-
For example, OKD 4.11, 4.13.
-
For example, OKD 4.10, 4.12.
The control plane, which is composed of control plane machines, manages the OKD cluster. The control plane machines manage workloads on the compute machines, which are also known as worker machines. The cluster itself manages all upgrades to the machines by the actions of the Cluster Version Operator (CVO), the Machine Config Operator, and a set of individual Operators.
Machines that run control plane components or user workloads are divided into groups based on the types of resources they handle. These groups of machines are called machine config pools (MCP). Each MCP manages a set of nodes and its corresponding machine configs. The role of the node determines which MCP it belongs to; the MCP governs nodes based on its assigned node role label. Nodes in an MCP have the same configuration; this means nodes can be scaled up and torn down in response to increased or decreased workloads.
By default, there are two MCPs created by the cluster when it is installed: master
and worker
. Each default MCP has a defined configuration applied by the Machine Config Operator (MCO), which is responsible for managing MCPs and facilitating MCP updates.
For worker nodes, you can create additional MCPs, or custom pools, to manage nodes with custom use cases that extend outside of the default node types. Custom MCPs for the control plane nodes are not supported.
Custom pools are pools that inherit their configurations from the worker pool. They use any machine config targeted for the worker pool, but add the ability to deploy changes only targeted at the custom pool. Since a custom pool inherits its configuration from the worker pool, any change to the worker pool is applied to the custom pool as well. Custom pools that do not inherit their configurations from the worker pool are not supported by the MCO.
A node can only be included in one MCP. If a node has multiple labels that correspond to several MCPs, like |
It is recommended to have a custom pool for every node role you want to manage in your cluster. For example, if you create infra nodes to handle infra workloads, it is recommended to create a custom infra MCP to group those nodes together. If you apply an infra
role label to a worker node so it has the worker,infra
dual label, but do not have a custom infra MCP, the MCO considers it a worker node. If you remove the worker
label from a node and apply the infra
label without grouping it in a custom pool, the node is not recognized by the MCO and is unmanaged by the cluster.
Any node labeled with the |
The MCO applies updates for pools independently; for example, if there is an update that affects all pools, nodes from each pool update in parallel with each other. If you add a custom pool, nodes from that pool also attempt to update concurrently with the master and worker nodes.
There might be situations where the configuration on a node does not fully match what the currently-applied machine config specifies. This state is called configuration drift. The Machine Config Daemon (MCD) regularly checks the nodes for configuration drift. If the MCD detects configuration drift, the MCO marks the node degraded
until an administrator corrects the node configuration. A degraded node is online and operational, but, it cannot be updated.
OKD assigns hosts different roles. These roles define the function of the machine within the cluster. The cluster contains definitions for the standard master
and worker
role types.
The cluster also contains the definition for the |
The OKD version must match between control plane host and node host. For example, in a 4.17 cluster, all control plane hosts must be 4.17 and all nodes must be 4.17.
Temporary mismatches during cluster upgrades are acceptable. For example, when upgrading from the previous OKD version to 4.17, some nodes will upgrade to 4.17 before others. Prolonged skewing of control plane hosts and node hosts might expose older compute machines to bugs and missing features. Users should resolve skewed control plane hosts and node hosts as soon as possible.
The kubelet
service must not be newer than kube-apiserver
, and can be up to two minor versions older depending on whether your OKD version is odd or even. The table below shows the appropriate version compatibility:
OKD version | Supported kubelet skew |
---|---|
Odd OKD minor versions [1] |
Up to one version older |
Even OKD minor versions [2] |
Up to two versions older |
For example, OKD 4.11, 4.13.
For example, OKD 4.10, 4.12.
In a Kubernetes cluster, worker nodes run and manage the actual workloads requested by Kubernetes users. The worker nodes advertise their capacity and the scheduler, which is a control plane service, determines on which nodes to start pods and containers. The following important services run on each worker node:
CRI-O, which is the container engine.
kubelet, which is the service that accepts and fulfills requests for running and stopping container workloads.
A service proxy, which manages communication for pods across workers.
The runC or crun low-level container runtime, which creates and runs containers.
For information about how to enable crun instead of the default runC, see the documentation for creating a |
In OKD, compute machine sets control the compute machines, which are assigned the worker
machine role. Machines with the worker
role drive compute workloads that are governed by a specific machine pool that autoscales them. Because OKD has the capacity to support multiple machine types, the machines with the worker
role are classed as compute machines. In this release, the terms worker machine and compute machine are used interchangeably because the only default type of compute machine is the worker machine. In future versions of OKD, different types of compute machines, such as infrastructure machines, might be used by default.
Compute machine sets are groupings of compute machine resources under the |
In a Kubernetes cluster, the master nodes run services that are required to control the Kubernetes cluster. In OKD, the control plane is comprised of control plane machines that have a master
machine role. They contain more than just the Kubernetes services for managing the OKD cluster.
For most OKD clusters, control plane machines are defined by a series of standalone machine API resources. For supported cloud provider and OKD version combinations, control planes can be managed with control plane machine sets. Extra controls apply to control plane machines to prevent you from deleting all of the control plane machines and breaking your cluster.
Exactly three control plane nodes must be used for all production deployments. However, on bare metal platforms, clusters can be scaled up to five control plane nodes. |
Services that fall under the Kubernetes category on the control plane include the Kubernetes API server, etcd, the Kubernetes controller manager, and the Kubernetes scheduler.
Component | Description |
---|---|
Kubernetes API server |
The Kubernetes API server validates and configures the data for pods, services, and replication controllers. It also provides a focal point for the shared state of the cluster. |
etcd |
etcd stores the persistent control plane state while other components watch etcd for changes to bring themselves into the specified state. |
Kubernetes controller manager |
The Kubernetes controller manager watches etcd for changes to objects such as replication, namespace, and service account controller objects, and then uses the API to enforce the specified state. Several such processes create a cluster with one active leader at a time. |
Kubernetes scheduler |
The Kubernetes scheduler watches for newly created pods without an assigned node and selects the best node to host the pod. |
There are also OpenShift services that run on the control plane, which include the OpenShift API server, OpenShift controller manager, OpenShift OAuth API server, and OpenShift OAuth server.
Component | Description |
---|---|
OpenShift API server |
The OpenShift API server validates and configures the data for OpenShift resources, such as projects, routes, and templates. The OpenShift API server is managed by the OpenShift API Server Operator. |
OpenShift controller manager |
The OpenShift controller manager watches etcd for changes to OpenShift objects, such as project, route, and template controller objects, and then uses the API to enforce the specified state. The OpenShift controller manager is managed by the OpenShift Controller Manager Operator. |
OpenShift OAuth API server |
The OpenShift OAuth API server validates and configures the data to authenticate to OKD, such as users, groups, and OAuth tokens. The OpenShift OAuth API server is managed by the Cluster Authentication Operator. |
OpenShift OAuth server |
Users request tokens from the OpenShift OAuth server to authenticate themselves to the API. The OpenShift OAuth server is managed by the Cluster Authentication Operator. |
Some of these services on the control plane machines run as systemd services, while others run as static pods.
Systemd services are appropriate for services that you need to always come up on that particular system shortly after it starts. For control plane machines, those include sshd, which allows remote login. It also includes services such as:
The CRI-O container engine (crio), which runs and manages the containers. OKD 4.17 uses CRI-O instead of the Docker Container Engine.
Kubelet (kubelet), which accepts requests for managing containers on the machine from control plane services.
CRI-O and Kubelet must run directly on the host as systemd services because they need to be running before you can run other containers.
The installer-*
and revision-pruner-*
control plane pods must run with root permissions because they write to the /etc/kubernetes
directory, which is owned by the root user. These pods are in the following namespaces:
openshift-etcd
openshift-kube-apiserver
openshift-kube-controller-manager
openshift-kube-scheduler
Operators are among the most important components of OKD. Operators are the preferred method of packaging, deploying, and managing services on the control plane. They can also provide advantages to applications that users run.
Operators integrate with Kubernetes APIs and CLI tools such as kubectl
and oc
commands. They provide the means of monitoring applications, performing health checks, managing over-the-air (OTA) updates, and ensuring that applications remain in your specified state.
Operators also offer a more granular configuration experience. You configure each component by modifying the API that the Operator exposes instead of modifying a global configuration file.
Because CRI-O and the Kubelet run on every node, almost every other cluster function can be managed on the control plane by using Operators. Components that are added to the control plane by using Operators include critical networking and credential services.
While both follow similar Operator concepts and goals, Operators in OKD are managed by two different systems, depending on their purpose:
Cluster Operators, which are managed by the Cluster Version Operator (CVO), are installed by default to perform cluster functions.
Optional add-on Operators, which are managed by Operator Lifecycle Manager (OLM), can be made accessible for users to run in their applications.
In OKD, all cluster functions are divided into a series of default cluster Operators. Cluster Operators manage a particular area of cluster functionality, such as cluster-wide application logging, management of the Kubernetes control plane, or the machine provisioning system.
Cluster Operators are represented by a ClusterOperator
object, which
cluster administrators
can view in the OKD web console from the Administration → Cluster Settings page. Each cluster Operator provides a simple API for determining cluster functionality. The Operator hides the details of managing the lifecycle of that component. Operators can manage a single component or tens of components, but the end goal is always to reduce operational burden by automating common actions.
Operator Lifecycle Manager (OLM) and OperatorHub are default components in OKD that help manage Kubernetes-native applications as Operators. Together they provide the system for discovering, installing, and managing the optional add-on Operators available on the cluster.
Using OperatorHub in the OKD web console, cluster administrators and authorized users can select Operators to install from catalogs of Operators. After installing an Operator from OperatorHub, it can be made available globally or in specific namespaces to run in user applications.
Default catalog sources are available that include Red Hat Operators, certified Operators, and community Operators. Cluster administrators can also add their own custom catalog sources, which can contain a custom set of Operators.
Developers can use the Operator SDK to help author custom Operators that take advantage of OLM features, as well. Their Operator can then be bundled and added to a custom catalog source, which can be added to a cluster and made available to users.
OLM does not manage the cluster Operators that comprise the OKD architecture. |
For more details on running add-on Operators in OKD, see the Operators guide sections on Operator Lifecycle Manager (OLM) and OperatorHub.
For more details on the Operator SDK, see Developing Operators.
OKD 4.17 integrates both operating system and cluster management. Because the cluster manages its own updates, including updates to Red Hat Enterprise Linux CoreOS (RHCOS) on cluster nodes, OKD provides an opinionated lifecycle management experience that simplifies the orchestration of node upgrades.
OKD employs three daemon sets and controllers to simplify node management. These daemon sets orchestrate operating system updates and configuration changes to the hosts by using standard Kubernetes-style constructs. They include:
The machine-config-controller
, which coordinates machine upgrades from the control
plane. It monitors all of the cluster nodes and orchestrates their configuration
updates.
The machine-config-daemon
daemon set, which runs on
each node in the cluster and updates a machine to configuration as defined by
machine config and as instructed by the MachineConfigController. When the node detects
a change, it drains off its pods, applies the update, and reboots. These changes
come in the form of Ignition configuration files that apply the specified
machine configuration and control kubelet configuration. The update itself is
delivered in a container. This process is key to the success of managing
OKD and FCOS updates together.
The machine-config-server
daemon set, which provides the Ignition config files
to control plane nodes as they join the cluster.
The machine configuration is a subset of the Ignition configuration. The
machine-config-daemon
reads the machine configuration to see if it needs to do
an OSTree update or if it must apply a series of systemd kubelet file changes,
configuration changes, or other changes to the operating system or OKD
configuration.
When you perform node management operations, you create or modify a
KubeletConfig
custom resource (CR).
When changes are made to a machine configuration, the Machine Config Operator (MCO) automatically reboots all corresponding nodes in order for the changes to take effect. You can mitigate the disruption caused by some machine config changes by using a node disruption policy. See Understanding node restart behaviors after machine config changes. Alternatively, you can prevent the nodes from automatically rebooting after machine configuration changes before making the changes. Pause the autoreboot process by setting the The following modifications do not trigger a node reboot:
|
There might be situations where the configuration on a node does not fully match what the currently-applied machine config specifies. This state is called configuration drift. The Machine Config Daemon (MCD) regularly checks the nodes for configuration drift. If the MCD detects configuration drift, the MCO marks the node degraded
until an administrator corrects the node configuration. A degraded node is online and operational, but, it cannot be updated.
For more information about detecting configuration drift, see Understanding configuration drift detection.
For information about preventing the control plane machines from rebooting after the Machine Config Operator makes changes to the machine configuration, see Disabling Machine Config Operator from automatically rebooting.
Understanding node restart behaviors after machine config changes
etcd is a consistent, distributed key-value store that holds small amounts of data that can fit entirely in memory. Although etcd is a core component of many projects, it is the primary data store for Kubernetes, which is the standard system for container orchestration.
By using etcd, you can benefit in several ways:
Maintain consistent uptime for your cloud-native applications, and keep them working even if individual servers fail
Store and replicate all cluster states for Kubernetes
Distribute configuration data to provide redundancy and resiliency for the configuration of nodes
To ensure a reliable approach to cluster configuration and management, etcd uses the etcd Operator. The Operator simplifies the use of etcd on a Kubernetes container platform like OKD. With the etcd Operator, you can create or delete etcd members, resize clusters, perform backups, and upgrade etcd.
The etcd Operator observes, analyzes, and acts:
It observes the cluster state by using the Kubernetes API.
It analyzes differences between the current state and the state that you want.
It fixes the differences through the etcd cluster management APIs, the Kubernetes API, or both.
etcd holds the cluster state, which is constantly updated. This state is continuously persisted, which leads to a high number of small changes at high frequency. As a result, it is critical to back the etcd cluster member with fast, low-latency I/O. For more information about best practices for etcd, see "Recommended etcd practices".