Operations | Monitoring | ITSM | DevOps | Cloud

KoolKits (Kubernetes toolkits) are language-specific container images that contain a (highly-opinionated) set of tools for debugging applications running in Kubernetes pods. You can read more about the motivation behind this project here. Those images are intended for use with the new kubectl debug feature, which spins up Ephemeral containers for interactive troubleshooting. A KoolKit will be pulled by kubectl debug, spun up as a container in your pod, and have the ability to access the same process namespace as your original container.

Watch as engineering leaders from Netflix, Meta (Facebook), and HashiCorp dive deep into how you too can empower your developers to focus more on the core tasks and less on the mundane. Toil - begone!

Learn debugging basics in Java, Kotlin, JavaScript (NodeJS) and Python. On IntelliJ/IDEA, VSCode, WebStorm and PyCharm. In this quick tutorial we'll walk through the basics of conditional breakpoints and various core debugging principals.

Check out how Lightrun can help you observe, understand and debug your production application in Python and Node.js. Amit Shuster, Lightrun Product Manager, will show you how to use Lightrun logs and snapshots to quickly resolve issues.

How to authenticate your plugin How to create Lightrun Actions How to view log, snashot and metric data

Learn how to add on-demand, real-time Lightrun logs to your application - without ever stopping the running process.

Learn how to use Lightrun snapshots to explore all stack variables, walk through the stack frames and evaluate expressions at runtime - all without ever stopping the running process.

Learn how to measure the performance of your application by adding on-demand Lightrun metrics - while your application is still running.

Learn how Taboola implemented Lightrun to enable truly seamless progressive delivery using real-time production debugging.

Join JFrog’s Baruch Sadogursky and Lightrun’s Tom Granot as they investigate how high-performing engineering teams remain agile throughout the entire software production lifecycle, from development through deployment and all the way to observing and maintaining high-quality production systems at scale.