In the dynamic landscape of modern application development, managing telemetry across diverse environments and technologies can be a daunting task. Adding to that challenge is the multiple groups that are involved in the software development life cycle within an organization.

Software debugging has undergone many transcendental shifts. These shifts are as fascinating as the transition from the biological origins of the term ‘debugging’ to its computer science incarnation. The moth that caused the first computer bug has led to a metamorphosis of the debugging scope to cover a much broader role in software development over the years. Live debugging is the latest manifestation of this evolution.

According to PYPL (PopularitY of Programming Language), Python has been the most popular programming language worldwide from 2018 to the present. Remarkably, Python’s popularity has grown by 2.5% over the last five years. In contrast, Java, the previously most popular language, has seen a 4.8% decrease in its popularity. While Java is typically faster than Python, Python is easier to read with its simpler syntax.

One of the major trends in software development in the last decade has been “shifting left” responsibilities that have traditionally been under operation’s domain to earlier in the software development life cycle (SDLC). It first came in the form of DevOps where a lot of the software engineering best practices were introduced to the deploy, operate, monitor phases. Such examples include continuous integration and continuous deployment (CI/CD) and Infrastructure as Code (IaC).

Lightrun’s LogOptimizer stands as a groundbreaking automated solution for log optimization and cost reduction in logging. An integral part of the Lightrun IDE plugins, this tool empowers developers to swiftly scan their source code—be it a single file or entire projects—to identify and replace log lines with Lightrun’s dynamic logs, all within seconds.

Live debugging refers to debugging software while running in production without causing any downtime. It has gained popularity in modern software development practices, which drives many critical systems across businesses and industries. In the context of always-on, cloud-native applications, unearthing severe bugs and fixing them in real time is only possible through live debugging. Therefore, live debugging becomes an integral part of any developer’s skill set.

Platform engineering has been one of the hottest keywords in the software community in recent years. As a natural extension of DevOps and the shift-left mentality it fosters, platform engineering is a subfield within software engineering that focuses on building and maintaining tools, workflows, and frameworks that allow developers to build and test their applications efficiently.

Organizations are moving to micro-services and container-based architectures because these modern environments enable speed, efficiency, availability, and the power to innovate and scale more quickly. However, when it comes to troubleshooting distributed cloud native applications, teams face a unique set of challenges due to the dynamic and decentralized nature of these systems.

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.