Cacti vs Kibana vs Nagios

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Cacti

77
160
+ 1
10
Kibana

15.4K
12K
+ 1
256
Nagios

782
916
+ 1
102
Advice on Cacti, Kibana, and Nagios
Needs advice
on
GrafanaGrafana
and
KibanaKibana

From a StackShare Community member: “We need better analytics & insights into our Elasticsearch cluster. Grafana, which ships with advanced support for Elasticsearch, looks great but isn’t officially supported/endorsed by Elastic. Kibana, on the other hand, is made and supported by Elastic. I’m wondering what people suggest in this situation."

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Replies (7)
Recommends
GrafanaGrafana
at

For our Predictive Analytics platform, we have used both Grafana and Kibana

Kibana has predictions and ML algorithms support, so if you need them, you may be better off with Kibana . The multi-variate analysis features it provide are very unique (not available in Grafana).

For everything else, definitely Grafana . Especially the number of supported data sources, and plugins clearly makes Grafana a winner (in just visualization and reporting sense). Creating your own plugin is also very easy. The top pros of Grafana (which it does better than Kibana ) are:

  • Creating and organizing visualization panels
  • Templating the panels on dashboards for repetetive tasks
  • Realtime monitoring, filtering of charts based on conditions and variables
  • Export / Import in JSON format (that allows you to version and save your dashboard as part of git)
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Recommends
KibanaKibana

I use both Kibana and Grafana on my workplace: Kibana for logging and Grafana for monitoring. Since you already work with Elasticsearch, I think Kibana is the safest choice in terms of ease of use and variety of messages it can manage, while Grafana has still (in my opinion) a strong link to metrics

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Bram Verdonck
Recommends
GrafanaGrafana
at

After looking for a way to monitor or at least get a better overview of our infrastructure, we found out that Grafana (which I previously only used in ELK stacks) has a plugin available to fully integrate with Amazon CloudWatch . Which makes it way better for our use-case than the offer of the different competitors (most of them are even paid). There is also a CloudFlare plugin available, the platform we use to serve our DNS requests. Although we are a big fan of https://smashing.github.io/ (previously dashing), for now we are starting with Grafana .

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Recommends
KibanaKibana

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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Recommends
KibanaKibana

Kibana should be sufficient in this architecture for decent analytics, if stronger metrics is needed then combine with Grafana. Datadog also offers nice overview but there's no need for it in this case unless you need more monitoring and alerting (and more technicalities).

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Recommends
GrafanaGrafana

I use Grafana because it is without a doubt the best way to visualize metrics

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Povilas Brilius
PHP Web Developer at GroundIn Software · | 0 upvotes · 327.2K views
Recommends
KibanaKibana
at

@Kibana, of course, because @Grafana looks like amateur sort of solution, crammed with query builder grouping aggregates, but in essence, as recommended by CERN - KIbana is the corporate (startup vectored) decision.

Furthermore, @Kibana comes with complexity adhering ELK stack, whereas @InfluxDB + @Grafana & co. recently have become sophisticated development conglomerate instead of advancing towards a understandable installation step by step inheritance.

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Decisions about Cacti, Kibana, and Nagios
Leonardo Henrique da Paixão
Student, QA Developer at SolarView Business · | 15 upvotes · 158.9K views

The objective of this work was to develop a system to monitor the materials of a production line using IoT technology. Currently, the process of monitoring and replacing parts depends on manual services. For this, load cells, microcontroller, Broker MQTT, Telegraf, InfluxDB, and Grafana were used. It was implemented in a workflow that had the function of collecting sensor data, storing it in a database, and visualizing it in the form of weight and quantity. With these developed solutions, he hopes to contribute to the logistics area, in the replacement and control of materials.

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Matthias Fleschütz
Teamlead IT at NanoTemper Technologies · | 2 upvotes · 68.8K views
  • free open source
  • modern interface and architecture
  • large community
  • extendable I knew Nagios for decades but it was really outdated (by its architecture) at some point. That's why Icinga started first as a fork, not with Icinga2 it is completely built from scratch but backward-compatible with Nagios plugins. Now it has reached a state with which I am confident.
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Pros of Cacti
Pros of Kibana
Pros of Nagios
  • 3
    Rrdtool based
  • 3
    Free
  • 2
    Fast poller
  • 1
    Graphs from snmp
  • 1
    Graphs from language independent scripts
  • 88
    Easy to setup
  • 62
    Free
  • 44
    Can search text
  • 21
    Has pie chart
  • 13
    X-axis is not restricted to timestamp
  • 8
    Easy queries and is a good way to view logs
  • 6
    Supports Plugins
  • 3
    Dev Tools
  • 3
    More "user-friendly"
  • 3
    Can build dashboards
  • 2
    Easy to drill-down
  • 2
    Out-of-Box Dashboards/Analytics for Metrics/Heartbeat
  • 1
    Up and running
  • 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

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Cons of Cacti
Cons of Kibana
Cons of Nagios
    Be the first to leave a con
    • 5
      Unintuituve
    • 3
      Elasticsearch is huge
    • 3
      Works on top of elastic only
    • 2
      Hardweight UI
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      - No public GitHub repository available -

      What is Cacti?

      Cacti is a complete network graphing solution designed to harness the power of RRDTool's data storage and graphing functionality. Cacti provides a fast poller, advanced graph templating, multiple data acquisition methods, and user management features out of the box.

      What is Kibana?

      Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.

      What is Nagios?

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

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      Jobs that mention Cacti, Kibana, and Nagios as a desired skillset
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      What companies use Cacti?
      What companies use Kibana?
      What companies use Nagios?

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      What tools integrate with Cacti?
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      Blog Posts

      May 21 2019 at 12:20AM

      Elastic

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      GitHubPythonReact+42
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      GitHubPythonGit+22
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      GitHubSlackMySQL+44
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      What are some alternatives to Cacti, Kibana, and Nagios?
      Zabbix
      Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.
      Munin
      Munin is a networked resource monitoring tool that can help analyze resource trends and "what just happened to kill our performance?" problems. It is designed to be very plug and play. A default installation provides a lot of graphs with almost no work.
      Cactus
      Cactus makes setting up a website look easy. Choose a template for a blog, portfolio or single page and Cactus generates all files and folders to get you on your way.
      Solarwinds
      Developed by network and systems engineers who know what it takes to manage today's dynamic IT environments, SolarWinds has a deep connection to the IT community.
      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.
      See all alternatives