From 4726f5b64d657a13d02d3cb20bf60a1858c530bf Mon Sep 17 00:00:00 2001 From: Karl Cardenas Date: Tue, 14 May 2024 07:53:49 -0700 Subject: [PATCH] docs: DOC-1166 image update (#2773) * docs: DOC-1166 image update * Optimised images with calibre/image-actions * Optimised images with calibre/image-actions * Optimised images with calibre/image-actions * Optimised images with calibre/image-actions * docs: language touch-up * Update docs/docs-content/architecture/orchestration-spectrocloud.md * Apply suggestions from code review Co-authored-by: caroldelwing * chore: updated language --------- Co-authored-by: vault-token-factory-spectrocloud[bot] <133815545+vault-token-factory-spectrocloud[bot]@users.noreply.github.com> Co-authored-by: caroldelwing --- .../orchestration-spectrocloud.md | 86 ++++++++++-------- ...estartion-spectrocloud_provision-flow.webp | Bin 28884 -> 56442 bytes 2 files changed, 49 insertions(+), 37 deletions(-) diff --git a/docs/docs-content/architecture/orchestration-spectrocloud.md b/docs/docs-content/architecture/orchestration-spectrocloud.md index f9da2e1e45..232dcab244 100644 --- a/docs/docs-content/architecture/orchestration-spectrocloud.md +++ b/docs/docs-content/architecture/orchestration-spectrocloud.md @@ -1,47 +1,57 @@ --- sidebar_label: "Order of Operations" title: "Order of Operations" -description: "The methods of workload cluster provisioning for K8S clusters with Palette" +description: + "Learn about the order of operations that make up the workload cluster provisioning process in Palette and how Cluster + API is used." icon: "" hide_table_of_contents: false sidebar_position: 10 --- -Spectro Cloud Palette provisions standard, upstream Kubernetes clusters using -[Cluster API](https://cluster-api.sigs.k8s.io/). +Palette provisions standard upstream Kubernetes clusters using [Cluster API](https://cluster-api.sigs.k8s.io/). Cluster +API is a Kubernetes sub-project focused on providing declarative APIs and tooling to simplify provisioning, upgrading, +and operating multiple Kubernetes clusters. -Cluster API is a Kubernetes sub-project focused on providing declarative APIs and tooling to simplify provisioning, -upgrading, and operating multiple Kubernetes clusters. +:::info + +Check out the [Cluster API concepts](https://cluster-api.sigs.k8s.io/user/concepts) page for a detailed explanation of +the components and concepts used in the Cluster API. Cluster API is a Kubernetes sub-project and different from the +[Kubernetes API](https://kubernetes.io/docs/concepts/overview/kubernetes-api/) that you use to interact with your +Kubernetes clusters. -Cluster API demonstratively manages the lifecycle of a cluster (creation, scaling, enhancement, and deletion) and helps -in automating the process of cluster lifecycle management for platform operations. Cluster API also helps in consistent -and repeated cluster deployment across multiple infrastructure environments. +::: -
+Cluster API automates cluster lifecycle management for platform operations. It ensures a consistent experience in +cluster deployment across different infrastructure environments. ## Workload Cluster Provisioning +The following diagram illustrates the order of operations that make up the workload cluster provisioning process. + ![workload_cluster_provisioning.webp](/architecture_orchestartion-spectrocloud_provision-flow.webp) -1. New K8S cluster request from user submitted to the cluster management system. +1. A user submits a request to Palette for a new Kubernetes cluster. The request may come from the UI, API, or + Infrastructure as Code (IaC) tools such as Terraform or Crossplane. -2. Palette creates the Cluster-API (CAPI) custom-resource specifications for the target cloud, e.g in VMware this would - translate to: Cluster, vSphereCluster, KubeadmControlPlane (with replica 1), and VSphereMachineTemplate. These - resources are created in the management cluster. +2. Palette creates Cluster-API (CAPI) custom-resource specifications for the target cloud, such as AWS, GCP, etc. For + example, in VMware, this would translate to the following resources getting created: Cluster, vSphereCluster, + KubeadmControlPlane, and VSphereMachineTemplate. These resources are created in the Palette internal management + plane. -3. Cluster API and corresponding cluster-api provider, e.g: cluster-api-provider-vsphere, provisions the first - control-plane node CP-A on the target cloud. +3. Cluster API and the respective cluster-api provider, specific to the target platform, such as + cluster-api-provider-vsphere, provisions the first control-plane node (CP-A) on the target cloud. -4. When CP-A is operational, the management platform will install a Palette agent into the workload cluster and then - perform a pivot of the Cluster API resources. +4. When CP-A is operational, the Palette management platform will install a Palette agent into the workload cluster and + then perform a pivot of Cluster API resources. This means that Cluster API resources and their responsibilities are + now handled by the workload cluster, not the Palette management plane. -5. CP-A agent will retrieve the latest specifications for the cluster, e.g: 3 control-plane, and 3 workers. CP-A will - generate and update the remaining CAPI resources, e.g: update replicas to 3 for KubeadmControlPlane, create the - worker's MachineDeployment or VSphereMachineTemplate. Cluster API running in CP-A will provision the remaining - control plane and worker nodes. +5. CP-A agent will retrieve the required specifications for the cluster, such as the number of nodes. CP-A will generate + and update the remaining CAPI resources, e.g: update replicas to 3 for KubeadmControlPlane and create the worker's + MachineDeployment or VSphereMachineTemplate. The Cluster API active in CP-A will provision the remaining control + plane and worker nodes. -6. The Palette agent will install all the additional add-ons as specified by the cluster's cluster profile (e.g: - logging, monitoring, security). +6. The Palette agent will install all the additional add-ons as the cluster profile specifies. :::info @@ -52,26 +62,28 @@ clusters. ## Why Palette Pivots? -Palette's decentralized model is based on a "decentralized management - local policy enforcement" scalable architecture. +Palette's decentralized model is based on a "decentralized management" design with local policy enforcement that allows +for a scalable architecture. ![distributed_orchestration.webp](/architecture_orchestartion-spectrocloud_distributed-flow.webp) -As part of the workload K8s cluster provisioning, only the first control-plane node is launched by Cluster API, running -in the Palette management cluster. Once the control-plane node is operational, Cluster API resources are _pivoted_ from -the management platform into the target workload cluster. +As part of the workload for the Kubernetes cluster provisioning, only the first control-plane node is launched by the +Cluster API active in the Palette management cluster. Once the control plane node is operational, Cluster API resources +are _pivoted_ from the Palette management platform into the target workload cluster. -The target workload cluster is then responsible for provisioning and maintaining the remaining control-plane and worker -nodes. All Day-2 operations which result in node changes, including OS/K8s upgrades, scaling, and K8s certificate -rotation, are triggered by changes to the Cluster API resources in the target workload cluster. +The target workload cluster is responsible for provisioning and maintaining the remaining control plane and worker +nodes. All Day-2 operations, which may result in node changes, including the operating system and Kubernetes upgrades, +node scaling, and Kubernetes SSL certificate rotation, are triggered by changes to Cluster API resources in the target +workload cluster. -Palette pivots these clusters for several reasons, related to scalability and availability: +Palette pivots Cluster API resources from the Palette management platform to the workload clusters for reasons such as: -- **Scalability** - The management platform scales to meet the demand of all your workload clusters as the number of - tenant clusters and nodes increases in size. +- **Scalability** - The central management platform, Palette, can scale to meet the demand of all your workload clusters + as the number of workload clusters and nodes increase in size. The workload cluster manages its own lifecycle and + resources through guidance from the Palette management platform. -- **Resiliency** - Even if the management platform were to experience an outage, the workload clusters would retain - their resiliency capabilities, auto-recovery, launching of new nodes on failures, auto-scaling, and other policies - still work! +- **Resiliency** - If the management platform were to experience an outage, the workload clusters would retain their + capabilities, such as auto-recovery, launching of new nodes on failures, auto-scaling, and other features. -- **Intermittent network resiliency** - The design supports use cases where the workload clusters can still operate in +- **Network resiliency** - The decentralized design supports use cases where the workload clusters can still operate in intermittent and disconnected network availability situations. diff --git a/static/assets/docs/images/architecture_orchestartion-spectrocloud_provision-flow.webp 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