Kibana vs Nagios vs Prometheus

Overview

Nagios

Stacks811

Followers1.1K

Votes102

GitHub Stars57

Forks38

Kibana

Stacks20.6K

Followers16.4K

Votes262

GitHub Stars20.8K

Forks8.5K

Prometheus

Stacks4.8K

Followers3.8K

Votes239

GitHub Stars61.1K

Forks9.9K

Kibana vs Nagios vs Prometheus: What are the differences?

Introduction:

Kibana, Nagios, and Prometheus are all popular monitoring tools used in the IT industry. While they serve a similar purpose, each tool has its specific features and differences that cater to different monitoring needs.

1. **Data Visualization**:
Kibana specializes in data visualization, offering rich graphical presentations of data stored in Elasticsearch, making it ideal for real-time data analysis and visualization.

2. **Alerting Capabilities**:
Nagios is known for its robust alerting system, which allows users to set up and receive alerts based on predefined thresholds, ensuring timely responses to critical issues in the IT environment.

3. **Data Collection**:
Prometheus stands out in its ability to collect data using a pull model, scraping metrics from monitored targets, making it capable of handling dynamic environments and services.

4. **Monitoring Approach**:
Nagios follows a traditional monitoring approach, primarily focusing on server and network monitoring, whereas Prometheus is geared towards microservices and containerized environments, providing visibility into complex ecosystems.

5. **Scalability**:
While Nagios may face scalability challenges in large and dynamic environments, Prometheus is highly scalable and efficient due to its distributed architecture, enabling seamless monitoring of thousands of targets.

6. **Integration Capabilities**:
Kibana offers seamless integration with the ELK (Elasticsearch, Logstash, Kibana) stack, making it a preferred choice for organizations already using the ELK stack for log management and analysis.

In Summary, Kibana excels at data visualization, Nagios is strong in alerting capabilities, and Prometheus is tailored for dynamic environments with its pull-based data collection method and scalability.

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CLI (Node.js)

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Advice on Nagios, Kibana, Prometheus

Matt

Senior Software Engineering Manager at PayIt

May 3, 2021

Decidedon

Grafana

Prometheus

Kubernetes

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.

1.1M views1.1M

Comments

Raja Subramaniam

Aug 27, 2019

Needs adviceon

Prometheus

Kubernetes

Sysdig

We have Prometheus as a monitoring engine as a part of our stack which contains Kubernetes cluster, container images and other open source tools. Also, I am aware that Sysdig can be integrated with Prometheus but I really wanted to know whether Sysdig or sysdig+prometheus will make better monitoring solution.

779k views779k

Comments

StackShare

Jun 25, 2019

Needs advice

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."

663k views663k

Comments

Detailed Comparison

Nagios	Kibana	Prometheus
Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.	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.	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.
Monitor your entire IT infrastructure;Spot problems before they occur;Know immediately when problems arise;Share availability data with stakeholders;Detect security breaches;Plan and budget for IT upgrades;Reduce downtime and business losses	Flexible analytics and visualization platform;Real-time summary and charting of streaming data;Intuitive interface for a variety of users;Instant sharing and embedding of dashboards	Dimensional data; Powerful queries; Great visualization; Efficient storage; Precise alerting; Simple operation
Statistics
GitHub Stars 57	GitHub Stars 20.8K	GitHub Stars 61.1K
GitHub Forks 38	GitHub Forks 8.5K	GitHub Forks 9.9K
Stacks 811	Stacks 20.6K	Stacks 4.8K
Followers 1.1K	Followers 16.4K	Followers 3.8K
Votes 102	Votes 262	Votes 239
Pros & Cons
Pros 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	Pros 88 Easy to setup 65 Free 45 Can search text 21 Has pie chart 13 X-axis is not restricted to timestamp Cons 7 Unintuituve 4 Works on top of elastic only 4 Elasticsearch is huge 3 Hardweight UI	Pros 47 Powerful easy to use monitoring 38 Flexible query language 32 Dimensional data model 27 Alerts 23 Active and responsive community Cons 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
Integrations
No integrations available	Logstash Elasticsearch Beats	Grafana

What are some alternatives to Nagios, Kibana, Prometheus?

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.

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

Sensu

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.

Graphite

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

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

StatsD

It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

Jaeger

Jaeger, a Distributed Tracing System

Telegraf

It is an agent for collecting, processing, aggregating, and writing metrics. Design goals are to have a minimal memory footprint with a plugin system so that developers in the community can easily add support for collecting metrics.

Sysdig

Sysdig is open source, system-level exploration: capture system state and activity from a running Linux instance, then save, filter and analyze. Sysdig is scriptable in Lua and includes a command line interface and a powerful interactive UI, csysdig, that runs in your terminal. Think of sysdig as strace + tcpdump + htop + iftop + lsof + awesome sauce. With state of the art container visibility on top.

Related Comparisons

Kibana vs Nagios vs Prometheus: What are the differences?

Introduction:

Kibana, Nagios, and Prometheus are all popular monitoring tools used in the IT industry. While they serve a similar purpose, each tool has its specific features and differences that cater to different monitoring needs.

1. **Data Visualization**:
Kibana specializes in data visualization, offering rich graphical presentations of data stored in Elasticsearch, making it ideal for real-time data analysis and visualization.

2. **Alerting Capabilities**:
Nagios is known for its robust alerting system, which allows users to set up and receive alerts based on predefined thresholds, ensuring timely responses to critical issues in the IT environment.

3. **Data Collection**:
Prometheus stands out in its ability to collect data using a pull model, scraping metrics from monitored targets, making it capable of handling dynamic environments and services.

4. **Monitoring Approach**:
Nagios follows a traditional monitoring approach, primarily focusing on server and network monitoring, whereas Prometheus is geared towards microservices and containerized environments, providing visibility into complex ecosystems.

5. **Scalability**:
While Nagios may face scalability challenges in large and dynamic environments, Prometheus is highly scalable and efficient due to its distributed architecture, enabling seamless monitoring of thousands of targets.

6. **Integration Capabilities**:
Kibana offers seamless integration with the ELK (Elasticsearch, Logstash, Kibana) stack, making it a preferred choice for organizations already using the ELK stack for log management and analysis.

In Summary, Kibana excels at data visualization, Nagios is strong in alerting capabilities, and Prometheus is tailored for dynamic environments with its pull-based data collection method and scalability.

Kibana vs Nagios vs Prometheus

Overview