HAMi became a CNCF Incubating project

HAMi was originally known as k8s-vGPU-scheduler and today stands for Heterogeneous AI computing virtualisation Middleware. It enables slicing a physical GPU into units by memory/core/device count, enforcing hard runtime isolation, and scheduling Pods using binpack, spread, and topology-aware policies. You can learn more about this project from this overview.

HAMi joined the CNCF Sandbox in August, 2024. Two weeks ago, the CNCF TOC voted to promote it to the incubating level. This change was formally announced yesterday.

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Buildpacks graduates, k8gb incubates

Following the CNCF TOC votes that happened over the last weekend, two CNCF projects were promoted to the next level:

1. Buildpacks, a set of specifications and tooling that transform application source code into container images that can run on any cloud, became a Graduated project. It was started by Pivotal and Heroku in January 2018, joined the CNCF Sandbox in October 2018, and became Incubated in November 2020. The companies that adopted Buildpacks include Bloomberg, Google, Microsoft, Red Hat, Salesforce, and VMware by Broadcom.

2. k8gb, a Kubernetes global balancer, became an Incubating project. It originated in Absa Group in 2019 and joined the CNCF Sandbox in March 2021. Current k8gb adopters include Eficode, Millennium bcp, and PagBank.

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KubeSchool by Portainer

As Neil Cresswell, CEO of Portainer, said on Reddit, one of his engineers recently asked him to help better understand Kubernetes architecture and components. Answering this request, he decided to go bigger and launched KubeSchool.

It's an educational website featuring 15 chapters on Kubernetes basics for beginners. They cover the core ideas behind K8s, its main components, pluggable layers (CNI, CSI, CRDs, etc.), and production-ready recommendations.

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Confidential Containers became a CNCF Incubating project

Another level up has just happened in the CNCF, with its TOC accepting moving Confidential Containers to the Incubating level. This project enables confidential computing by leveraging hardware-based TEEs (Trusted Execution Environments) to protect containers and data by encrypting data during computation.

Confidential Containers started in 2021 by Red Hat, Intel, IBM, and other companies. It was accepted into the CNCF Sandbox in March 2022. Today, this technology is used in IBM LinuxONE, Red Hat OpenShift, Kubermatic KubeOne, Alibaba Cloud, and several other solutions.

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Kubeflow became a CNCF Graduated project

The summer series of CNCF level-ups keeps going, and Kubeflow has just joined the list of the organisation’s most mature (i.e. Graduated) projects. The CNCF Technical Oversight Committee (TOC) voted for this graduation last Friday.

Kubeflow is a machine learning toolkit for Kubernetes that serves as a foundation for K8s-based AI platforms. Its subprojects include Pipelines for end-to-end ML workflows, Trainer for distributed AI model training and LLM fine-tuning, Katib for AutoML, and a Kubernetes operator for Apache Spark.

Kubeflow originated in Google, with its first public announcement in 2017. It was accepted into the CNCF as an Incubating project in July 2023. Today, its adopters include Alibaba Cloud, AWS, Cisco, Huawei, IBM, NVIDIA, Red Hat, and Tencent.

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OpenTelemetry got a one-command Linux setup

The OpenTelemetry Packaging SIG introduced a ready-to-use opentelemetry package for Linux distributions that installs the OpenTelemetry Injector together with the OpenTelemetry SDKs and auto-instrumentation packages for various programming languages (Java, .NET, Node.js, and Python).

It is now available as an APT repository (for Debian, Ubuntu, and derivatives) and a YUM repository (for Fedora, RHEL, and derivatives). Find more details in this announcement or read the full instructions on GitHub.

#news #observability

Thought of running agents on Kubernetes more efficiently? Here’s a project from Google that you might find useful.

Agent Substrate is an experimental system for running agents and similar workloads on Kubernetes at scale, providing specialised scheduling and controls to improve scalability and reduce latency. It relies on Kubernetes Pods and Pod autoscaling (but not K8s control plane) and manages the lifecycle of "actors" (agents or similar apps): creating and destroying them, assigning them to Pods, and routing traffic to them. It handles OCI containers at the kernel level via gVisor, so it can work with apps that are built on any stack.

▶️ GitHub repo

Language: Go | License: Apache 2.0 | 912 ⭐️

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What to expect in Kubernetes v1.37

The next Kubernetes release, v1.37, is scheduled later this month, on August 26th. It will come with several important deprecations (e.g., static Pods won't longer reference Secrets/ConfigMaps, the ipvs mode will be removed from kube-proxy) and over 20 new features, including Recreate update strategy for StatefulSets, volume health monitor, default Pod sysctls in Kubelet, CompositePodGroup API, and others.

Learn more about these upcoming changes from the first related articles published last week:

- Kubernetes 1.37: Deep dive into new alpha features on Palark tech blog;
- Kubernetes v1.37 Sneak Peek on the official Kubernetes blog.

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New free Kubernetes workshop

Konrad Heimel announced the Kubernetes Practitioner Workshop, a GitHub repo that offers structured educational content for engineers looking to learn Kubernetes concepts and practice them. It comes with:

- 28 topics (e.g., Containers, StatefulSet, The operator pattern, or Helm), each presented with 20-30 slides and accompanied with a practical lab requiring 15-30 minutes to complete;
- two types of environments for labs: a specific namespace on a shared cluster or a local kind cluster;
- downloadable PDFs provided as GitHub releases;
- facilitator guide with additional notes on setting up the required environment and running this workshop.

All content is free and available as Open Source (under the Zero-Clause BSD permissive license).

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Community has met KYAML, a strict subset of standard YAML for Kubernetes (KEP-5295), with mixed feelings. However, it will become stable in the upcoming Kubernetes v1.37 release. Thus, yesterday’s Kubernetes blog post on what KYAML is and how to use it* may be helpful.

* TL;DR: via kubectl -o kyaml or yamlfmt (from Kubernetes itself or Google).

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