Today’s applications are designed to be always available and serve users 24/7. Performing live debugging on such applications is akin to doctors operating on a patient. Since the advent of the “as a service” model, software is like a living, breathing entity, akin to an anatomical system. Operating on such entities requires more dexterity on the developer’s part, to ensure that the software application lives on while being debugged and improved continuously.

In a previous post, we looked at the remote debugging features of Visual Studio Code and how Lightrun takes the remote debugging experience to the next level. This post will examine how Lightrun enables Python remote debugging in PyCharm, the Python IDE from JetBrains.

Throughout the third quarter of this year, Lightrun continued its efforts to develop a multitude of solutions and improvements focused on enhancing developer productivity. Their primary objectives were to improve troubleshooting for distributed workload applications, reduce mean time to resolution (MTTR) for complex issues, and optimize costs in the realm of cloud computing. Read more below the main new features as well as the key product enhancements that were released in Q3 of 2023!

Organizations today must embrace a modern observability approach to develop user-centric and reliable software. This isn’t just about tools; it’s about processes, mentality, and having developers actively involved throughout the software development lifecycle up to production release. In recent years, the concept of observability has gained prominence in the world of software development and operations.

This post will discuss remote debugging in VS Code and how to improve the remote debugging experience to maximize debugging productivity for developers. Visual Studio Code, or VS Code, is one of the most popular IDEs. Within ten years of its initial release, VS Code has garnered the top spot among popularity indices, and its community is growing steadily. Developers love VS Code not only for its simplicity but also due to its rich ecosystem of extensions, including the support for debugging.

In this age of complex software systems, code instrumentation patterns define specific approaches to debugging various anomalies in business logic. These approaches offer more options beyond the built-in debuggers to improve developer productivity, ultimately creating a positive impact on the software’s commercial performance. In this post, let’s examine the various code instrumentation patterns for Node.js.

When it comes to debugging performance related issues, the range of these issues together with their root cause can be overwhelming to developers.

Debugging in production is always a necessary evil. No matter how well your code is written and reviewed, bugs are bound to appear, and their consequences are there for your users to see. While debugging any app has challenges, debugging legacy systems is a different ballgame. From unfamiliarity with the codebase to a lack of knowledge about the tech, your developers can find themselves aimlessly searching for solutions where solutions don’t exist.