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• Debugging Kubernetes applications is challenging due to the lack of a debugger in the pod and the separation of the target executable and process from the debugger client
• Ephemeral containers can be used to run the debugger in the same process namespace as the target and to avoid including unnecessary utilities in the container image
• The presenter demonstrates how to use an IDE to simultaneously debug multiple controllers in Cluster API using breakpoints
• The use of widely-available, open-source tools such as the Delve debugger and Alpine Linux image makes interactive debugging of Kubernetes applications more accessible

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• Debugging in a Kubernetes environment is challenging due to multiple layers of abstraction and the bare bone container problem.
• Cube City or Debug and Cogito are solutions to these challenges.
• Cube City or Debug allows for inspection of a pod even if it has crashed or is a bare bone image.
• Cogito is an open source project that includes a set of opinionated curated platform-specific tools for debugging with Cube City or Debug.
• Anecdote: The presentation provides a demo of using Cube City or Debug to increase logging levels and connect to an ephemeral container with the Busybox image.
• Tags: Kubernetes, debugging, Cube City or Debug, Cogito, ephemeral container, bare bone container problem.

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• Set up tools to check for issues
• Debug to find the source of the issue
• Fix the issue by patching the code or dropping unreported elements
• Submit the patch to upstream or fork the project
• Add the patch to build reports and revisit later if necessary

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• Kubernetes resources have conditions, phases, and states that provide clues about the status of an application
• kubectl commands like get, describe, and events can be used to extract information about the status of an application
• Modifiers like -o can be used to output specific information about an object
• Deployment, ReplicaSet, StatefulSet, and Job have different status conditions that provide information about the status of an application
• Ready is an important concept in Kubernetes that indicates whether a pod is ready to serve requests

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• CNI is the container networking interface that provides an API for networking plugins to manipulate pod sandboxes
• Debugging CNI plugins in production requires a toolbox of tools and techniques
• CNI tool is a useful tool for debugging CNI plugins
• CNI 2.0 needs to address the need for better debugging capabilities

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• Ephemeral containers allow for dynamic deployment of a container that shares pod resources
• They use Linux namespaces to share network and process resources for debugging
• Ephemeral containers provide privileged access to pods for complete debugging capabilities
• They also allow for running commands like ls and ps in containers for easier debugging
• Ephemeral containers can remain listed in the pod after exiting with an exit status
• Restarting the pod will remove any ephemeral containers

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• Structured and easily queryable location for data cataloging is important
• Quality of data should be known to avoid wasting time on processing and feature processing
• Catch regressions early by putting checks upstream in the build process
• Lock device version for on-device logging
• Record metadata for debugging purposes
• Involve subject matter experts for debugging machine learning models