Alternatives to LightStep logo

Alternatives to LightStep

Honeycomb, New Relic, Jaeger, Datadog, and Instana are the most popular alternatives and competitors to LightStep.
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What is LightStep and what are its top alternatives?

It diagnoses anomalies and slowdowns, spanning mobile, monoliths, and micro services: best-in-class observability, at scale, for modern applications.
LightStep is a tool in the Performance Monitoring category of a tech stack.

LightStep alternatives & related posts

Honeycomb logo

Honeycomb

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Observability for a distributed world--designed for high cardinality data and collaborative problem solving 🐝💖
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    Robert Zuber
    Robert Zuber
    CTO at CircleCI · | 8 upvotes · 218.6K views
    atCircleCICircleCI
    Datadog
    Datadog
    PagerDuty
    PagerDuty
    Honeycomb
    Honeycomb
    Rollbar
    Rollbar
    Segment
    Segment
    Amplitude
    Amplitude
    PostgreSQL
    PostgreSQL
    Looker
    Looker

    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.

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    New Relic logo

    New Relic

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    1.9K
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    SaaS Application Performance Management for Ruby, PHP, .Net, Java, Python, and Node.js Apps.
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    Sebastian Gębski
    Sebastian Gębski
    CTO at Shedul/Fresha · | 4 upvotes · 300.6K views
    atFresha EngineeringFresha Engineering
    CircleCI
    CircleCI
    Jenkins
    Jenkins
    Git
    Git
    GitHub
    GitHub
    New Relic
    New Relic
    AppSignal
    AppSignal
    Sentry
    Sentry
    Logentries
    Logentries

    Regarding Continuous Integration - we've started with something very easy to set up - CircleCI , but with time we're adding more & more complex pipelines - we use Jenkins to configure & run those. It's much more effort, but at some point we had to pay for the flexibility we expected. Our source code version control is Git (which probably doesn't require a rationale these days) and we keep repos in GitHub - since the very beginning & we never considered moving out. Our primary monitoring these days is in New Relic (Ruby & SPA apps) and AppSignal (Elixir apps) - we're considering unifying it in New Relic , but this will require some improvements in Elixir app observability. For error reporting we use Sentry (a very popular choice in this class) & we collect our distributed logs using Logentries (to avoid semi-manual handling here).

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    Julien DeFrance
    Julien DeFrance
    Principal Software Engineer at Tophatter · | 3 upvotes · 102.5K views
    atStessaStessa
    New Relic
    New Relic
    Datadog
    Datadog
    #APM

    Which #APM / #Infrastructure #Monitoring solution to use?

    The 2 major players in that space are New Relic and Datadog Both are very comparable in terms of pricing, capabilities (Datadog recently introduced APM as well).

    In our use case, keeping the number of tools minimal was a major selection criteria.

    As we were already using #NewRelic, my recommendation was to move to the pro tier so we would benefit from advanced APM features, synthetics, mobile & infrastructure monitoring. And gain 360 degree view of our infrastructure.

    Few things I liked about New Relic: - Mobile App and push notificatin - Ease of setting up new alerts - Being notified via email and push notifications without requiring another alerting 3rd party solution

    I've certainly seen use cases where NewRelic can also be used as an input data source for Datadog. Therefore depending on your use case, it might also be worth evaluating a joint usage of both solutions.

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    Jaeger logo

    Jaeger

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    Distributed tracing system released as open source by Uber
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    Robert Zuber
    Robert Zuber
    CTO at CircleCI · | 8 upvotes · 218.6K views
    atCircleCICircleCI
    Datadog
    Datadog
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    PagerDuty
    Honeycomb
    Honeycomb
    Rollbar
    Rollbar
    Segment
    Segment
    Amplitude
    Amplitude
    PostgreSQL
    PostgreSQL
    Looker
    Looker

    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.

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    StackShare Editors
    StackShare Editors
    Grafana
    Grafana
    StatsD
    StatsD
    Airflow
    Airflow
    PagerDuty
    PagerDuty
    Datadog
    Datadog
    Celery
    Celery
    AWS EC2
    AWS EC2
    Flask
    Flask

    Data science and engineering teams at Lyft maintain several big data pipelines that serve as the foundation for various types of analysis throughout the business.

    Apache Airflow sits at the center of this big data infrastructure, allowing users to “programmatically author, schedule, and monitor data pipelines.” Airflow is an open source tool, and “Lyft is the very first Airflow adopter in production since the project was open sourced around three years ago.”

    There are several key components of the architecture. A web UI allows users to view the status of their queries, along with an audit trail of any modifications the query. A metadata database stores things like job status and task instance status. A multi-process scheduler handles job requests, and triggers the executor to execute those tasks.

    Airflow supports several executors, though Lyft uses CeleryExecutor to scale task execution in production. Airflow is deployed to three Amazon Auto Scaling Groups, with each associated with a celery queue.

    Audit logs supplied to the web UI are powered by the existing Airflow audit logs as well as Flask signal.

    Datadog, Statsd, Grafana, and PagerDuty are all used to monitor the Airflow system.

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    Instana logo

    Instana

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    Automatic Application and Infrastructure Monitoring
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      ruxit logo

      ruxit

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      Full stack availability and performance monitoring powered by artificial intelligence
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      AppDynamics logo

      AppDynamics

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      Application management for the cloud generation
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      Azure Application Insights logo

      Azure Application Insights

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      It is an extensible Application Performance Management (APM) service for web developers
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        Librato logo

        Librato

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        Real-Time Cloud Monitoring
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        Jerome Dalbert
        Jerome Dalbert
        Senior Backend Engineer at StackShare · | 3 upvotes · 74.9K views
        atStackShareStackShare
        Heroku
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        Rails
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        Pingdom
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        Slack
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        We currently monitor performance with the following tools:

        1. Heroku Metrics: our main app is Hosted on Heroku, so it is the best place to get quick server metrics like memory usage, load averages, or response times.
        2. Good old New Relic for detailed general metrics, including transaction times.
        3. Skylight for more specific Rails Controller#action transaction times. Navigating those timings is much better than with New Relic, as you get a clear full breakdown of everything that happens for a given request.

        Skylight offers better Rails performance insights, so why use New Relic? Because it does frontend monitoring, while Skylight doesn't. Now that we have a separate frontend app though, our frontend engineers are looking into more specialized frontend monitoring solutions.

        Finally, if one of our apps go down, Pingdom alerts us on Slack and texts some of us.

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        phpMyAdmin logo

        phpMyAdmin

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        A free software, for MySQL and MariaDB
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        Sebastian Gębski
        Sebastian Gębski
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        Git
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        GitHub
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        Regarding Continuous Integration - we've started with something very easy to set up - CircleCI , but with time we're adding more & more complex pipelines - we use Jenkins to configure & run those. It's much more effort, but at some point we had to pay for the flexibility we expected. Our source code version control is Git (which probably doesn't require a rationale these days) and we keep repos in GitHub - since the very beginning & we never considered moving out. Our primary monitoring these days is in New Relic (Ruby & SPA apps) and AppSignal (Elixir apps) - we're considering unifying it in New Relic , but this will require some improvements in Elixir app observability. For error reporting we use Sentry (a very popular choice in this class) & we collect our distributed logs using Logentries (to avoid semi-manual handling here).

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        Scout logo

        Scout

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        Application Monitoring that Developers Love
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        Blackfire.io

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        Blackfire.io enables developers to continuously measure & improve their code performance in dev, test, staging and prod.
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        A comprehensive DB tool for MySQL, MariaDB, SQL Server, SQLite, Oracle and PostgreSQL development and management.
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          Monitoring and Operational Intelligence for the Cloud
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          Wavefront

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          Unified Cloud Monitoring with Real-Time Analytics
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