As developers, we spend a lot of time in our IDEs writing new code, refactoring code, adding tests, fixing bugs and more. And in recent years, IDEs have become powerful tools, helping us developers with anything from interacting with HTTP requests to generally boosting our productivity. So you have to ask — what if we could also prevent security issues in our code before we ship it?

A fundamental element of the Kubernetes microservices system is the services model, which gives teams greater understanding of how their applications are deployed. These objects running within pods and containers, by extension, are RESTful since they’re based on APIs. However, DevOps teams can’t hope to run a tight ship without managing their services. Communication and visibility are absolutely crucial in a Kubernetes system.

An application running in production is a difficult beast to tame. Most experienced developers–ones who spent enough late nights or Saturday mornings trying to break apart a nasty production bug–will try and create the clearest possible picture for their later selves while writing their code, so that they could understand what’s actually going on in the system during an incident.

You’re likely familiar with local debugging—the ability to go through your code line by line to find and eliminate bugs. However, with the ever-increasing complexity of development environments, working efficiently with remote systems is becoming more necessary. In this case, “remote” can mean any machine you don’t have native OS-level access to, such as Virtual Machines, Docker containers, and entirely separate devices accessed over the network.

After building Lightrun for the JVM – an easier way to get a better grasp on production applications written in Java, Scala, and Kotlin – we’re pleased to announce the release of Lightrun’s developer-native observability platform for Python!