Coordinating different goroutines to achieve a single goal

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Photo by Hunter Harritt on Unsplash

In a previous article I talked about how we can use the context.Context struct to share data and group distinct goroutines. One thing that’s missing from that article, is how to synchronise that group of things. Synchronise concurrent tasks means either wait for all of them to finish before doing something else, or cancelling all of them in case things go wrong. That’s where the sync/errgroup comes to the scene. Here are the official docs for the package. The package name conveys two things: used to synchronise, and we are going to…


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There’s no one size fits all when it comes to testing apps

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Photo by Scott Graham on Unsplash

Most people agree that testing software is one of the most important activities software engineers perform. Nothing matters if a piece of software is very fast or well written but it doesn’t accomplish what it is intended to. Testing is a very interesting discipline and definitely an important one to master if you want to become a better software engineer. In this article, we are going to review some very good patterns for improving the tests of a Golang application. We will go through various different scenarios that differ in nature, complexity, and objectives we want to achieve with tests.

Testing package


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Harnessing one of the most useful packages in go

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Photo by Pietro Jeng on Unsplash

Applications in golang use Contexts for controlling and managing very important aspects of reliable applications, such as cancellation and data sharing in concurrent programming. This may sound trivial but in reality, it’s not that so. The entry point for the contexts in golang is the context package. It is extremely useful and probably one of the most versatile packages of the entire language. If you haven’t come across anything dealing with contexts yet, you probably will very soon (or maybe you just didn’t pay much attention to it). The usage of context is so widespread that multiple other packages rely…


Tracing requests in distributed systems

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Photo by Stephen Dawson on Unsplash

In this article we will be focusing on the implementation of the architecture presented in the previous article. Take your time to review it.

The entire code can be found on my github repo. I’ll be creating and pasting some gists here for reference, those will only contain the most relevant and important pieces of the code. So I really encourage you to check my github for a full reference. …


Understanding OpenTelemetry and distributed tracing

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Photo by Luke Chesser on Unsplash

Running distributed systems in production is not an easy task. Access is limited, therefore issues are hard to track down and understand as well as to reproduce in other environments. No other environment is like production, no matter how similar it may seem. Usually you rely on different pieces of information to troubleshoot and understand what is happening to your applications in production. The most common ones are logs and custom metrics. This two things are really powerful when combined and used together. With logs you can understand and troubleshoot exactly what happened with a specific request or a scenario…


Combining SonarQube and gosec to get more information out of your source code

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Photo by Carlos Muza on Unsplash

Static analysis (or static code analysis) is a great technique to find issues related to security, performance, coverage, coding style, and some times even logic without running your application. Usually this type of analysis is run against the source code of the application only. No execution required.

This is a very easy and powerful type of analysis to run against new code being integrated. Most tools are designed to run as part of the continuous integration pipeline because of that. You can compare the results from the new code and create acceptance rules based on that. This will help the…


How to harness immutability to enhance readability and stability in your Golang app

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Photo by Ferenc Almasi on Unsplash

The concept of immutability is very simple. After an object (or struct) is created, it can never be changed. It’s immutable. Although the concept seems simple, it’s not always easy to use it or benefit from it.

As most things in computer science (and life), there are multiple ways of achieving the same result, in regards to immutability it is not different. You have to consider it as another tool in your toolkit and use what works best for each issue you face. One very strong use case for immutability is when you are working with concurrent programming. Golang was…


Leveraging Golang’s concurrency model to create concurrent data pipelines for data intensive applications

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Photo by Mika Baumeister on Unsplash

Data is a vital piece for all applications. Applications mainly receive data, process it and then create some sort of output out of it. The amount of data that is available nowadays is immense, which brings many challenges when trying to make sense out of it and transforming it into useful information. Besides the usual data system process, we also have to consider the data that is generated by the execution of such systems, like logs and metrics. Everything is data.

Therefore, there’s a growing need for data driven applications. It’s not unusual to have systems only dealing with moving…


Creating pipelines for handling requests

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Photo by Remy Ludo Gieling on Unsplash

When working with web apps, like web API’s, web sites, or any application that exposes a web server and handle requests, the most common behaviour is to handle each URL in a different way. Return different web pages, persist data in a storage, fetch and return data as JSON, among many other things.

However, some tasks need to be executed regardless of the request you receive in a generic way. Copying and pasting the code or a call to a separate function, although being an option, is not the best way of approaching this issue. One problem with that approach…


Simple yet powerful technique to implement dependency injection in golang

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Photo by Markus Spiske on Unsplash

Dependency injection is great technique for decoupling code, making it more stable, testable and robust. The technique consists in designing your code to receive dependencies. In object oriented languages, we usually use the class constructor to do it. So when someone creates an instance of your object, all dependencies will be injected into it. That makes perfect sense as dependencies shouldn’t be part of interface signatures, otherwise all implementations would have to receive the dependencies as parameters for doing their job. But each implementation can have different dependencies based on what they do. Well you get the problem, right?

Awesome…

Ricardo Linck

Software Engineer. Distributed systems lover, golang and .net enthusiast. Curious by nature. https://github.com/ricardolinck

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