This article is a case study of how we improved stability in our critical application. It’s mostly a technical analysis of what happens in fresh Java based instance, how JIT Compiler toyed with us at application start and how we learned to control it.
As a part of a broader initiative of refreshing Allegro platform, we are upgrading our internal libraries to Spring Boot 3.0 and Java 17. The task is daunting and filled with challenges, however overall progress is steady and thanks to the modular nature of our code it should end in finite time. Everyone who has performed such an upgrade knows that you need to expect the unexpected and at the end of the day prepare for lots of debugging. No amount of migration guide would prepare you for what’s coming in the field. In the words of Donald Rumsfeld there are unknown unknowns and we need to be equipped with the tools to uncover these unknowns and patch them up. In this blog post I’d like to walk you through a process that should show where the application hangs, although there seems to be nothing wrong with it. I will also show that you don’t always know what code you have – problem known as dependecy hell, place we got quite cosy in during this upgrade.
We all make errors, but some errors seem so ridiculous we wonder how anyone, let alone we ourselves, could have done such a thing. This is, of course, easy to notice only after the fact. Below, I describe a series of such errors which we recently made in one of our applications. What makes it interesting is that initial symptoms indicated a completely different kind of problem than the one actually present.
Kotlin may seem like a new kid on the block — itʼs been officially released only in February. Its history however dates a few years back and itʼs mature and stable enough to be used for developing solid reliable applications. Therefore at Allegro we decided to give it a chance — we built our new shiny server-side system using Kotlin as its primary language and we do not regret it.
CPU time and memory are the two primary resources every performance-sensitive application needs to use wisely. Java is now the language of choice for many such systems. While most developers have at least basic understanding of computational complexity, I believe that few, especially among those who primarily use Virtual-Machine based languages such as Java, understand well how their applications manage memory. This is not only a very interesting topic in itself, but can also help in improving performance of Java applications or in understanding better the behavior of common Java-based databases such as Apache Cassandra.
