Visual Studio Code (VScode) is an open-source and cross-platform source-code editor. It was ranked the most popular development tool in the Stack Overflow 2021 Developer Survey, with 70% of the respondents using it as their primary editor. VScode allows you to use a few programming languages like JavaScript and TypeScript. Still, you need an extension if you want to use any other programming language and include extra functionalities to improve your code.
Parsing bugs are the gift that keeps giving in the age of APIs. We use a service; it works perfectly in debugging, QA, etc. Then some user input that made its way to the web request, returns a result we just can’t parse. Unfortunately, there isn’t much we can do at this stage. We need to understand why the failure occurred and how we can workaround it and fix it.
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.
