Cachet vs Prometheus

Overview

Prometheus

Stacks4.8K

Followers3.8K

Votes239

GitHub Stars61.1K

Forks9.9K

Cachet

Stacks79

Followers129

Votes48

GitHub Stars14.7K

Forks1.6K

Cachet vs Prometheus: What are the differences?

Introduction: Cachet and Prometheus are both popular monitoring tools used in the field of IT operations. However, despite serving similar purposes, they have key differences that set them apart from each other.

Data Collection Methodology: Cachet primarily focuses on providing status updates and incident management for services, while Prometheus is designed for metrics collection, storage, and query. Cachet is more service-oriented, while Prometheus is more metric-focused.
Alerting Capabilities: Prometheus has a robust alerting system that allows users to set up and manage alerts based on specific metrics and thresholds. On the other hand, Cachet lacks built-in alerting capabilities and relies on integration with other tools for this functionality.
Scalability and Performance: While both tools are scalable, Prometheus is known for its ability to handle large amounts of data and perform efficiently in high-traffic environments. Cachet, on the other hand, may face performance issues with excessive data loads.
Data Visualization and Dashboarding: Prometheus provides powerful visualization and dashboarding capabilities through tools like Grafana, making it easy for users to create custom dashboards. Cachet, on the other hand, has more limited options for data visualization and dashboarding.
Support for Monitoring Types: Cachet is primarily geared towards service monitoring and incident management, while Prometheus is more versatile in terms of the types of systems and services it can monitor. Prometheus supports a wide range of monitoring types beyond just services.
Community and Ecosystem: Prometheus has a larger and more active community, leading to a wide range of integrations, plugins, and resources available for users. Cachet, while still having a supportive community, may have a more limited ecosystem compared to Prometheus.

In Summary, Cachet and Prometheus differ in data collection methodology, alerting capabilities, scalability, data visualization, support for monitoring types, and community engagement.

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CLI (Node.js)

Manual

Advice on Prometheus, Cachet

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

Susmita

Senior SRE at African Bank

Jul 28, 2020

Needs adviceon

Grafana

Looking for a tool which can be used for mainly dashboard purposes, but here are the main requirements:

Must be able to get custom data from AS400,
Able to display automation test results,
System monitoring / Nginx API,
Able to get data from 3rd parties DB.

Grafana is almost solving all the problems, except AS400 and no database to get automation test results.

869k views869k

Comments

Mat

Head of Cloud at Mats Cloud

Oct 30, 2019

Needs advice

We're looking for a Monitoring and Logging tool. It has to support AWS (mostly 100% serverless, Lambdas, SNS, SQS, API GW, CloudFront, Autora, etc.), as well as Azure and GCP (for now mostly used as pure IaaS, with a lot of cognitive services, and mostly managed DB). Hopefully, something not as expensive as Datadog or New relic, as our SRE team could support the tool inhouse. At the moment, we primarily use CloudWatch for AWS and Pandora for most on-prem.

794k views794k

Comments

Detailed Comparison

Prometheus	Cachet
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.	Cachet is an open source status page system written in PHP, using the Laravel framework.
Dimensional data; Powerful queries; Great visualization; Efficient storage; Precise alerting; Simple operation	Log incidents;Apply a custom stylesheet to the status page;Markdown support for incident messages;RESTful API;Translated into several languages;Easy Heroku deployment;Metrics;Cross-database support: MySQL, PostgreSQL and SQLite
Statistics
GitHub Stars 61.1K	GitHub Stars 14.7K
GitHub Forks 9.9K	GitHub Forks 1.6K
Stacks 4.8K	Stacks 79
Followers 3.8K	Followers 129
Votes 239	Votes 48
Pros & Cons
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	Pros 18 Open Source 7 RESTful API 7 Looks beautiful 5 Scheduled maintenance 5 Free to use
Integrations
Grafana	No integrations available

What are some alternatives to Prometheus, Cachet?

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.

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.

Nagios

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

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.

StatusPage.io

The #1 status and incident communication tool. Use Statuspage to build trust with every incident.

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).

Related Comparisons

Cachet vs Prometheus: What are the differences?

Data Collection Methodology: Cachet primarily focuses on providing status updates and incident management for services, while Prometheus is designed for metrics collection, storage, and query. Cachet is more service-oriented, while Prometheus is more metric-focused.
Alerting Capabilities: Prometheus has a robust alerting system that allows users to set up and manage alerts based on specific metrics and thresholds. On the other hand, Cachet lacks built-in alerting capabilities and relies on integration with other tools for this functionality.
Scalability and Performance: While both tools are scalable, Prometheus is known for its ability to handle large amounts of data and perform efficiently in high-traffic environments. Cachet, on the other hand, may face performance issues with excessive data loads.
Data Visualization and Dashboarding: Prometheus provides powerful visualization and dashboarding capabilities through tools like Grafana, making it easy for users to create custom dashboards. Cachet, on the other hand, has more limited options for data visualization and dashboarding.
Support for Monitoring Types: Cachet is primarily geared towards service monitoring and incident management, while Prometheus is more versatile in terms of the types of systems and services it can monitor. Prometheus supports a wide range of monitoring types beyond just services.
Community and Ecosystem: Prometheus has a larger and more active community, leading to a wide range of integrations, plugins, and resources available for users. Cachet, while still having a supportive community, may have a more limited ecosystem compared to Prometheus.

In Summary, Cachet and Prometheus differ in data collection methodology, alerting capabilities, scalability, data visualization, support for monitoring types, and community engagement.

Cachet vs Prometheus

Overview