Grafana Library Panels Download BETTER

Apache ECharts is a powerful and versatile data visualization library providing a wide range of chart types including statistical capabilities. It is written in pure JavaScript and based on zrender, a lightweight graphic library for chart rendering.

The Library panel tab lets you create a library panel that can be reused in other Grafana dashboards. Do this in a single step by selecting The Create library panel at the bottom of the tab. Optionally update the panel library name and select another folder to save it in.

Grafana Library Panels Download

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Grafana monitoring is not possible without panels. Panels can be visualized as free text, a graph, a map, and so on. It can also integrate plugins to extend the features it can offer. The users can customize the style of the panels and create the visualization that suits their needs. A Dashboard is considered a collection of panels containing a set of variables. It offers a lot of possibilities that can be achieved through the features that are offered. Grafana v7 & V8 were major stable releases with interesting features that were highlighted as they were going to offer a new exciting experience to users. Grafana offers many features, and among them, some features can be considered top regarding your needs.

Grafana uses the concept of a library panel which is a reusable panel that can be used in any dashboard you want. The advantage is that a change made in a library panel is also done automatically in all instances where the panel is used. So, it can be used in multiple dashboards. At the same time, the v8 came with a beta feature: Bar chart visualization that represents data with rectangular bars and supports one data frame. It displays the collected metrics from the different data sources and can be visualized in different formats in the panels. Within each dashboard, you will be able to add the monitoring of different statistics. Say you want to see memory usage over time, then you'll probably use a graph.

The only parameter which is maybe not obvious is Access. It specify if the requests to the datasource will be performed from your browser or by the grafana server itself. When setup on proxy, the grafana server instance will perform the requests. So you can secure your database setup by allowing only connections from it.

The process of maintaining grafana dashboards or updating the dashboard JSON files can sometimes become a mess as the size of the JSON files becomes too large to debug it. The average lines of code for a normal grafana dashboard json file sometimes exceeds 700-800. The large json files usually comprise of redundant attributes which most of the times have similar values throughout the file. The fact is that we receive most of our external contributions in this area, hence it becomes vital to pay more attention to maintain the grafana dashboard files without much hustle. In this blog you can find out how grafana dashboards can be managed as code using Grafonnet.

The grafonnet library exposes functions we can use to define our Grafana dashboards. First, we need to import Grafonnet. Grafana.libsonnet works as an entry point and exposes all required functions and interfaces from the library files. The code below is the minimal code required to create a dashboard requiring only a title.

If you wish to migrate from your existing Grafana JSON Dashboards to Grafonnet, all you need to do is install jsonnet package in your application. The other thing you need to do is clone the Grafonnet library, the link for which I have mentioned in the about section. Some prior knowledge of how to code in jsonnet will benefit a lot. If not, you can get some idea from this link - jsonnet. You can start coding your dashboards in jsonnet and generate equivalent json files from that and import them to your existing Grafana Dashboards.

Generate Grafana-compatible JSON containing dashboard objects. The Grafonnet library is the official way to develop dashboards using the Jsonnet language. There is also Weaveworks' grafanalib for Python which is not presented in this article.

As you can see in the configuration, we use k8s-sidecar to automatically collect all dashboard JSON files into one directory for use by Grafana. Each ConfigMap must have the label collect-me: grafana-dashboard to get picked up. The following script creates such ConfigMap manifests. I do not explain here how to integrate it with your specific CI tool, but that should be easy if it works locally. Save the script as render-and-configmap.sh.

By default, hovering over a graph with many series shows them in a box in alphabetical order of the display label, e.g. sorted by {{customer_name}}. Typically however, such as for error rate metrics, you want the top values shown first, since the bottom of the tooltip may be cut off in case of many entries. Go to setting Display > Hover tooltip > Sort order and adjust to your liking (e.g. Decreasing). With jsonnet, use grafana.graphPanel.new(sort="decreasing") (not documented as of 2022-04).

Many metrics only produce non-negative numbers. Graphs with such a metric on the Y axis should therefore have Visualization > Axes > Y-Min set to 0 instead of auto in order to save screen space by not showing the negative area. Another problem is that you often want 0 to be the lower bound, or else Grafana chooses the display range based on the available data. In jsonnet: grafana.graphPanel.new(min=0). Setting the maximum may be helpful if you know the number range (e.g. disk full 0-100%) and want to have a consistent display.

Even if you rely on one Prometheus-compatible source in the beginning, you will very likely add more data sources, or migrate to another one, in the future. Therefore, explicitly define the source in each visualization. In jsonnet, use for example grafana.statPanel.new(datasource='thanos'). In general, do not ever name something default, anywhere. The same applies to the words "old" and "new", since "new" is always the next "old".

I showed how high-level dashboards and main business metrics cover most of your monitoring and incident resolution needs. On top of that, the article explains the advantages of dashboards as code and how to apply that concept, using jsonnet, the Grafonnet library and working scripts to integrate in your developer and CI/CD/GitOps workflow. Lastly, I listed the best practices for dashboard creation and visualization so that your monitoring becomes easier and faster to use.

Auto-deletion of manually authored changes: Remember my term Deleteday from above? Make sure to implement that. At best, your deployment from CI simply takes care to replace all existing dashboards, including those not created by code. Think of the deployment like rsync -a --delete committed-dashboards production-grafana-instance.

Amazon Managed Grafana also supports Grafana API Keys and the Terraform Grafana provider, enabling you to automate the creation of dashboards, data sources, and other Grafana resources. You can track and audit changes made to your Amazon Managed Grafana workspaces with an expanded set of CloudTrail logs, such as when dashboards are deleted, data source permissions are changed, and more. Amazon Managed Grafana now supports open source Grafana version 8.0, which includes new features such as library panels that you can build once and re-use on multiple dashboards, a prometheus metrics browser to quickly find and query metrics, new state timeline and status history visualizations, and much more. Additionally, Amazon Managed Grafana supports nine new data source plugins, such as the JSON and Redis data source plugins, as well as new Grafana Enterprise data source plugins including Salesforce, SAP HANA, Atlassian Jira, and more. To access enterprise data sources, you can upgrade to Grafana Enterprise from the Amazon Managed Grafana console, which will enable access to new and previously supported plugins including AppDynamics, DataDog, Dynatrace, MongoDB, New Relic, Snowflake, VMware Tanzu Observability by Wavefront, and more.

grafonnet-lib is a library, which provides Grafana-specific resources for use in Jsonnet. Both of these tools together allow to describe Grafana dashboards a lot easier and using considerably less text than plain JSON. It uses built-in defaults for describing dashboards, so you only need to provide parameters that are different than the defaults. This saves a lot of lines and effort.

Let's describe a simple dashboard with 3 panels in Jsonnet, using grafonnet-lib. First, let's assign some resources from grafonnet-lib to variables, to make it easier to use them for describing stuff on our dashboard:

Next, we can start building the dashboard itself. The flexibility of Jsonnet allows to adapt it to various situations. Some define panels as variables or functions, and then add these to the dashboard. Some define the panels straight into the dashboard resource or describe them in different files, and include them in various dashboards. Since this is example is quite simple and short, we will go the first route - have everything in a single file, define some local variables describing the panels, and then add them to the dashboard object.

There are 2 distinct methods for adding panels: addPanel, which adds a single panel, and addPanels, which can add more than 1 panel. Most of the examples and documentation I've seen use only addPanel. It works fine, if there are less than 10 panels on the dashboard, which examples mostly do. When there is a need to add more than that, using addPanel can become a problem, so using addPanels is crucial when building larger dashboards with grafonnet-lib.

Grafana provides a library of pre-built dashboards that you can use as-is or customize further. We included Azure Monitor integrations and several dashboards for popular Azure services in the Managed Grafana public preview:

Grafana is an open-source visualization and dashboard tool for any type of data.It allows you to query, visualize, alert on, and understand your metrics nomatter where they are stored. With its powerful query language, you can quicklyanalyze complex data sets and create dynamic dashboards to monitor yourapplications and infrastructure. Grafana also provides an ever-growing libraryof plugins for data sources, panel types, and visualizations. e24fc04721