You can use machine management to flexibly work with underlying infrastructure like Amazon Web Services (AWS), Azure, Google Cloud Platform (GCP), OpenStack, Red Hat Virtualization (RHV), and vSphere to manage the OKD cluster. You can control the cluster and perform auto-scaling, such as scaling up and down the cluster based on specific workload policies.
The OKD cluster can horizontally scale up and down when the load increases or decreases. It is important to have a cluster that adapts to changing workloads.
Machine management is implemented as a Custom Resource Definition(CRD).
A CRD object defines a new unique object
Kind in the cluster and enables the Kubernetes API server to handle the object’s entire lifecycle.
The Machine API Operator provisions the following resources:
Machine Health Checks
The Machine API is a combination of primary resources that are based on the upstream Cluster API project and custom OKD resources.
For OKD 4.10 clusters, the Machine API performs all node host provisioning management actions after the cluster installation finishes. Because of this system, OKD 4.10 offers an elastic, dynamic provisioning method on top of public or private cloud infrastructure.
The two primary resources are:
A fundamental unit that describes the host for a node. A machine has a
providerSpec specification, which describes the types of compute nodes that are offered for different cloud platforms. For example, a machine type for a worker node on Amazon Web Services (AWS) might define a specific machine type and required metadata.
MachineSet resources are groups of machines. Machine sets are to machines as replica sets are to pods. If you need more machines or must scale them down, you change the replicas field on the machine set to meet your compute need.
Control plane machines cannot be managed by machine sets.
The following custom resources add more capabilities to your cluster:
MachineAutoscaler resource automatically scales compute machines in a cloud. You can set the minimum and maximum scaling boundaries for nodes in a specified compute machine set, and the machine autoscaler maintains that range of nodes.
MachineAutoscaler object takes effect after a
ClusterAutoscaler object exists. Both
MachineAutoscaler resources are made available by the
This resource is based on the upstream cluster autoscaler project. In the OKD implementation, it is integrated with the Machine API by extending the machine set API. You can set cluster-wide scaling limits for resources such as cores, nodes, memory, GPU, and so on. You can set the priority so that the cluster prioritizes pods so that new nodes are not brought online for less important pods. You can also set the scaling policy so that you can scale up nodes but not scale them down.
MachineHealthCheck resource detects when a machine is unhealthy, deletes it, and, on supported platforms, makes a new machine.
In OKD version 3.11, you could not roll out a multi-zone architecture easily because the cluster did not manage machine provisioning. Beginning with OKD version 4.1, this process is easier. Each machine set is scoped to a single zone, so the installation program sends out machine sets across availability zones on your behalf. And then because your compute is dynamic, and in the face of a zone failure, you always have a zone for when you must rebalance your machines. In global Azure regions that do not have multiple availability zones, you can use availability sets to ensure high availability. The autoscaler provides best-effort balancing over the life of a cluster.
As a cluster administrator you can:
Create a machine set on:
Create a machine set for a bare metal deployment: Creating a compute machine set on bare metal
Manually scale a machine set by adding or removing a machine from the machine set.
Modify a machine set through the
MachineSet YAML configuration file.
Delete a machine.
Configure and deploy a machine health check to automatically fix damaged machines in a machine pool.
You can automatically scale your OKD cluster to ensure flexibility for changing workloads. To autoscale your cluster, you must first deploy a cluster autoscaler, and then deploy a machine autoscaler for each compute machine set.
The cluster autoscaler increases and decreases the size of the cluster based on deployment needs.
The machine autoscaler adjusts the number of machines in the compute machine sets that you deploy in your OKD cluster.
User-provisioned infrastructure is an environment where you can deploy infrastructure such as compute, network, and storage resources that host the OKD. You can add compute machines to a cluster on user-provisioned infrastructure during or after the installation process.
As a cluster administrator, you can perform the following actions:
Add Red Hat Enterprise Linux (RHEL) compute machines, also known as worker machines, to a user-provisioned infrastructure cluster or an installation-provisioned infrastructure cluster.
Add more Red Hat Enterprise Linux (RHEL) compute machines to an existing cluster.