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Icinga vs Prometheus: What are the differences?
Introduction
Icinga and Prometheus are two popular monitoring systems used by organizations to ensure the availability and performance of their systems. While both serve the same purpose, there are several key differences between them. In this article, we will explore these differences and highlight their specific features and capabilities.
Data Collection: Icinga is a system that primarily relies on active checks to monitor the health of various services and systems. It sends requests and collects data from the target systems at regular intervals. On the other hand, Prometheus follows a pull-based model, where it scrapes metrics from the target systems by periodically querying them. Thus, Icinga actively collects data, while Prometheus pulls data from the systems.
Data Storage: Icinga does not have its own data storage mechanism. It relies on external databases like MySQL or PostgreSQL to store monitoring data. Prometheus, in contrast, has its own local time-series database that stores all collected metrics by default. This built-in storage of Prometheus simplifies the deployment and eliminates the need for external databases.
Alerting System: Icinga has a powerful alerting system that allows users to set up custom-defined alerts based on various criteria, such as thresholds, patterns, or specific conditions. It provides flexible notification methods like email, SMS, or integration with chat platforms. Prometheus also has an alerting system, but it is tightly integrated with its data collection and query language. It allows users to define alerting rules based on metrics and perform complex queries to create more sophisticated alerts.
Query Language and Visualization: Icinga does not provide a dedicated query language or visualization tools. It relies on external tools like Grafana to analyze and visualize the collected monitoring data. Prometheus, on the other hand, has its own query language called PromQL, which allows users to write powerful and flexible queries on the collected metrics. It also has built-in visualizations and graphing capabilities, enabling users to explore and analyze metrics directly within the Prometheus ecosystem.
Scalability: Icinga can be scaled horizontally by setting up multiple Icinga instances and distributing the monitoring workload. However, achieving high scalability with Icinga requires manual configuration and management. Prometheus, on the other hand, is designed to be highly scalable by default. It supports federation, allowing multiple Prometheus instances to collect and aggregate metrics. Additionally, it integrates well with other systems like Kubernetes, making it easier to monitor large and complex environments.
Ecosystem and Integrations: Icinga has a rich ecosystem of plugins and integrations, making it compatible with a wide range of systems and technologies. It can monitor various protocols, devices, and services out of the box. Prometheus also has a growing ecosystem and offers numerous integrations with popular monitoring tools and frameworks. It has native support for exporters, making it easy to collect metrics from different systems. The availability of exporters and integrations helps users to easily extend Prometheus' monitoring capabilities.
In Summary, Icinga emphasizes active data collection, relies on external databases for storage, and offers a customizable alerting system, while Prometheus follows a pull-based approach, has its own database, provides a query language and visualizations, supports federation for scalability, and has a growing ecosystem of integrations.
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.
You can look out for Prometheus Instrumentation (https://prometheus.io/docs/practices/instrumentation/) Client Library available in various languages https://prometheus.io/docs/instrumenting/clientlibs/ to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.
Hi, We have a situation, where we are using Prometheus to get system metrics from PCF (Pivotal Cloud Foundry) platform. We send that as time-series data to Cortex via a Prometheus server and built a dashboard using Grafana. There is another pipeline where we need to read metrics from a Linux server using Metricbeat, CPU, memory, and Disk. That will be sent to Elasticsearch and Grafana will pull and show the data in a dashboard.
Is it OK to use Metricbeat for Linux server or can we use Prometheus?
What is the difference in system metrics sent by Metricbeat and Prometheus node exporters?
Regards, Sunil.
If you're already using Prometheus for your system metrics, then it seems like standing up Elasticsearch just for Linux host monitoring is excessive. The node_exporter is probably sufficient if you'e looking for standard system metrics.
Another thing to consider is that Metricbeat / ELK use a push model for metrics delivery, whereas Prometheus pulls metrics from each node it is monitoring. Depending on how you manage your network security, opting for one solution over two may make things simpler.
Hi Sunil! Unfortunately, I don´t have much experience with Metricbeat so I can´t advise on the diffs with Prometheus...for Linux server, I encourage you to use Prometheus node exporter and for PCF, I would recommend using the instana tile (https://www.instana.com/supported-technologies/pivotal-cloud-foundry/). Let me know if you have further questions! Regards Jose
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.
this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here https://www.apmexperts.com/observability/ranking-the-observability-offerings/
I worked with Datadog at least one year and my position is that commercial tools like Datadog are the best option to consolidate and analyze your metrics. Obviously, if you can't pay the tool, the best free options are the mix of Prometheus with their Alert Manager and Grafana to visualize (that are complementary not substitutable). But I think that no use a good tool it's finally more expensive that use a not really good implementation of free tools and you will pay also to maintain its.
- 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.
Pros of Icinga
Pros of Prometheus
- Powerful easy to use monitoring47
- Flexible query language38
- Dimensional data model32
- Alerts27
- Active and responsive community23
- Extensive integrations22
- Easy to setup19
- Beautiful Model and Query language12
- Easy to extend7
- Nice6
- Written in Go3
- Good for experimentation2
- Easy for monitoring1
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Cons of Icinga
Cons of Prometheus
- Just for metrics12
- Bad UI6
- Needs monitoring to access metrics endpoints6
- Not easy to configure and use4
- Supports only active agents3
- Written in Go2
- TLS is quite difficult to understand2
- Requires multiple applications and tools2
- Single point of failure1