Papertrail
Papertrail
Timber.io
Timber.io
LogDNA
LogDNA
Logentries
Logentries
#Heroku

Logentries, LogDNA, Timber.io, Papertrail and Sumo Logic provide free pricing plan for #Heroku application. You can add these applications as add-ons very easily.

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Splunk logo

Splunk

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Search, monitor, analyze and visualize machine data
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    Grafana
    Grafana
    Splunk
    Splunk
    Kibana
    Kibana

    I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.

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    Wavefront logo

    Wavefront

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    15
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    Unified Cloud Monitoring with Real-Time Analytics
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      ELK logo

      ELK

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      The acronym for three open source projects: Elasticsearch, Logstash, and Kibana
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        Wallace Alves
        Wallace Alves
        Cyber Security Analyst · | 1 upvotes · 2.9K views
        nginx
        nginx
        Logstash
        Logstash
        Kibana
        Kibana
        Elasticsearch
        Elasticsearch
        ELK
        ELK
        Portainer
        Portainer
        Docker Compose
        Docker Compose
        Docker
        Docker

        Docker Docker Compose Portainer ELK Elasticsearch Kibana Logstash nginx

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        Logstash logo

        Logstash

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        1.8K
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        Collect, Parse, & Enrich Data
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        Tymoteusz Paul
        Tymoteusz Paul
        Devops guy at X20X Development LTD · | 11 upvotes · 142.7K views
        Amazon EC2
        Amazon EC2
        LXC
        LXC
        CircleCI
        CircleCI
        Docker
        Docker
        Git
        Git
        Vault
        Vault
        Apache Maven
        Apache Maven
        Slack
        Slack
        Jenkins
        Jenkins
        TeamCity
        TeamCity
        Logstash
        Logstash
        Kibana
        Kibana
        Elasticsearch
        Elasticsearch
        Ansible
        Ansible
        VirtualBox
        VirtualBox
        Vagrant
        Vagrant

        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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        Tanya Bragin
        Tanya Bragin
        Product Lead, Observability at Elastic · | 10 upvotes · 19.6K views
        atElasticElastic
        Kibana
        Kibana
        Logstash
        Logstash
        Elasticsearch
        Elasticsearch

        ELK Stack (Elasticsearch, Logstash, Kibana) is widely known as the de facto way to centralize logs from operational systems. The assumption is that Elasticsearch (a "search engine") is a good place to put text-based logs for the purposes of free-text search. And indeed, simply searching text-based logs for the word "error" or filtering logs based on a set of a well-known tags is extremely powerful, and is often where most users start.

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        related Papertrail posts

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        Timber.io
        Timber.io
        LogDNA
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        Logentries
        Logentries
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        Logentries logo

        Logentries

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        Real-time log management and analytics built for the cloud
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        Fluentd logo

        Fluentd

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        Unified logging layer
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        AWS CloudTrail logo

        AWS CloudTrail

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        Record AWS API calls for your account and have log files delivered to you
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        Splunk Cloud logo

        Splunk Cloud

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        Easy and fast way to analyze valuable machine data with the convenience of software as a service (SaaS)
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        Sumo Logic
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        Logentries, LogDNA, Timber.io, Papertrail and Sumo Logic provide free pricing plan for #Heroku application. You can add these applications as add-ons very easily.

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        logz.io logo

        logz.io

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        A log management and log analysis service
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          Filebeat logo

          Filebeat

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          A lightweight shipper for forwarding and centralizing log data
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            SLF4J logo

            SLF4J

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            Simple logging facade for Java
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              Apache Flume logo

              Apache Flume

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              A service for collecting, aggregating, and moving large amounts of log data
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                Logback logo

                Logback

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                A logging framework for Java applications
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                  Timber.io logo

                  Timber.io

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                  Automatically convert logs from messy, hard-to-use, raw text to rich, useful, clean events.
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                    LogDNA
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                    Logentries, LogDNA, Timber.io, Papertrail and Sumo Logic provide free pricing plan for #Heroku application. You can add these applications as add-ons very easily.

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