Alternatives to Nagios XI logo

Alternatives to Nagios XI

Zabbix, Icinga, Nagios, Solarwinds, and Datadog are the most popular alternatives and competitors to Nagios XI.
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What is Nagios XI and what are its top alternatives?

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.
Nagios XI is a tool in the Network Monitoring category of a tech stack.

Top Alternatives of Nagios XI

Nagios XI alternatives & related posts

Icinga logo

Icinga

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A resilient, open source monitoring system
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    Icinga logo
    Icinga
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    Nagios XI logo
    Nagios XI

    related Icinga posts

    One size definitely doesn’t fit all when it comes to open source monitoring solutions, and executing generally understood best practices in the context of unique distributed systems presents all sorts of problems. Megan Anctil, a senior engineer on the Technical Operations team at Slack gave a talk at an O’Reilly Velocity Conference sharing pain points and lessons learned at wrangling known technologies such as Icinga, Graphite, Grafana, and the Elastic Stack to best fit the company’s use cases.

    At the time, Slack used a few well-known monitoring tools since it’s Technical Operations team wasn’t large enough to build an in-house solution for all of these. Nor did the team think it’s sustainable to throw money at the problem, given the volume of information processed and the not-insignificant price and rigidity of many vendor solutions. With thousands of servers across multiple regions and millions of metrics and documents being processed and indexed per second, the team had to figure out how to scale these technologies to fit Slack’s needs.

    On the backend, they experimented with multiple clusters in both Graphite and ELK, distributed Icinga nodes, and more. At the same time, they’ve tried to build usability into Grafana that reflects the team’s mental models of the system and have found ways to make alerts from Icinga more insightful and actionable.

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    Nagios logo

    Nagios

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    Complete monitoring and alerting for servers, switches, applications, and services
    Nagios logo
    Nagios
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    Nagios XI

    related Nagios posts

    Conor Myhrvold
    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 13 upvotes · 1.6M views

    Why we spent several years building an open source, large-scale metrics alerting system, M3, built for Prometheus:

    By late 2014, all services, infrastructure, and servers at Uber emitted metrics to a Graphite stack that stored them using the Whisper file format in a sharded Carbon cluster. We used Grafana for dashboarding and Nagios for alerting, issuing Graphite threshold checks via source-controlled scripts. While this worked for a while, expanding the Carbon cluster required a manual resharding process and, due to lack of replication, any single node’s disk failure caused permanent loss of its associated metrics. In short, this solution was not able to meet our needs as the company continued to grow.

    To ensure the scalability of Uber’s metrics backend, we decided to build out a system that provided fault tolerant metrics ingestion, storage, and querying as a managed platform...

    https://eng.uber.com/m3/

    (GitHub : https://github.com/m3db/m3)

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    Solarwinds logo

    Solarwinds

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    Unlock powerful workflows, automation, and reporting
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      Solarwinds
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      Nagios XI logo
      Nagios XI

      related Datadog posts

      Robert Zuber
      Robert Zuber
      CTO at CircleCI · | 8 upvotes · 461.8K views

      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

      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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      PRTG logo

      PRTG

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      A powerful & easy network monitoring software
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        PRTG
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        Nagios XI
        Dynatrace logo

        Dynatrace

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        Monitor, optimize, and scale every app, in any cloud
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        Dynatrace
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        Nagios XI
        Beats logo

        Beats

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        Lightweight Data Shippers
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          Beats
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          Nagios XI