The power of kata

Every day, many developers of enterprise systems have to face complex problems for which incorrect solutions often end with a loss of enormous amounts of money. That’s why they constantly learn new paradigms, frameworks, tools, read books and broaden their knowledge in technical conferences. It’s a lot of time and effort! All this dedication is on behalf of creating a high-quality product — but what is the result? Obviously it depends (as every software architect would say), but too many times the result isn’t the best. It takes a while, has got too many errors, often the code quality isn’t high… And let’s better not mention testing. Why is all this happening then? Everyone does their best, spends additional time on learning, so what exactly is missing? The answer is quite straightforward - constant practicing. Let’s say a few words about “code kata” which can make a remedy for the mentioned problems.

Using ESLint to improve your app’s performance

Let me start with a story. Once upon a time I stumbled upon an excellent article by Philip Walton where he describes how expensive script evaluations could (and should!) be deferred until the browser is idle or they are actually needed. One of the examples that awakened my interest was creating an instance of the Intl.DateTimeFormat object, as I was using this great API quite often but never thought it can cause real performance problems. Turns out it can, especially if used inside loops. Apart from the technique described in Philip’s article, another solution is to simply reuse Intl.DateTimeFormat instances instead of creating them every time.

Common code approach: from rich libraries to rich environment

We run over 800 microservices in our on-premise and public clouds. They are developed by hundreds of engineers in various technologies: from the most popular Java and Kotlin, through Scala, Clojure, Python, NodeJS, Golang, to less mainstream like Elixir or Swift. All these applications need to handle common technical concerns: logging, monitoring, service discovery, tracing, internationalization, security and more. How to provide common solutions to these requirements in such a heterogeneous setup? In this post I’m going to explain how we originally solved this problem with common libraries and how we are currently changing our runtime environment to make things even easier.

Persisting application state

An application can be defined as a set of use cases. It often happens that use case A requires a previously executed use case B for its execution. In such situation, it should be ensured that use case B has been executed while executing use case A. To achieve this, application state that is common to both use cases, is introduced. The state must be persisted to be visible to more than one use case. Most often, various types of databases are used for this purpose. While working with source code, I have encountered various methods of persisting the application state. I also came up with my own variations. In this post I will make a subjective comparison of these methods based on specific criteria.

Hexagonal Architecture by example - a hands-on introduction

When you go through articles related to Hexagonal Architecture (HA) you usually search for practical examples. HA isn’t simple, that’s why most trivial examples make readers even more confused, though it is not as complex as many theoretical elucidations present it. In most posts you have to scroll through exact citations or rephrased definitions of concepts such as Ports and Adapters or their conceptual diagrams. They have already been well defined and described by popular authors i.e. Alistair Cockburn or Martin Fowler. I assume you already have a general understanding of Domain Driven Design and that you understand terms such as Ports and Adapters. I’m not a HA expert, yet I use it everyday and I find it useful. The only reason I write this post is to show you that Hexagonal Architecture makes sense, at least if your service is a little more than a JsonToDatabaseMapper.

Migrating to Service Mesh

This year turns 21. The company, while serving millions of Poles in their online shopping, has taken part in many technological advances. Breaking the monolith, utilising public cloud offerings, machine learning, you name it. Even though many technologies we use might seem as just following the hype, their adoption is backed by solid reasoning. Let me tell you the story of a project I’ve had the privilege of working on.

At Allegro, we build and maintain some of the most distributed and scalable applications in Central Europe. This poses many challenges, starting with architecture and design, through the choice of technologies, code quality and performance tuning, and ending with deployment and devops. In this blog, our engineers share their experiences and write about some of the interesting things taking place at the company.