Alternatives to Netuitive logo

Alternatives to Netuitive

Datadog, New Relic, ruxit, AppDynamics, and Azure Application Insights are the most popular alternatives and competitors to Netuitive.
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What is Netuitive and what are its top alternatives?

Netuitive provides an adaptive monitoring, analytics, and anomaly detection platform for cloud infrastructure and web applications. By ingesting metrics from multiple data sources, Netuitive learns behaviors and utilizes pre-set dynamic policies that reduce the manual effort and human-guesswork typically required to monitor systems and applications. This unique technology enables IT operations and developers to automate performance analysis, detect relevant anomalies, and determine efficient capacity utilization.
Netuitive is a tool in the Performance Monitoring category of a tech stack.

Netuitive alternatives & related posts

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Robert Zuber
Robert Zuber
CTO at CircleCI · | 8 upvotes · 208.8K 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.

See more
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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New Relic logo

New Relic

14.7K
3.3K
1.9K
14.7K
3.3K
+ 1
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SaaS Application Performance Management for Ruby, PHP, .Net, Java, Python, and Node.js Apps.
New Relic logo
New Relic
VS
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Netuitive

related New Relic posts

Sebastian Gębski
Sebastian Gębski
CTO at Shedul/Fresha · | 4 upvotes · 295.3K views
atFresha EngineeringFresha Engineering
CircleCI
CircleCI
Jenkins
Jenkins
Git
Git
GitHub
GitHub
New Relic
New Relic
AppSignal
AppSignal
Sentry
Sentry
Logentries
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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).

See more
Julien DeFrance
Julien DeFrance
Principal Software Engineer at Tophatter · | 3 upvotes · 97.8K 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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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 · 72.1K views
    atStackShareStackShare
    Heroku
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    Rails
    Rails
    Pingdom
    Pingdom
    Slack
    Slack

    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

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    A free software, for MySQL and MariaDB
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    related AppSignal posts

    Sebastian Gębski
    Sebastian Gębski
    CTO at Shedul/Fresha · | 4 upvotes · 295.3K views
    atFresha EngineeringFresha Engineering
    CircleCI
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    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).

    See more
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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 · 208.8K views
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        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
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