Two years ago, my friend José Paumard held the talk 'Concurrent and Asynchronous Programming : Loom' at the Geneva Java User Group. In his talk, he mentioned that the Spring team would need to completely redesign their approach to transaction: his reasoning was that the transactions are implemented on top of ThreadLocal object and Loom’s virtual threads break this approach.

Last week, I described a gloomy situation: all public TLS certificate providers log your requests. By browsing through the subdomains, one can get their respective IP addresses. If one of them points to your home route, they know your general location. I analyzed several solutions and decided to use wildcard certificates, which don’t leak subdomain information, while continuing to use Let’s Encrypt. My solution caters to my Synology NAS, as it’s the one I’m using.

I recently learned about a new way to leak your privacy, and it’s a scary one. Before going further, know that I’m not a network engineer: perhaps if you work in this field, you’ve known it for your whole career, but it’s quite new to me. Let me share my findings, and you can judge for yourself. Since the original post was quite lengthy, I have broken it down into two installments: the problem and the solution. The situation I own my own domain.

You learn by comparing to what you already know. I was recently bitten by assuming Rust worked as Java regarding transitive dependency version resolution. In this post, I want to compare the two. Dependencies, transitivity, and version resolution Before diving into the specifics of each stack, let’s describe the domain and the problems that come with it. When developing any project above Hello World level, chances are you’ll face problems that others have faced before.

Creational patterns were first described in the famous Gang of Four’s Design Patterns. The book presents each pattern in a dedicated chapter and follows a strict structure for each one: intent, motivation, applicability, structure, participants, collaborations, consequences, implementation, sample codes, known uses, and related patterns. The intent pattern presents a succinct goal of the pattern, while the applicability tells when you should use it.

I’ve quite a lengthy experience with GitHub workflows, but not up to the point where I can claim I’m an expert. However, I recently developed a new workflow, and it prompted me to write this post. Feel free to add your own. What are GitHub workflows? A workflow is a configurable automated process that will run one or more jobs.

When I first started attending conferences, I diligently tried to write down notes and publish them. It forced me to actively listen to the talks I was attending. With the number of conferences rising, I couldn’t keep the rhythm. When I switched my career path to Developer Advocate, I drastically diminished the number of talks I attended in favor of the hallway track. As a result, the last conference 'report' I wrote was JPrime’s in 2022.

Last week, I described several approaches to OpenTelemetry on the JVM, their requirements, and their different results. This week, I want to highlight several gotchas found across stacks in the zero-code instrumentation. The promise of OpenTelemetry Since its inception, OpenTelemetry has unified the 3 pillars of observability. In the distributed tracing space, it replaced proprietary protocols Zipkin and Jaeger.