Alternatives to Papertrail logo

Alternatives to Papertrail

Sentry, Splunk, Logstash, Loggly, and Logentries are the most popular alternatives and competitors to Papertrail.
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What is Papertrail and what are its top alternatives?

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.
Papertrail is a tool in the Log Management category of a tech stack.

Top Alternatives to Papertrail

  • Sentry
    Sentry

    Sentry’s Application Monitoring platform helps developers see performance issues, fix errors faster, and optimize their code health. ...

  • Splunk
    Splunk

    It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data. ...

  • 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. ...

  • Loggly
    Loggly

    It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain. ...

  • Logentries
    Logentries

    Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users. ...

  • Datadog
    Datadog

    Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog! ...

  • LogDNA
    LogDNA

    The easiest log management system you will ever use! LogDNA is a cloud-based log management system that allows engineering and devops to aggregate all system and application logs into one efficient platform. Save, store, tail and search app ...

  • Sumo Logic
    Sumo Logic

    Cloud-based machine data analytics platform that enables companies to proactively identify availability and performance issues in their infrastructure, improve their security posture and enhance application rollouts. Companies using Sumo Logic reduce their mean-time-to-resolution by 50% and can save hundreds of thousands of dollars, annually. Customers include Netflix, Medallia, Orange, and GoGo Inflight. ...

Papertrail alternatives & related posts

Sentry logo

Sentry

14K
9.1K
863
See performance issues, fix errors faster, and optimize code health.
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PROS OF SENTRY
  • 237
    Consolidates similar errors and makes resolution easy
  • 121
    Email Notifications
  • 108
    Open source
  • 84
    Slack integration
  • 71
    Github integration
  • 49
    Easy
  • 44
    User-friendly interface
  • 28
    The most important tool we use in production
  • 18
    Hipchat integration
  • 17
    Heroku Integration
  • 15
    Good documentation
  • 14
    Free tier
  • 11
    Self-hosted
  • 9
    Easy setup
  • 7
    Realiable
  • 6
    Provides context, and great stack trace
  • 4
    Feedback form on error pages
  • 4
    Love it baby
  • 3
    Gitlab integration
  • 3
    Filter by custom tags
  • 3
    Super user friendly
  • 3
    Captures local variables at each frame in backtraces
  • 3
    Easy Integration
  • 1
    Performance measurements
CONS OF SENTRY
  • 12
    Confusing UI
  • 4
    Bundle size

related Sentry posts

Johnny Bell

For my portfolio websites and my personal OpenSource projects I had started exclusively using React and JavaScript so I needed a way to track any errors that we're happening for my users that I didn't uncover during my personal UAT.

I had narrowed it down to two tools LogRocket and Sentry (I also tried Bugsnag but it did not make the final two). Before I get into this I want to say that both of these tools are amazing and whichever you choose will suit your needs well.

I firstly decided to go with LogRocket the fact that they had a recorded screen capture of what the user was doing when the bug happened was amazing... I could go back and rewatch what the user did to replicate that error, this was fantastic. It was also very easy to setup and get going. They had options for React and Redux.js so you can track all your Redux.js actions. I had a fairly large Redux.js store, this was ended up being a issue, it killed the processing power on my machine, Chrome ended up using 2-4gb of ram, so I quickly disabled the Redux.js option.

After using LogRocket for a month or so I decided to switch to Sentry. I noticed that Sentry was openSorce and everyone was talking about Sentry so I thought I may as well give it a test drive. Setting it up was so easy, I had everything up and running within seconds. It also gives you the option to wrap an errorBoundry in React so get more specific errors. The simplicity of Sentry was a breath of fresh air, it allowed me find the bug that was shown to the user and fix that very simply. The UI for Sentry is beautiful and just really clean to look at, and their emails are also just perfect.

I have decided to stick with Sentry for the long run, I tested pretty much all the JS error loggers and I find Sentry the best.

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Paurush Rai
Full Stack Developer at Fuelbuddy · | 4 upvotes · 2K views
Shared insights
on
StackdriverStackdriverSentrySentryDatadogDatadog

Need advice on this.

Which one should I use for logging and error monitoring ( Datadog / Sentry / Stackdriver )?

Open to any other solutions.

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Splunk logo

Splunk

595
993
20
Search, monitor, analyze and visualize machine data
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PROS OF SPLUNK
  • 3
    API for searching logs, running reports
  • 3
    Alert system based on custom query results
  • 2
    Dashboarding on any log contents
  • 2
    Custom log parsing as well as automatic parsing
  • 2
    Ability to style search results into reports
  • 2
    Query engine supports joining, aggregation, stats, etc
  • 2
    Splunk language supports string, date manip, math, etc
  • 2
    Rich GUI for searching live logs
  • 1
    Query any log as key-value pairs
  • 1
    Granular scheduling and time window support
CONS OF SPLUNK
  • 1
    Splunk query language rich so lots to learn

related Splunk posts

Shared insights
on
KibanaKibanaSplunkSplunkGrafanaGrafana

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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Shared insights
on
SplunkSplunkElasticsearchElasticsearch

We are currently exploring Elasticsearch and Splunk for our centralized logging solution. I need some feedback about these two tools. We expect our logs in the range of upwards > of 10TB of logging data.

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Logstash logo

Logstash

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8.5K
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Collect, Parse, & Enrich Data
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PROS OF LOGSTASH
  • 69
    Free
  • 18
    Easy but powerful filtering
  • 12
    Scalable
  • 2
    Kibana provides machine learning based analytics to log
  • 1
    Great to meet GDPR goals
  • 1
    Well Documented
CONS OF LOGSTASH
  • 4
    Memory-intensive
  • 1
    Documentation difficult to use

related Logstash posts

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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Loggly logo

Loggly

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Unified log analysis & log monitoring
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+ 1
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PROS OF LOGGLY
  • 37
    Centralized log management
  • 25
    Easy to setup
  • 21
    Great filtering
  • 16
    Live logging
  • 15
    Json log support
  • 10
    Log Management
  • 10
    Alerting
  • 7
    Great Dashboards
  • 7
    Love the product
  • 4
    Heroku Add-on
  • 2
    Easy to setup and use
  • 2
    Easy setup
  • 2
    No alerts in free plan
  • 2
    Great UI
  • 2
    Good parsing
  • 2
    Powerful
  • 2
    Fast search
  • 2
    Backup to S3
CONS OF LOGGLY
  • 3
    Pricey after free plan

related Loggly posts

Logentries logo

Logentries

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Real-time log management and analytics built for the cloud
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PROS OF LOGENTRIES
  • 34
    Log search
  • 27
    Live logs
  • 19
    Easy setup
  • 14
    Heroku Add-on
  • 5
    Backup to S3
  • 2
    Easy setup, independent of existing logging setup
  • 2
    Free
  • 2
    Search/query with regex
  • 0
    E
CONS OF LOGENTRIES
    Be the first to leave a con

    related Logentries posts

    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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    Datadog logo

    Datadog

    9.1K
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    857
    Unify logs, metrics, and traces from across your distributed infrastructure.
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    PROS OF DATADOG
    • 137
      Monitoring for many apps (databases, web servers, etc)
    • 107
      Easy setup
    • 87
      Powerful ui
    • 83
      Powerful integrations
    • 70
      Great value
    • 54
      Great visualization
    • 46
      Events + metrics = clarity
    • 41
      Custom metrics
    • 41
      Notifications
    • 39
      Flexibility
    • 19
      Free & paid plans
    • 16
      Great customer support
    • 15
      Makes my life easier
    • 10
      Adapts automatically as i scale up
    • 9
      Easy setup and plugins
    • 8
      Super easy and powerful
    • 7
      AWS support
    • 7
      In-context collaboration
    • 6
      Rich in features
    • 5
      Docker support
    • 4
      Cost
    • 4
      Full visibility of applications
    • 4
      Monitor almost everything
    • 4
      Cute logo
    • 4
      Automation tools
    • 4
      Source control and bug tracking
    • 4
      Simple, powerful, great for infra
    • 4
      Easy to Analyze
    • 4
      Best than others
    • 3
      Best in the field
    • 3
      Expensive
    • 3
      Good for Startups
    • 3
      Free setup
    • 2
      APM
    CONS OF DATADOG
    • 19
      Expensive
    • 4
      No errors exception tracking
    • 2
      External Network Goes Down You Wont Be Logging
    • 1
      Complicated

    related Datadog posts

    Robert Zuber

    Our primary source of monitoring and alerting is Datadog. We’ve got prebuilt dashboards for every scenario and integration with PagerDuty to manage routing any alerts. We’ve definitely scaled past the point where managing dashboards is easy, but we haven’t had time to invest in using features like Anomaly Detection. We’ve started using Honeycomb for some targeted debugging of complex production issues and we are liking what we’ve seen. We capture any unhandled exceptions with Rollbar and, if we realize one will keep happening, we quickly convert the metrics to point back to Datadog, to keep Rollbar as clean as possible.

    We use Segment to consolidate all of our trackers, the most important of which goes to Amplitude to analyze user patterns. However, if we need a more consolidated view, we push all of our data to our own data warehouse running PostgreSQL; this is available for analytics and dashboard creation through Looker.

    See more
    Farzeem Diamond Jiwani
    Software Engineer at IVP · | 8 upvotes · 1.4M views

    Hey there! We are looking at Datadog, Dynatrace, AppDynamics, and New Relic as options for our web application monitoring.

    Current Environment: .NET Core Web app hosted on Microsoft IIS

    Future Environment: Web app will be hosted on Microsoft Azure

    Tech Stacks: IIS, RabbitMQ, Redis, Microsoft SQL Server

    Requirement: Infra Monitoring, APM, Real - User Monitoring (User activity monitoring i.e., time spent on a page, most active page, etc.), Service Tracing, Root Cause Analysis, and Centralized Log Management.

    Please advise on the above. Thanks!

    See more
    LogDNA logo

    LogDNA

    101
    143
    18
    Easy beautiful logging in the cloud
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    143
    + 1
    18
    PROS OF LOGDNA
    • 6
      Easy setup
    • 4
      Cheap
    • 3
      Extremely fast
    • 2
      Powerful filtering and alerting functionality
    • 1
      Graphing capabilities
    • 1
      Export data to S3
    • 1
      Multi-cloud
    CONS OF LOGDNA
    • 1
      Limited visualization capabilities
    • 1
      Cannot copy & paste text from visualization

    related LogDNA posts

    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.

    See more
    Sumo Logic logo

    Sumo Logic

    193
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    Cloud Log Management for Application Logs and IT Log Data
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    PROS OF SUMO LOGIC
    • 11
      Search capabilities
    • 5
      Live event streaming
    • 3
      Pci 3.0 compliant
    • 2
      Easy to setup
    CONS OF SUMO LOGIC
    • 2
      Expensive
    • 1
      Occasionally unreliable log ingestion
    • 1
      Missing Monitoring

    related Sumo Logic posts

    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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