KubeCon + CloudNativeCon North America 2024: Full Schedule

In-person
November 12-15
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Please note: This schedule is automatically displayed in Mountain Standard Time (UTC -7). To see the schedule in your preferred timezone, please select from the drop-down menu to the right, above "Filter by Date." The schedule is subject to change and session seating is available on a first-come, first-served basis.

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5:30pm MST

⚡ Lightning Talk: `Kubectl Debug` Lacks an `IDE` Option. Let’s Fix That! - Mario Loriedo, Red Hat

Tuesday November 12, 2024 5:30pm - 5:35pm MST

Hyatt Regency | Level 4 | Regency Ballroom B

Don't get me wrong. `kubectl debug` is one of my favorite `kubectl` commands. But probably because I like it so much, I am convinced it deserves more love! This talk will present a `kubectl debug` extension that starts an IDE in an ephemeral container for debugging purposes. This extension uses the DevWorkspace operator, which is capable of running lightweight cloud development environments, including the IDE, in containers. If you like debugging by adding breakpoints in an IDE rather than inspecting your application's logs, you should attend this talk.

Speakers

Mario Loriedo

Senior Principal Software Engineer, Red Hat

Mario is a Senior Principal Software Engineer at Red Hat. He works on Podman and on container-based developer tools. He has been a CNCF Ambassador and the tech lead of the Eclipse Che project. He has co-created the Devfile (a CNCF Sandbox Project). He has been a speaker at conferences... Read More →

#1 Mario Loriedo kubectl debug is missing an IDE option pdf

Tuesday November 12, 2024 5:30pm - 5:35pm MST
Hyatt Regency | Level 4 | Regency Ballroom B

⚡ Lightning Talks, Cloud Native Experience

Content Experience Level Any

5:45pm MST

⚡ Lightning Talk: Evaluating Scheduler Efficiency for AI/ML Jobs Using Custom Resource Metrics - Dmitry Shmulevich, NVIDIA

Tuesday November 12, 2024 5:45pm - 5:50pm MST

Hyatt Regency | Level 4 | Regency Ballroom B

Kubernetes deployments frequently utilize custom resources beyond just CPU and memory, such as GPUs, which are essential for AI/ML workloads. While the Metrics API offers insights into CPU and memory usage at both the pod and node levels, it does not provide similar information for custom resources. Although resource requests for custom resources are specified in the pod spec, there is no visibility into how efficiently these resources are utilized at the node and cluster levels. To address this gap, we developed a Prometheus Node Resource Exporter tailored to monitor custom resources. Our case study focuses on evaluating the efficiency of Kubernetes schedulers when handling a high volume of AI/ML jobs, using GPU occupancy on the nodes as the primary indicator. In this lightning talk, we will present a comparative analysis of several scheduling frameworks based on the metrics collected by our custom exporter.

Speakers

Dmitry Shmulevich

Software Engineer, NVIDIA

Dmitry is a software engineer at NVIDIA with over 25 years of experience in software development, specializing in cloud computing for the past eight years. Throughout his career, he has made significant contributions to various systems and projects across the cloud stack. He is also... Read More →

Tuesday November 12, 2024 5:45pm - 5:50pm MST
Hyatt Regency | Level 4 | Regency Ballroom B

⚡ Lightning Talks, Observability

Content Experience Level Any

5:50pm MST

⚡ Lightning Talk: Future-Proofing Kubernetes: Impact of Storage Version Migration and Meaning of Resource Version (RV) - Nilekh Chaudhari, Microsoft

Tuesday November 12, 2024 5:50pm - 5:55pm MST

Hyatt Regency | Level 4 | Regency Ballroom B

Kubernetes relies on API data being actively rewritten to support some maintenance activities related to at-rest storage. Two prominent examples are the versioned schema of stored resources (i.e., the preferred storage schema changing from v1 to v2 for a given resource) and encryption at rest (i.e., rewriting stale data based on a change in how the data should be encrypted). The simplest way to rewrite data is to issue no-op update requests via kubectl. This approach is problematic for any resource that can contain a large amount of data, such as Kubernetes secrets, and it is also impractical to perform without automation, as the number of resources that need migration is always growing. Storage Version Migration (SVM), which is now available as a built-in alpha API since Kubernetes v1.30, helps achieve this. However, the implementation of SVM has significant implications for the entire Kubernetes project and its ecosystem.

Speakers

Nilekh Chaudhari

Software Engineer, Microsoft

Nilekh is a Software Engineer at Microsoft, specializing in Kubernetes. He actively contributes to SIG Auth and SIG API Machinery and is a core maintainer of the Secrets Store CSI Driver, the Azure Provider for the Secrets Store CSI Driver, and the Gatekeeper Library project.

Tuesday November 12, 2024 5:50pm - 5:55pm MST
Hyatt Regency | Level 4 | Regency Ballroom B

⚡ Lightning Talks, Platform Engineering

Content Experience Level Any

6:05pm MST

⚡ Lightning Talk: Running Kind Clusters with GPU Support Using Nvkind - Evan Lezar, NVIDIA

Tuesday November 12, 2024 6:05pm - 6:10pm MST

Hyatt Regency | Level 4 | Regency Ballroom B

Kind is a powerful tool for running local Kubernetes clusters using Docker. It is particularly useful for testing, development, and CI/CD workflows, offering features like multi-node cluster support, easy configuration, and cross-platform compatibility. However, providing access to GPUs in Kind is not a very straightforward process. There is no standard way to inject GPUs into a Kind worker node, and even with a series of "hacks" to make it possible, post-processing is still needed to isolate different sets of GPUs to different nodes. In this lightning talk, we introduce nvkind – a wrapper around Kind that encapsulates the steps necessary to make GPUs available to Kind worker nodes. Ideally, GPU support would have been added to Kind directly, but many challenges exist to make this possible. This talk discusses those challenges, how we've overcome them with nvkind, and the steps needed to eventually support GPUs directly within Kind itself.

Speakers

Evan Lezar

Senior Systems Software Engineer, NVIDIA

Evan Lezar is a Senior Systems Software Engineer on the Cloud Native team at NVIDIA. His focus is making GPUs and other NVIDIA devices easily accessible from containerized environments. This includes driving development and adoption of the Container Device Interface (CDI).

KCNA24 elezar Running Kind Clusters with GPU Support Using nvkind pptx

Tuesday November 12, 2024 6:05pm - 6:10pm MST
Hyatt Regency | Level 4 | Regency Ballroom B

⚡ Lightning Talks, AI + ML

Content Experience Level Any