The main purpose of the open-source monitoring system Prometheus is to collect and analyse time-series data. Its monitoring functions might be useful for settings like Kubernetes and other containerized systems. It is a cross-platform monitoring tool that lets you gather and handle data identically from servers, containers, and apps.
What the Prometheus Architecture Offers
Now that we have cleared things out, let’s examine the actual operation of the Prometheus Architecture:
There are several subsystems inside the Prometheus system. Even though they may all be included, there is a lot of flexibility in choosing which of the following will actually be used in a Prometheus deployment.
Prometheus may collect metrics directly from tasks or, in the case of transient jobs, indirectly via a push gateway after the work is completed. The scraped samples are kept locally and rules are applied to them to aggregate and create new time series from existing data and to send alerts depending on user-defined triggers. Grafana is the standard method for visualising the gathered data, even though Prometheus has a comprehensive Web dashboard that may be utilised or other API consumers. Choosing the right kinds of prometheus metrics is essential here.
Let’s look at a few of the elements that have contributed to Prometheus’ explosive growth in popularity as a monitoring tool:
- Prometheus is a pull-based system since it actively scrapes its targets to collect metrics.
- Because Prometheus is configured on the server instead of the client, you may access any option without limitations. This means that you have the freedom to decide who to scrape and how often.
- The alerting system built-in, Prometheus, alerts the Alert manager based on the customisable parameters specified in the configuration files. From there, it may inform further services, including Google Hangout and Slack, among others.
The Disclosure of Materials
When you instruct it to, Prometheus can automatically eliminate previous targets and locate new ones on the fly. A range of service discovery tools are provided by Prometheus to assist users in finding appropriate scrape targets. Consul, Kubernetes, and several more systems belong to this group.
Reliability It can be scaled to amazing heights. Using the federation concept, several Prometheus servers may be combined into a single, cohesive system.
Lastly, Prometheus offers a useful query language known as PromQL (Prometheus Query Language) that enables users to instantly choose and combine time-series data.
There are several metrics available on the Prometheus platform that may be used in a variety of scenarios. Would it be possible for us to briefly discuss each of them?
It displays a data histogram.
A histogram is a kind of statistical representation that may be used to assess the frequency with which observations of a value fall into discrete bins. One tool for calculating how long it takes to finish an HTTP request is a histogram. Prometheus will provide an estimate based on how often requests fit into certain categories rather than tracking the amount of time it takes for each request. Prometheus will be able to respond with more dependability as a result.
Conclusion
We’ve spoken about Prometheus’s features, functionality, and reasons for being the most widely used platform available right now. We have gone through the four most important metrics that you will encounter in your day-to-day work with Prometheus, which utilises a vast array of information gathered from servers.
