Go

An unofficial Grafana data source for You Need A Budget.

If your data source retrieves data from an official, well-defined API, you can simplify your data source configuration by only asking for the relevant data, such as the API token. However, if the user should be able to access data from any given HTTP endpoint, you probably want to let them configure things like authentication headers and query parameters to fit their needs. In this post, I’ll explain how you can build a configurable HTTP-based backend data source.

In my previous post on how to display custom stats for your data source queries, I explained how you can return metrics about the query back to the user. This can be useful to dashboard authors who want to troubleshoot or optimize their queries. As an administrator however, you might want to understand how the data source performs over time, across dashboards. In this post, I’ll show you how you can instrument your backend data source using Prometheus.

The Query inspector in Grafana can be helpful when you’re trying to figure out why your query is failing, or why it’s taking too long to return a result. While Grafana displays some basic information about your query by default, in this post you’ll learn how to add your own stats for you query.

The primary way for a data source to retrieve data is through the query method. But sometimes your data source needs to request auxiliary data on demand, for example to offer auto-completion inside the data source’s query editor. In this post, I want to show you how to add a resource handler to your data source. By adding a resource handler to your backend plugin, you can extend the Grafana HTTP API with your own data source-specific routes.

Load CSV files into Grafana.

A data source plugin for loading JSON APIs into Grafana using JSONPath or JSONata.

Create static query results for prototyping dashboards and testing panels.

A simple JSON Schema to Markdown generator.

Command-line utility application for displaying frequencies as histograms or bar charts, from the standard input.

This meetup will introduce you to Go in the form of a code-along workshop. We’ll help you get your development environment set up and walk you through the language through talks mixed with exercises. If you’ve been thinking about learning Go, this is a perfect chance to get started!

This repository contains gopher artwork, based on the original artwork by Renee French.

Go client for Serialized IO.

More tips and tricks for building a Go client package.

A UI library for terminal applications.

My response to some of the questions I got after my talk in London.

Go has been widely successful for creating tools and infrastructure, but the simplicity of the language also makes for an excellent fit for implementing core business applications. We will look at a few patterns for domain objects and code organization and hopefully we’ll take some additional steps towards Go in the modern enterprise. During this talk we will look at a sample application that demonstrates how a core domain could be implemented in Go.

Up until now, we have only looked at one service in isolation, but this is seldom the case in a service-oriented architecture. For the last post in this blog series on Domain Driven Design in Go we will have a look at how we interact with other services. In particular, we will have a look at two concepts that help us reason about these interactions: application services and bounded contexts.

Learn how to build a Go client for your REST API.

In my previous post I announced a project I have been tinkering with lately; porting an existing DDD sample application to Go. I elaborated a bit about its background and the general structure of the application. In this post we are going to have a look at some of the implementation aspects that I have encountered so far.

In 2008, Citerus developed a Java sample application in close collaboration with Eric Evans, based on the examples in his book. The purpose was to showcase the concepts from DDD in a real-world application. Since then, the application has been ported to other languages such as C# and Ruby. Of course, as a DDD practitioner and a Go developer I thought it might be a fun exercise to try porting it to Go.

Learn how to add circuit breakers to your Go services.

Check if a file belongs to a datset from DAT-o-MATIC.

The routing context from the original DDD Sample Application, written in Go.

Implementing Clean Architecture and DDD building blocks in Go.

DDD Sample Application in Go