[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-09-04。"],[[["\u003cp\u003eThis document defines various terms related to the Google Distributed Cloud (GDC) air-gapped appliance, providing a glossary of key concepts.\u003c/p\u003e\n"],["\u003cp\u003eGDC air-gapped is a Google Cloud product that runs on certified hardware, delivering managed software and services outside of traditional data centers.\u003c/p\u003e\n"],["\u003cp\u003eThe admin cluster manages shared services and user clusters, while user clusters are made up of virtual machines and support Kubernetes-based workloads.\u003c/p\u003e\n"],["\u003cp\u003eConfigs, constraint templates, and custom resources are fundamental components of managing and enforcing policies within GDC, enabling consistent and compliant operations.\u003c/p\u003e\n"],["\u003cp\u003eConcepts such as data plane, control plane, and management plane are described in the context of GDC architecture, detailing how data, workloads, and resources are managed.\u003c/p\u003e\n"]]],[],null,["# Google Distributed Cloud air-gapped appliance glossary\n\nThis page provides definitions for Google Distributed Cloud (GDC) air-gapped appliance terms.\n\nA\n---\n\nAPI endpoint\n: A service config aspect that specifies the network address, also known as a service endpoint. For example, `aiplatform.googleapis.com`.\n\nArtifact registry\n: A single place for your organization to manage system container images, operating system (OS) images for bootstrapping bare metal hosts, Debian packages and kernels for in-place OS upgrade, OS images for KubeVirt virtual machines that form a Kubernetes cluster, and bundles to support GDC services.\n\nC\n---\n\ncell config\n: Set of YAML-formatted Kubernetes resource definitions that specify the initial GDC configuration.\n\ncluster\n: A set of nodes that run containerized applications. In Kubernetes, a cluster\n is a grouping of multiple nodes that runs containerized applications.\n In GDC, a single cluster encompasses all\n three of its bare metal nodes. A dedicated Management API server, which runs\n as pod workloads on the cluster, hosts management plane APIs. User workloads,\n which include both VMs and Kubernetes pods, can run on this cluster.\n\nClusterSelector\n: A `ClusterSelector` custom resource is a special type of config that uses Kubernetes label selectors. You can use a `ClusterSelector` custom resource to limit which clusters a particular config applies to, based on the cluster's labels. You can also use a `ClusterSelector` custom resource to limit which clusters instantiate a namespace-scoped object.\n\nconfig\n: A config is a Kubernetes configuration declaration written in YAML or JSON. To read and apply a config to a cluster to create or configure a Kubernetes object or resource in that cluster, GDC uses Config Sync. Config Sync is an open source tool that lets Application Operators and Platform Administrators deploy consistent configurations and policies. A config contains configuration details you apply to a Kubernetes cluster using `kubectl edit` or `kubectl apply`. You must store configs in a repository.\n\nconfig sync\n: A config sync lets Application Operators and Platform Administrators deploy consistent configurations and policies. You deploy these configurations and policies to individual Kubernetes clusters, and multiple namespaces within clusters.\n\nconstraint\n: A constraint is a set of rules and parameters that govern interaction with a Kubernetes cluster. By defining one or more constraints, Policy Controller lets you enforce a policy for a Kubernetes cluster. After a constraint is installed, requests to the API server are checked against the constraint and are rejected if they do not comply.\n\nconstraint template\n: A constraint template defines the schema and logic of the constraint. You source constraint templates from Google and third parties or write your own.\n\nconstraint template library\n: The constraint template library is a collection of prebuilt policies included with Policy Controller for common security and compliance controls.\n\ncontrol plane\n: A cluster's controlling unit, consisting of a set of components that schedule and manage workloads, communicate with clusters, and ensure that clusters are functioning. Control planes include the etcd key-value datastore, the Kubernetes API server, the scheduler, and the controller manager.\n\ncustom resource\n: A custom resource is an instance of a kind defined by a custom resource definition.\n\nD\n---\n\ndeployment model for a workload\n: A plan to deploy one or multiple instances of the workload, and how GDC distributes those instances.\n\ndata plane\n: In networking, the data plane is where the action takes place. It includes forwarding tables, routing tables, Address Resolution Protocol (ARP) tables, queues, tagging, and re-tagging. The data plane carries out the commands of the control plane. In the data plane, the routers and switches use what the control plane built to dispose of incoming and outgoing frames and packets. Some get sent to another router, for example. Some might get queued up when congested. Some might get dropped if congestion gets poor.\n\nG\n---\n\nGoogle Distributed Cloud (GDC) air-gapped appliance\n: A human-portable device that has Google Distributed Cloud air-gapped deployed on\n it, for use outside of data centers, such as in the field or in other remote\n sites.\n\nGoogle Distributed Cloud air-gapped\n: A Google Cloud product that delivers a managed software platform running on certified hardware to deliver Google Cloud services and other services.\n\nGKE\n: Google Kubernetes Engine (GKE) provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. The GKE environment consists of multiple machines grouped together to form a cluster.\n\nI\n---\n\ninfrastructure cluster\n: A bare metal Kubernetes cluster that runs the control plane and data plane components of the device. It also hosts the Management API server where all non-container workloads and services are deployed. For GDC, the infrastructure cluster runs all container workloads.\n\nK\n---\n\nKubernetes-based workload\n: A user workload that deploys Kubernetes `Pod` objects. The Application Operator creates pods that run on the Kubernetes cluster.\n\nKubernetes namespace\n: A Kubernetes namespace helps different projects, teams, or customers share a Kubernetes cluster.\n\nL\n---\n\nlong-running operation\n: A long-running operation is a running program that takes a long time to complete.\n\nM\n---\n\nmanagement API server\n: An API server running on the infrastructure cluster. All non-container workloads and services are deployed to the management API server.\n\nmanagement plane\n: A service or API surface used to manage resources which host your data or workload. It represents service components that control the lifecycle of a resource such as create, read, update, and delete.\n\nN\n---\n\nnode\n: A machine in a Kubernetes cluster. In the context of GDC, a node is either a bare metal machine or a virtual machine. A node might run on VM-based workloads directly, or a node might be part of a cluster that runs Kubernetes-based workloads.\n\nnode pool\n: A node pool is a group of nodes within a cluster that all have the same configuration.\n\nO\n---\n\norganization\n: A root resource for all resources a single customer owns. GDC\n has one organization per device. An organization might contain multiple projects.\n\nP\n---\n\nproject\n: A logical grouping of related resources into a single access boundary. Multiple projects within an organization share the underlying compute, storage, and network resources. A project might contain workloads with multiple virtual machines or Kubernetes resources. One project aligns to one Kubernetes namespace.\n\nS\n---\n\nservice\n: A Kubernetes object that logically groups a set of pods and defines a policy by which to access them.\n\nsingle-tenancy\n: A single instance of the software and supporting infrastructure that serves a single customer.\n\nSecurity information and event management (SIEM, SEM, and SIM)\n: The real-time analysis of security alerts generated by network hardware and applications. Vendors sell SIEM as software, as appliances, or as managed services. These products are also used to log security data and generate reports for compliance purposes. This segment of security management deals with real-time monitoring, correlation of events, notifications, and console views.\n\nSKU\n: A Stock Keeping Unit (SKU). In GDC air-gapped appliance, a SKU represents\n a purchasable service, such as Object storage and Block storage. Each SKU is\n billable to you.\n\nStatefulSet\n: A Kubernetes object meant for stateful applications. Pods managed by a `StatefulSet` object get a unique, permanent identity in their cluster.\n\nU\n---\n\nuser workloads\n: Any custom code that the Application Operator deploys to GDC. This can include VM-based workloads or container-based workloads.\n\nV\n---\n\nVM-based workload\n: A user workload that deploys to virtual machines (VM). The Application Operator creates VMs that run directly on the management API server."]]
