diff --git a/.claude/commands/pr.md b/.claude/commands/pr.md index fa3190a1fb2..6aea481e3c0 100644 --- a/.claude/commands/pr.md +++ b/.claude/commands/pr.md @@ -2,7 +2,7 @@ description: Format code, stage changes, and create a pull request allowed-tools: - Bash -argument-hint: [base-branch] +argument-hint: "[base-branch]" --- # Prepare and create pull request diff --git a/docs/book/component-guide/orchestrators/kubernetes.md b/docs/book/component-guide/orchestrators/kubernetes.md index db4a1f5a1ed..202849ae073 100644 --- a/docs/book/component-guide/orchestrators/kubernetes.md +++ b/docs/book/component-guide/orchestrators/kubernetes.md @@ -6,6 +6,8 @@ description: Orchestrating your pipelines to run on Kubernetes clusters. Using the ZenML `kubernetes` integration, you can orchestrate and scale your ML pipelines on a [Kubernetes](https://kubernetes.io/) cluster without writing a single line of Kubernetes code. +The orchestrator uses standard Kubernetes APIs and works on managed cloud clusters (EKS, GKE, AKS), enterprise platforms like Red Hat OpenShift and SUSE Rancher, and self-managed clusters on-premises or in your own cloud. + This Kubernetes-native orchestrator is a minimalist, lightweight alternative to other distributed orchestrators like Airflow or Kubeflow. Overall, the Kubernetes orchestrator is quite similar to the Kubeflow orchestrator in that it runs each pipeline step in a separate Kubernetes pod. However, the orchestration of the different pods is not done by Kubeflow but by a separate master pod that orchestrates the step execution via topological sort. @@ -20,15 +22,18 @@ This component is only meant to be used within the context of a [remote ZenML de You should use the Kubernetes orchestrator if: +* you already have a Kubernetes cluster—managed cloud, Red Hat OpenShift, SUSE Rancher, or self-managed on-premises. * you're looking for a lightweight way of running your pipelines on Kubernetes. * you're not willing to maintain [Kubeflow Pipelines](kubeflow.md) on your Kubernetes cluster. * you're not interested in paying for managed solutions like [Vertex](vertex.md). ## How to deploy it -The Kubernetes orchestrator requires a Kubernetes cluster in order to run. There are many ways to deploy a Kubernetes cluster using different cloud providers or on your custom infrastructure, and we can't possibly cover all of them, but you can check out our [our production guide](https://docs.zenml.io/user-guides/production-guide). +The Kubernetes orchestrator requires a Kubernetes cluster (version 1.21 or higher recommended). + +There are many ways to deploy a Kubernetes cluster using different cloud providers or on your custom infrastructure, and we can't possibly cover all of them, but you can check out our [production guide](https://docs.zenml.io/user-guides/production-guide). -If the above Kubernetes cluster is deployed remotely on the cloud, then another pre-requisite to use this orchestrator would be to deploy and connect to a [remote ZenML server](https://docs.zenml.io/getting-started/deploying-zenml/). +If the Kubernetes cluster is deployed remotely, another prerequisite is to deploy and connect to a [remote ZenML server](https://docs.zenml.io/getting-started/deploying-zenml/). ## How to use it @@ -42,7 +47,7 @@ To use the Kubernetes orchestrator, we need: * [Docker](https://www.docker.com) installed and running. * A [remote artifact store](../artifact-stores/README.md) as part of your stack. * A [remote container registry](../container-registries/README.md) as part of your stack. -* A Kubernetes cluster [deployed](kubernetes.md#how-to-deploy-it) +* A Kubernetes cluster [deployed](kubernetes.md#how-to-deploy-it) (version 1.21 or higher recommended) * [kubectl](https://kubernetes.io/docs/tasks/tools/#kubectl) installed and the name of the Kubernetes configuration context which points to the target cluster (i.e. run`kubectl config get-contexts` to see a list of available contexts) . This is optional (see below). {% hint style="info" %} diff --git a/docs/book/getting-started/deploying-zenml/deploy-with-helm.md b/docs/book/getting-started/deploying-zenml/deploy-with-helm.md index f132952e6c2..f27dcc320c5 100644 --- a/docs/book/getting-started/deploying-zenml/deploy-with-helm.md +++ b/docs/book/getting-started/deploying-zenml/deploy-with-helm.md @@ -6,13 +6,15 @@ description: Deploying ZenML in a Kubernetes cluster with Helm. If you wish to manually deploy and manage ZenML in a Kubernetes cluster of your choice, ZenML also includes a Helm chart among its available deployment options. +The chart uses standard Kubernetes APIs and works on managed cloud clusters (EKS, GKE, AKS), enterprise platforms like Red Hat OpenShift and SUSE Rancher, and self-managed clusters on-premises or in your own cloud. + You can find the chart on this [ArtifactHub repository](https://artifacthub.io/packages/helm/zenml/zenml), along with the templates, default values and instructions on how to install it. Read on to find detailed explanations on prerequisites, configuration, and deployment scenarios. ## Prerequisites You'll need the following: -* A Kubernetes cluster +* A Kubernetes cluster (version 1.21 or higher recommended) * Optional, but recommended: a MySQL-compatible database reachable from the Kubernetes cluster (e.g. one of the managed databases offered by Google Cloud, AWS, or Azure). A MySQL server version of 8.0 or higher is required * the [Kubernetes client](https://kubernetes.io/docs/tasks/tools/#kubectl) already installed on your machine and configured to access your cluster * [Helm](https://helm.sh/docs/intro/install/) installed on your machine diff --git a/docs/book/getting-started/zenml-pro/deploy-control-plane-k8s.md b/docs/book/getting-started/zenml-pro/deploy-control-plane-k8s.md index e947cfd6438..2246a490a4d 100644 --- a/docs/book/getting-started/zenml-pro/deploy-control-plane-k8s.md +++ b/docs/book/getting-started/zenml-pro/deploy-control-plane-k8s.md @@ -17,6 +17,8 @@ layout: This guide provides step-by-step instructions for deploying ZenML Pro on Kubernetes using Helm charts. All components run within your infrastructure with zero external dependencies. +ZenML Pro deployments use standard Kubernetes APIs and work on managed cloud clusters (EKS, GKE, AKS), enterprise platforms like Red Hat OpenShift and SUSE Rancher, and self-managed clusters on-premises or in your own cloud. + ## Deployment Architecture All components run entirely within your Kubernetes cluster and infrastructure: diff --git a/docs/book/getting-started/zenml-pro/deploy-prerequisites.md b/docs/book/getting-started/zenml-pro/deploy-prerequisites.md index 58e52da73fe..ca93eed11c7 100644 --- a/docs/book/getting-started/zenml-pro/deploy-prerequisites.md +++ b/docs/book/getting-started/zenml-pro/deploy-prerequisites.md @@ -238,12 +238,14 @@ The Control Plane and Workspace Server components are completely independent fro | Infrastructure Type | Support Level | |---------------------|---------------| -| Kubernetes (managed or self-hosted, 1.24+) | ✅ Officially supported and documented | +| Kubernetes (1.24+) | ✅ Officially supported and documented | | Container-as-a-Service (ECS, Cloud Run, etc.) | ⚠️ Possible but not documented | | Serverless containers (Fargate, Lambda, etc.) | ⚠️ Possible but not documented | | Virtual machines with Docker (VMware, VirtualBox, etc.) | ⚠️ Possible but not documented | | Docker-compose | ✅ Can be provided upon request for local testing purposes | +These Helm-based deployments use standard Kubernetes APIs and work on managed cloud clusters (EKS, GKE, AKS), enterprise platforms like Red Hat OpenShift and SUSE Rancher, and self-managed clusters on-premises or in your own cloud. + {% hint style="warning" %} While ZenML Pro can theoretically run on any container orchestration platform, only Kubernetes deployments are officially fully supported and documented. If you require a different deployment target, please contact [cloud@zenml.io](mailto:cloud@zenml.io) to discuss your requirements. {% endhint %} diff --git a/docs/book/getting-started/zenml-pro/deploy-workspace-k8s.md b/docs/book/getting-started/zenml-pro/deploy-workspace-k8s.md index 64f292cbd81..0d82a6dd3fe 100644 --- a/docs/book/getting-started/zenml-pro/deploy-workspace-k8s.md +++ b/docs/book/getting-started/zenml-pro/deploy-workspace-k8s.md @@ -17,6 +17,8 @@ layout: This guide provides step-by-step instructions for deploying ZenML Pro workspaces on Kubernetes using Helm and enrolling them in the ZenML Pro control plane. +ZenML Pro workspace deployments use standard Kubernetes APIs and work on managed cloud clusters (EKS, GKE, AKS), enterprise platforms like Red Hat OpenShift and SUSE Rancher, and self-managed clusters on-premises or in your own cloud. + ## Prerequisites diff --git a/docs/book/reference/legacy-docs.md b/docs/book/reference/legacy-docs.md index f58b005ec1c..7109deb3079 100644 --- a/docs/book/reference/legacy-docs.md +++ b/docs/book/reference/legacy-docs.md @@ -5,6 +5,6 @@ icon: user-bounty-hunter # Legacy docs -
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ZenML Scarf