Operations | Monitoring | ITSM | DevOps | Cloud

Back in November 2020 Apple’s M1 chip was introduced and as the end users moved forward to M1 based Macs it became mandatory to build applications that are compatible with the new technology. The M1 chip has incredible improvements and features but I won’t cover them in this post.There are many resources on the internet covering this and I encourage you to explore them. In this post I will cover several challenges I tackled while setting up an M1 build.

Monitoring and observability have increased with software applications moving from monolithic to distributed microservice architectures. While observability and application monitoring share similar definitions, they also have some differences. The purpose of both monitoring and observability is to find issues in an application. However, monitoring aims to capture already known issues and display them on a dashboard to understand their root cause and the time they occurred.

Say you have a new code base to study or picked up an open source project. You might be a seasoned developer for whom this is another project in a packed resume. Alternatively, you might be a junior engineer for whom this is the first “real” project. It doesn’t matter! With completely new source code repositories, we still know nothing… The seasoned senior might have a leg up in finding some things and recognizing patterns.

A couple of weeks ago, we had a great time hosting the workshop you can see below with Vlad Mihalcea. It was loads of fun and I hope to do this again soon! In this workshop we focused on Spring Boot performance but most importantly on Hibernate performance, which is a common issue in production environments. It’s especially hard to track since issues related to data are often hard to perceive when debugging locally.

Python has become one of the most popular programming languages globally and is particularly popular in data science and artificial intelligence. Python’s popularity can be attributed to its ease of use and readability and the large ecosystem of libraries and frameworks built around it. Python is also popular among developers working on cloud-based applications, as they can use it to orchestrate complex workflows.

Let’s get real – as developers, we spend a significant amount of time staring at a screen and trying to figure out why our code isn’t working. According to Coralogix, there are an average of 70 bugs per 1000 lines of code. That’s a solid 7% worth of blimps, bumps, and bugs. In addition to this, fixing a bug can take 30 times longer than writing an actual line of code. But it doesn’t have to be this way.

We’re delighted to announce that Lightrun for Web IDEs is now available for our beta users! Lightrun for the Web is now supported in three different IDEs: If you want to check out the individual plugins, check out the respectable documentation articles: Lightrun’s users are now able to connect to their live applications directly from the browser, without having to download one of our dedicated plugins – and enjoy the full suite of Lightrun features right in the browser.

Debugging is an essential step in software development, as it allows developers to fix errors before releasing the software to the public. Debugging tools can be integrated into code editors, making the debugging process more efficient. This tutorial will show you how to debug node.js in Visual Studio Code.

Let’s look at IllegalArgumentException, which is one of the most common types of exceptions that Java developers deal with. We’ll see when and why IllegalArgumentException usually occurs, whether it’s a checked or unchecked exception, as well as how to catch and when to throw it. We’ll use a few examples based on common Java library methods to describe some of the ways to handle IllegalArgumentException.

The Java Collections Framework was a huge leap forward when it was introduced as part of Java 2 (JDK 1.2). Thanks to the included collection classes we finally moved beyond the limits of Vector and Hashtable to more mature and generic solutions. With the introduction of streams and functional concepts in Java 8 the framework took everything to the next level. One of the core principles underlying the framework is coding to the interface.