For more information on how to set up Grafana, check out our article on Getting Started With Grafana. Grafana is easy to use and easy to set up. Grafana can build great graphs, alert on complex alert rules, and push the alerting information directly to your smart phone with notifications. Grafana can do what time-series databases can’t.
You can use Prometheus directly in-app, and skip the hassle of installation, remote-storage set up, and other configurations.Īlthough Grafana is only a dashboard tool, and not a full server monitoring tool, it is pivotal in any monitoring stack. To solve the issues with remote-storage and independently managing an in-house Prometheus setup, MetricFire offers Hosted Prometheus. Prometheus is not built for multi-process multi-threaded applications, but work-arounds are possible. The second problem occurs when monitoring multi-process applications as seen in many Python web apps. This can be time-consuming and expensive. To get long term storage on the order of months and years, you’ll need to set up remote storage. The first problem is long-term storage, where the open source project is only configured to store data for a maximum of 14 days. However, Grafana is a better dashboard tool, which supersedes the Expression Browser for long-term data monitoring, alerting, and notification. You can query with Prometheus’s own query language called PromQL, which is a powerful tool when combined with Prometheus’s multi-dimensional data structure. Prometheus has its own dashboard, called the Prometheus Expression Browser, which is a good console for deep diving into your metrics. Prometheus is built to monitor Kubernetes and Docker, and is almost always used alongside Grafana for visualizations. With one installation you get data collectors, the Prometheus server, data aggregation with a complex labeling system, visualization, querying, indexing, alerts and notifications. Prometheus is a one-stop shop for time-series monitoring. Prometheus is a newer product, developed by soundcloud in 2012. If you’re interested in Graphite, definitely check out Hosted Graphite as a way to get around some of the issues with Graphite, and to make it easier to scale. Hosted Graphite by MetricFire improves upon Graphite, and offers a solution to the biggest issues with Graphite. However, Graphite has a few persisting issues, such as data aggregation, cluster-native storage, and a lack of good alerting. You can check the adaptations on the GitHub project, such as the official docker image and test scripts. Recently there has been a push to make Graphite more compatible with Docker and Kubernetes. For more information on the Graphite architecture, read up on Graphite Architecture and Concepts.
This usually requires the use of a daemon, such as StatsD or collectd. Graphite requires clients push metrics to it, while it listens and receives metrics.
Each piece plays a specific role, and is interchangeable with other technology if the developer prefers something else. There is Carbon, Whisper, Graphite server, and Graphite Web UI. Graphite is built on a set of subcomponents that work together as one monitoring stack. This tool was one of the first open source server monitoring tools, and it has been a strong player on the field ever since. It has over 5,000 stargazers on GitHub and 300 contributors.
Graphite is a tried and true time-series monitoring tool that was first released in 2008. These tools are all currently being maintained, and have huge communities of contributors and users. Let’s take a look at the best open source monitoring tools available today. Similarly, it’s common to use Prometheus and Elasticsearch simultaneously, one for time-series and the other for logs. For example, it’s very common for AWS CloudWatch users to pull Grafana into their stack for better dashboarding, despite already having a wide range of tools at their disposal. Users often apply open source monitoring tools in conjunction with other open source tools, or with proprietary tools. However, you can save a lot when using open source for specific and focused tasks.
Of course, using open source can become expensive due to higher head-count costs, usually caused by the time and expertise needed to make the open source software run. If you do it right, using open source server monitoring can save you money. Open source server monitoring tools allow us to gain functionality without spending more. In today’s development environment, many engineers are opting for open source monitoring to get more freedom and customizations. There are hundreds of server monitoring tools out there, all with slightly different levels of customer support and functionalities.