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  1. Stackups
  2. DevOps
  3. Monitoring
  4. Monitoring Tools
  5. Cacti vs Kibana vs Prometheus

Cacti vs Kibana vs Prometheus

OverviewDecisionsComparisonAlternatives

Overview

Cacti
Cacti
Stacks89
Followers202
Votes10
Kibana
Kibana
Stacks20.6K
Followers16.4K
Votes262
GitHub Stars20.8K
Forks8.5K
Prometheus
Prometheus
Stacks4.8K
Followers3.8K
Votes239
GitHub Stars61.1K
Forks9.9K

Cacti vs Kibana vs Prometheus: What are the differences?

# Introduction
Cacti, Kibana, and Prometheus are popular monitoring tools used in IT environments. Each tool has its unique features and capabilities that cater to different needs and requirements.

# 1. **Data Visualization**:
Cacti is specialized in graphing network bandwidth utilization, while Kibana focuses on visualizing and analyzing log data. Prometheus, on the other hand, is more focused on time series data monitoring with customizable dashboards.

# 2. **Data Collection**:
Cacti relies on SNMP for data collection, Kibana integrates with Elasticsearch for data indexing and querying, and Prometheus uses its own time-series database and a pull model to collect metrics from monitored targets.

# 3. **Alerting**:
Cacti lacks built-in alerting capabilities and requires external plugins for alerting functionality. Kibana also lacks native alerting features, while Prometheus has robust alerting capabilities with alert manager for defining and managing alerts.

# 4. **Scalability**:
Cacti is suitable for small to medium-sized environments due to its limitations in scalability. Kibana can scale horizontally by adding more nodes to the Elasticsearch cluster. Prometheus is designed to be highly scalable and can handle large deployments with thousands of targets.

# 5. **Integration**:
Cacti has limited integrations with other tools and technologies, making it less flexible for complex monitoring setups. Kibana can be easily integrated with various data sources and systems, providing more flexibility in monitoring different types of data. Prometheus has extensive integrations with cloud-native technologies, making it a popular choice for monitoring containerized environments.

# 6. **Querying and Analysis**:
Cacti lacks advanced querying and analysis capabilities, mainly focusing on graphing historical data. Kibana offers powerful querying and visualization tools for log analysis and monitoring. Prometheus has a PromQL language for querying metrics, enabling advanced analysis and troubleshooting.

In Summary, Cacti, Kibana, and Prometheus differ in data visualization focus, data collection methods, alerting capabilities, scalability, integrations, and querying and analysis tools.

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Advice on Cacti, Kibana, Prometheus

Matt
Matt

Senior Software Engineering Manager at PayIt

May 3, 2021

DecidedonGrafanaGrafanaPrometheusPrometheusKubernetesKubernetes

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
Raja Subramaniam

Aug 27, 2019

Needs adviceonPrometheusPrometheusKubernetesKubernetesSysdigSysdig

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
matteo1989it
matteo1989it

Jun 26, 2019

ReviewonKibanaKibanaGrafanaGrafanaElasticsearchElasticsearch

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

757k views757k
Comments

Detailed Comparison

Cacti
Cacti
Kibana
Kibana
Prometheus
Prometheus

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.

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.

Unlimited number of graph items can be defined for each graph optionally utilizing CDEFs or data sources from within cacti.;Automatic grouping of GPRINT graph items to AREA, STACK, and LINE[1-3] to allow for quick re-sequencing of graph items.;Auto-Padding support to make sure graph legend text lines up.;Graph data can be manipulated using the CDEF math functions built into RRDTool. These CDEF functions can be defined in cacti and can be used globally on each graph.;Data sources can be created that utilize RRDTool's "create" and "update" functions. Each data source can be used to gather local or remote data and placed on a graph.
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
-
GitHub Stars
20.8K
GitHub Stars
61.1K
GitHub Forks
-
GitHub Forks
8.5K
GitHub Forks
9.9K
Stacks
89
Stacks
20.6K
Stacks
4.8K
Followers
202
Followers
16.4K
Followers
3.8K
Votes
10
Votes
262
Votes
239
Pros & Cons
Pros
  • 3
    Free
  • 3
    Rrdtool based
  • 2
    Fast poller
  • 1
    Graphs from snmp
  • 1
    Graphs from language independent scripts
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
RRDtool
RRDtool
Logstash
Logstash
Elasticsearch
Elasticsearch
Beats
Beats
Grafana
Grafana

What are some alternatives to Cacti, Kibana, Prometheus?

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.

Nagios

Nagios

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

Netdata

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

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

Sensu

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

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

Lumigo

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

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

Jaeger, a Distributed Tracing System

Telegraf

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.

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