Prometheus software is an open-source tool useful for metrics-based monitoring and alerting. It is one of the most popular and powerful solutions for Kubernetes monitoring.
Prometheus was built by SoundCloud. It is a standalone open-source project that the Cloud Native Computing Foundation (CNCF) manages.
- It is a powerful tool for collecting and querying metric data.
- It works by pulling(scraping) real-time metrics from applications on a regular basis by sending HTTP requests on metrics endpoints of applications.
- It provides Client libraries that is useful to instrument custom applications including Go, Python, Ruby, Node.js, Java, .NET, Haskell, Erlang, and Rust.
- It collects the data from application services and hosts, then compresses and stores them in a time-series database.
- It offers a simple and powerful data model and a query language (PromQL), and also provides detailed and actionable metrics that let us analyze how your applications and infrastructure are performing.
- A properly tuned and deployed Prometheus cluster can collect millions of metrics every second which makes it very well-suited for complex workloads.
- Prometheus Software is useful alongside Grafana. Grafana is a visualization tool that pulls Prometheus metrics and makes it very easier to monitor.
We can use Prometheus for the following reasons
- Prometheus does not require us to install any custom software or configuration on servers, or even in container images to enable collecting metrics.
- Prometheus does not require our applications to use CPU cycles pushing metrics to some centralized collector.
- Prometheus can easily handle service failure/unavailability gracefully. When the application goes down, Prometheus can record that it was unable to retrieve data.
- In situations where pulling metrics is not feasible (e.g. short-lived jobs) Prometheus provides a Pushgateway that allows applications to push metric data if required.
- All components of Prometheus can be run in containers and it offers better integration with Kubernetes.
Prometheus: How does it work?
Prometheus uses an exposed HTTP endpoint to get metrics. Once an endpoint is available, Prometheus will start scraping numerical data, capture it as a time series and store it in a local database suited to time-series data. You can integrate Prometheus with remote storage repositories also.
Users can leverage questions to create temporary time series from the source. These times series are defined by metric names and labels. Queries are written in PromQL which is a unique language that allows users to choose and aggregate time-series data in real-time.
PromQL can also help us establish alert conditions, resulting in notifications to external systems like email, PagerDuty, or Slack.
Prometheus can display collected data in tabular or graph form and is shown in its web-based user interface. We can also use APIs to integrate with third-party visualization solutions like Grafana.
Prometheus Best Practices
The best practices for implementing Prometheus monitoring are:
- Choose the best exporter
- Label Carefully
- Set actionable alerts
Choose the Best Exporter
Prometheus Software uses exporters to retrieve metrics from systems that cannot easily be scrapped, such as HAProxy or Linux operating systems. Exporters are client libraries that are useful on the target system which export metrics and send them to Prometheus.
While all Prometheus exporters provide similar functionality, we should choose the most relevant exporter for our purposes. This can critically affect the success of our Kubernetes monitoring strategy.
We can research the available exporters and evaluate how each handles the metrics relevant to our workloads. We should also assess the quality of the exporter, according to parameters like user reviews, recent updates, and security advisories.
It is important to label our metrics in a way that provides context. We must establish consistent labeling across different monitoring targets. While we can customize and define our own data we should remember that each label we create uses resources.
On a larger scale, too many labels can increase our overall resource costs. This is why we should strive to use up to 10 labels.
Set Actionable Alerts
A well-defined alerting strategy will help us achieve effective performance monitoring. We should first determine which events or metrics are critical to monitor, and then set a reasonable threshold that can catch issues before they can affect our end users.
Ideally, we should define a threshold that does not cause alert fatigue. We should also ensure the configuration of notifications are proper reach the appropriate team in a timely manner.
Prometheus Software is a very powerful monitoring system, designed to support and work with dynamic environments. Prometheus has gained a reputation in recent times. Its ease of use, versatility and endless integration options makes it a favorite in the monitoring and alerting world.
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