Alternatives to Zabbix logo

Alternatives to Zabbix

Nagios, Graphite, Datadog, InfluxDB, and Prometheus are the most popular alternatives and competitors to Zabbix.
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What is Zabbix and what are its top alternatives?

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.
Zabbix is a tool in the Monitoring Tools category of a tech stack.
Zabbix is an open source tool with 2.3K GitHub stars and 692 GitHub forks. Here’s a link to Zabbix's open source repository on GitHub

Top Alternatives to Zabbix

  • Nagios
    Nagios

    Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License. ...

  • Graphite
    Graphite

    Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand ...

  • 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! ...

  • InfluxDB
    InfluxDB

    InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out. ...

  • Prometheus
    Prometheus

    Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true. ...

  • PRTG
    PRTG

    It can monitor and classify system conditions like bandwidth usage or uptime and collect statistics from miscellaneous hosts as switches, routers, servers and other devices and applications. ...

  • LibreNMS
    LibreNMS

    It is an auto-discovering PHP/MySQL/SNMP based network monitoring which includes support for a wide range of network hardware and operating systems including Cisco, Linux, FreeBSD, Juniper, Brocade, Foundry, HP and many more. ...

  • Grafana
    Grafana

    Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins. ...

Zabbix alternatives & related posts

Nagios logo

Nagios

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Complete monitoring and alerting for servers, switches, applications, and services
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PROS OF NAGIOS
  • 53
    It just works
  • 28
    The standard
  • 12
    Customizable
  • 8
    The Most flexible monitoring system
  • 1
    Huge stack of free checks/plugins to choose from
CONS OF NAGIOS
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    related Nagios posts

    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 15 upvotes · 3.1M 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)

    See more
    Shared insights
    on
    PrometheusPrometheusNagiosNagios

    I am new to DevOps and looking for training in DevOps. Some institutes are offering Nagios while some Prometheus in their syllabus. Please suggest which one is being used in the industry and which one should I learn.

    See more
    Graphite logo

    Graphite

    376
    394
    39
    A highly scalable real-time graphing system
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    PROS OF GRAPHITE
    • 16
      Render any graph
    • 9
      Great functions to apply on timeseries
    • 7
      Well supported integrations
    • 5
      Includes event tracking
    • 2
      Rolling aggregation makes storage managable
    CONS OF GRAPHITE
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      related Graphite posts

      Conor Myhrvold
      Tech Brand Mgr, Office of CTO at Uber · | 15 upvotes · 3.1M 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)

      See more

      A huge part of our continuous deployment practices is to have granular alerting and monitoring across the platform. To do this, we run Sentry on-premise, inside our VPCs, for our event alerting, and we run an awesome observability and monitoring system consisting of StatsD, Graphite and Grafana. We have dashboards using this system to monitor our core subsystems so that we can know the health of any given subsystem at any moment. This system ties into our PagerDuty rotation, as well as alerts from some of our Amazon CloudWatch alarms (we’re looking to migrate all of these to our internal monitoring system soon).

      See more
      Datadog logo

      Datadog

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      Unify logs, metrics, and traces from across your distributed infrastructure.
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      PROS OF DATADOG
      • 135
        Monitoring for many apps (databases, web servers, etc)
      • 106
        Easy setup
      • 86
        Powerful ui
      • 82
        Powerful integrations
      • 69
        Great value
      • 53
        Great visualization
      • 45
        Events + metrics = clarity
      • 40
        Custom metrics
      • 40
        Notifications
      • 38
        Flexibility
      • 18
        Free & paid plans
      • 15
        Great customer support
      • 14
        Makes my life easier
      • 9
        Adapts automatically as i scale up
      • 8
        Easy setup and plugins
      • 7
        Super easy and powerful
      • 6
        AWS support
      • 6
        In-context collaboration
      • 5
        Rich in features
      • 4
        Docker support
      • 4
        Cost
      • 3
        Automation tools
      • 3
        Source control and bug tracking
      • 3
        Simple, powerful, great for infra
      • 3
        Cute logo
      • 3
        Expensive
      • 3
        Easy to Analyze
      • 3
        Full visibility of applications
      • 3
        Monitor almost everything
      • 3
        Best than others
      • 2
        Good for Startups
      • 2
        Free setup
      • 2
        Best in the field
      • 1
        APM
      CONS OF DATADOG
      • 17
        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

      We are looking for a centralised monitoring solution for our application deployed on Amazon EKS. We would like to monitor using metrics from Kubernetes, AWS services (NeptuneDB, AWS Elastic Load Balancing (ELB), Amazon EBS, Amazon S3, etc) and application microservice's custom metrics.

      We are expected to use around 80 microservices (not replicas). I think a total of 200-250 microservices will be there in the system with 10-12 slave nodes.

      We tried Prometheus but it looks like maintenance is a big issue. We need to manage scaling, maintaining the storage, and dealing with multiple exporters and Grafana. I felt this itself needs few dedicated resources (at least 2-3 people) to manage. Not sure if I am thinking in the correct direction. Please confirm.

      You mentioned Datadog and Sysdig charges per host. Does it charge per slave node?

      See more
      InfluxDB logo

      InfluxDB

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      167
      An open-source distributed time series database with no external dependencies
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      PROS OF INFLUXDB
      • 53
        Time-series data analysis
      • 29
        Easy setup, no dependencies
      • 24
        Fast, scalable & open source
      • 21
        Open source
      • 19
        Real-time analytics
      • 6
        Continuous Query support
      • 5
        Easy Query Language
      • 4
        HTTP API
      • 4
        Out-of-the-box, automatic Retention Policy
      • 1
        Offers Enterprise version
      • 1
        Free Open Source version
      CONS OF INFLUXDB
      • 4
        Instability
      • 1
        HA or Clustering is only in paid version

      related InfluxDB posts

      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.

      See more
      Prometheus logo

      Prometheus

      2.8K
      3.3K
      238
      An open-source service monitoring system and time series database, developed by SoundCloud
      2.8K
      3.3K
      + 1
      238
      PROS OF PROMETHEUS
      • 46
        Powerful easy to use monitoring
      • 38
        Flexible query language
      • 32
        Dimensional data model
      • 27
        Alerts
      • 23
        Active and responsive community
      • 22
        Extensive integrations
      • 19
        Easy to setup
      • 12
        Beautiful Model and Query language
      • 7
        Easy to extend
      • 6
        Nice
      • 3
        Written in Go
      • 2
        Good for experimentation
      • 1
        Easy for monitoring
      CONS OF PROMETHEUS
      • 12
        Just for metrics
      • 6
        Bad UI
      • 6
        Needs monitoring to access metrics endpoints
      • 4
        Not easy to configure and use
      • 3
        Supports only active agents
      • 2
        Written in Go
      • 2
        TLS is quite difficult to understand
      • 2
        Requires multiple applications and tools
      • 1
        Single point of failure

      related Prometheus posts

      Conor Myhrvold
      Tech Brand Mgr, Office of CTO at Uber · | 15 upvotes · 3.1M 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)

      See more
      Matt Menzenski
      Senior Software Engineering Manager at PayIt · | 14 upvotes · 231.7K views

      Grafana and Prometheus together, running on Kubernetes , is a powerful combination. These tools are cloud-native and offer a large community and easy integrations. At PayIt we're using exporting Java application metrics using a Dropwizard metrics exporter, and our Node.js services now use the prom-client npm library to serve metrics.

      See more
      PRTG logo

      PRTG

      43
      56
      0
      A powerful & easy network monitoring software
      43
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      + 1
      0
      PROS OF PRTG
        Be the first to leave a pro
        CONS OF PRTG
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          related PRTG posts

          LibreNMS logo

          LibreNMS

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          146
          0
          Opensource Auto-discoverying network monitoring system
          45
          146
          + 1
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          PROS OF LIBRENMS
            Be the first to leave a pro
            CONS OF LIBRENMS
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              related LibreNMS posts

              Grafana logo

              Grafana

              13.2K
              10.6K
              402
              Open source Graphite & InfluxDB Dashboard and Graph Editor
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              PROS OF GRAFANA
              • 84
                Beautiful
              • 67
                Graphs are interactive
              • 57
                Free
              • 56
                Easy
              • 33
                Nicer than the Graphite web interface
              • 24
                Many integrations
              • 17
                Can build dashboards
              • 10
                Easy to specify time window
              • 9
                Dashboards contain number tiles
              • 8
                Can collaborate on dashboards
              • 5
                Open Source
              • 5
                Click and drag to zoom in
              • 5
                Integration with InfluxDB
              • 4
                Authentification and users management
              • 4
                Threshold limits in graphs
              • 3
                It is open to cloud watch and many database
              • 3
                Simple and native support to Prometheus
              • 2
                Great community support
              • 2
                Alerts
              • 2
                You can visualize real time data to put alerts
              • 2
                You can use this for development to check memcache
              • 0
                Grapsh as code
              • 0
                Plugin visualizationa
              CONS OF GRAFANA
              • 1
                No interactive query builder

              related Grafana posts

              Conor Myhrvold
              Tech Brand Mgr, Office of CTO at Uber · | 15 upvotes · 3.1M 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)

              See more
              Matt Menzenski
              Senior Software Engineering Manager at PayIt · | 14 upvotes · 231.7K views

              Grafana and Prometheus together, running on Kubernetes , is a powerful combination. These tools are cloud-native and offer a large community and easy integrations. At PayIt we're using exporting Java application metrics using a Dropwizard metrics exporter, and our Node.js services now use the prom-client npm library to serve metrics.

              See more