$ rosa list machinepools --cluster=<cluster_name>- Documentation
- Red Hat OpenShift Service on AWS
- Cluster administration
- Manage nodes using machine pools
- About autoscaling nodes on a cluster history bug_report picture_as_pdf
- About
- What's new
- Introduction to ROSA
- Architecture
- Tutorials
- Tutorials overview
- ROSA with HCP activation and account linking
- Verifying Permissions for a ROSA STS Deployment
- Configuring log forwarding for CloudWatch logs and STS
- Using AWS WAF and Amazon CloudFront to protect ROSA workloads
- Using AWS WAF and AWS ALBs to protect ROSA workloads
- Deploying OpenShift API for Data Protection on a ROSA cluster
- AWS Load Balancer Operator on ROSA
- Configuring ROSA/OSD to use custom TLS ciphers on the ingress controllers
- Configuring Microsoft Entra ID (formerly Azure Active Directory) as an identity provider
- Using AWS Secrets Manager CSI on ROSA with STS
- Using AWS Controllers for Kubernetes on ROSA
- Deploying the External DNS Operator on ROSA
- Dynamically issuing certificates using the cert-manager Operator on ROSA
- Assigning consistent egress IP for external traffic
- Getting started with ROSA
- Deploying an application
- Getting started
- Prepare your environment
- Install ROSA with HCP clusters
- Install ROSA Classic clusters
- Creating a ROSA cluster with STS using the default options
- Creating a ROSA cluster with STS using customizations
- Creating a ROSA cluster with STS using Terraform
- Interactive cluster creation mode reference
- Creating an AWS PrivateLink cluster on ROSA
- Configuring a shared virtual private cloud for ROSA clusters
- Accessing a ROSA cluster
- Configuring identity providers using Red Hat OpenShift Cluster Manager
- Revoking access to a ROSA cluster
- Deleting a ROSA cluster
- Deploying ROSA without AWS STS
- AWS prerequisites for ROSA
- Understanding the ROSA deployment workflow
- Required AWS service quotas
- Configuring your AWS account
- Installing the ROSA CLI
- Creating a ROSA cluster without AWS STS
- Configuring a private cluster
- Deleting access to a ROSA cluster
- Deleting a ROSA cluster
- Command quick reference for creating clusters and users
- Support
- Support overview
- Managing your cluster resources
- Getting support
- Remote health monitoring with connected clusters
- Summarizing cluster specifications
- Troubleshooting
- Troubleshooting ROSA installations
- Troubleshooting networking
- Verifying node health
- Troubleshooting Operator issues
- Investigating pod issues
- Troubleshooting storage issues
- Investigating monitoring issues
- Diagnosing OpenShift CLI (oc) issues
- Troubleshooting expired offline access tokens
- Troubleshooting IAM roles
- Troubleshooting cluster deployments
- Red Hat OpenShift Service on AWS managed resources
- Web console
- CLI tools
- Red Hat OpenShift Cluster Manager
- Cluster administration
- Security and compliance
- Authentication and authorization
- Authentication and authorization overview
- Understanding authentication
- Managing user-owned OAuth access tokens
- Configuring identity providers
- Using RBAC to define and apply permissions
- Understanding and creating service accounts
- Using service accounts in applications
- Using a service account as an OAuth client
- Assuming an AWS IAM role for a service account
- Scoping tokens
- Using bound service account tokens
- Managing security context constraints
- Understanding and managing pod security admission
- Syncing LDAP groups
- Upgrading
- CI/CD
- Images
- Overview of images
- Overview of the Cluster Samples Operator
- Using the Cluster Samples Operator with an alternate registry
- Creating images
- Managing images
- Managing image streams
- Using image streams with Kubernetes resources
- Triggering updates on image stream changes
- Image configuration resources
- Using templates
- Using Ruby on Rails
- Using images
- Add-on services
- Storage
- Registry
- Operators
- Operators overview
- Understanding Operators
- User tasks
- Administrator tasks
- Developing Operators
- About the Operator SDK
- Installing the Operator SDK CLI
- Go-based Operators
- Ansible-based Operators
- Helm-based Operators
- Defining cluster service versions (CSVs)
- Working with bundle images
- Complying with pod security admission
- Validating Operators using the scorecard
- Validating Operator bundles
- High-availability or single-node cluster detection and support
- Configuring built-in monitoring with Prometheus
- Configuring leader election
- Object pruning utility
- Migrating package manifest projects to bundle format
- Operator SDK CLI reference
- Migrating to Operator SDK v0.1.0
- Networking
- Building applications
- Building applications overview
- Projects
- Creating applications
- Viewing application composition using the Topology view
- Connecting applications to services
- Service Binding Operator release notes
- Understanding Service Binding Operator
- Installing Service Binding Operator
- Getting started with service binding
- Exposing binding data from a service
- Projecting binding data
- Binding workloads using Service Binding Operator
- Connecting an application to a service using the Developer perspective
- Working with Helm charts
- Deployments
- Quotas
- Using config maps with applications
- Monitoring project and application metrics using the Developer perspective
- Monitoring application health
- Editing applications
- Working with quotas
- Pruning objects to reclaim resources
- Idling applications
- Deleting applications
- Using the Red Hat Marketplace
- Backing up and restoring applications
- Nodes
- Overview of nodes
- Working with pods
- Automatically scaling pods with the Custom Metrics Autoscaler Operator
- Release notes
- Custom Metrics Autoscaler Operator overview
- Installing the custom metrics autoscaler
- Understanding the custom metrics autoscaler triggers
- Understanding the custom metrics autoscaler trigger authentications
- Pausing the custom metrics autoscaler
- Gathering audit logs
- Gathering debugging data
- Viewing Operator metrics
- Understanding how to add custom metrics autoscalers
- Removing the Custom Metrics Autoscaler Operator
- Controlling pod placement onto nodes (scheduling)
- About pod placement using the scheduler
- Placing pods relative to other pods using pod affinity and anti-affinity rules
- Controlling pod placement on nodes using node affinity rules
- Placing pods onto overcommited nodes
- Controlling pod placement using node taints
- Placing pods on specific nodes using node selectors
- Controlling pod placement using pod topology spread constraints
- Using Jobs and DaemonSets
- Working with nodes
- Working with containers
- Understanding containers
- Using Init Containers to perform tasks before a pod is deployed
- Using volumes to persist container data
- Mapping volumes using projected volumes
- Allowing containers to consume API objects
- Copying files to or from a container
- Executing remote commands in a container
- Using port forwarding to access applications in a container
- Working with clusters
- Logging
- Release notes
- Support
- Troubleshooting logging
- About Logging
- Installing Logging
- Updating Logging
- Visualizing logs
- Accessing the service logs
- Viewing cluster logs in the AWS Console
- Configuring your Logging deployment
- Log collection and forwarding
- Log storage
- Logging alerts
- Performance and reliability tuning
- Scheduling resources
- Uninstalling Logging
- Exported fields
- API reference
- Glossary
- Observability
- Monitoring
- Monitoring overview
- Accessing monitoring for user-defined projects
- Configuring the monitoring stack
- Disabling monitoring for user-defined projects
- Enabling alert routing for user-defined projects
- Managing metrics
- Managing alerts
- Reviewing monitoring dashboards
- Accessing third-party monitoring APIs
- Troubleshooting monitoring issues
- Config map reference for the Cluster Monitoring Operator
- Monitoring
- Service Mesh
- Service Mesh 2.x
- About OpenShift Service Mesh
- Service Mesh 2.x release notes
- Service Mesh architecture
- Service Mesh deployment models
- Service Mesh and Istio differences
- Preparing to install Service Mesh
- Installing the Operators
- Creating the ServiceMeshControlPlane
- Adding workloads to a service mesh
- Enabling sidecar injection
- Upgrading Service Mesh
- Managing users and profiles
- Security
- Traffic management
- Metrics, logs, and traces
- Performance and scalability
- Deploying to production
- Federation
- Extensions
- 3scale WebAssembly for 2.1
- 3scale Istio adapter for 2.0
- Troubleshooting Service Mesh
- Control plane configuration reference
- Kiali configuration reference
- Jaeger configuration reference
- Uninstalling Service Mesh
- Service Mesh 2.x
- Serverless
- Virtualization
- About
- Getting started
- Installing
- Post-installation configuration
- Updating
- Virtual machines
- Creating VMs from Red Hat images
- Creating VMs from custom images
- Connecting to VM consoles
- Configuring SSH access to VMs
- Editing virtual machines
- Editing boot order
- Deleting virtual machines
- Exporting virtual machines
- Managing virtual machine instances
- Controlling virtual machine states
- Using virtual Trusted Platform Module devices
- Managing virtual machines with OpenShift Pipelines
- Advanced virtual machine management
- Working with resource quotas for virtual machines
- Specifying nodes for virtual machines
- Configuring certificate rotation
- Configuring the default CPU model
- UEFI mode for virtual machines
- Configuring PXE booting for virtual machines
- Scheduling virtual machines
- About high availability for virtual machines
- Control plane tuning
- VM disks
- Networking
- Networking configuration overview
- Connecting a VM to the default pod network
- Exposing a VM by using a service
- Connecting a VM to an OVN-Kubernetes secondary network
- Connecting a VM to a service mesh
- Configuring a dedicated network for live migration
- Configuring and viewing IP addresses
- Managing MAC address pools for network interfaces
- Storage
- Storage configuration overview
- Configuring storage profiles
- Managing automatic boot source updates
- Reserving PVC space for file system overhead
- Configuring local storage by using HPP
- Enabling user permissions to clone data volumes across namespaces
- Configuring CDI to override CPU and memory quotas
- Preparing CDI scratch space
- Using preallocation for data volumes
- Managing data volume annotations
- Live migration
- Nodes
- Monitoring
- Support
- Backup and restore
×
About autoscaling nodes on a cluster
The autoscaler option can be configured to automatically scale the number of machines in a cluster.
The cluster autoscaler increases the size of the cluster when there are pods that failed to schedule on any of the current nodes due to insufficient resources or when another node is necessary to meet deployment needs. The cluster autoscaler does not increase the cluster resources beyond the limits that you specify.
Additionally, the cluster autoscaler decreases the size of the cluster when some nodes are consistently not needed for a significant period, such as when it has low resource use and all of its important pods can fit on other nodes.
When you enable autoscaling, you must also set a minimum and maximum number of worker nodes.
|
Only cluster owners and organization admins can scale or delete a cluster. |
Enabling autoscaling nodes on a cluster
You can enable autoscaling on worker nodes to increase or decrease the number of nodes available by editing the machine pool definition for an existing cluster.
Enabling autoscaling nodes in an existing cluster using Red Hat OpenShift Cluster Manager
Enable autoscaling for worker nodes in the machine pool definition from OpenShift Cluster Manager console.
Procedure
-
From OpenShift Cluster Manager, navigate to the Clusters page and select the cluster that you want to enable autoscaling for.
-
On the selected cluster, select the Machine pools tab.
-
Click the Options menu
at the end of the machine pool that you want to enable autoscaling for and select Scale. -
On the Edit node count dialog, select the Enable autoscaling checkbox.
-
Select Apply to save these changes and enable autoscaling for the cluster.
|
Additionally, you can configure autoscaling on the default machine pool when you create the cluster using interactive mode. |
Enabling autoscaling nodes in an existing cluster using the ROSA CLI
Configure autoscaling to dynamically scale the number of worker nodes up or down based on load.
Successful autoscaling is dependent on having the correct AWS resource quotas in your AWS account. Verify resource quotas and request quota increases from the AWS console.
Procedure
-
To identify the machine pool IDs in a cluster, enter the following command:
Example outputID AUTOSCALING REPLICAS INSTANCE TYPE LABELS TAINTS AVAILABILITY ZONES DISK SIZE SG IDs default No 2 m5.xlarge us-east-1a 300GiB sg-0e375ff0ec4a6cfa2 mp1 No 2 m5.xlarge us-east-1a 300GiB sg-0e375ff0ec4a6cfa2 -
Get the ID of the machine pools that you want to configure.
-
To enable autoscaling on a machine pool, enter the following command:
$ rosa edit machinepool --cluster=<cluster_name> <machinepool_ID> --enable-autoscaling --min-replicas=<number> --max-replicas=<number>ExampleEnable autoscaling on a machine pool with the ID
mp1on a cluster namedmycluster, with the number of replicas set to scale between 2 and 5 worker nodes:$ rosa edit machinepool --cluster=mycluster mp1 --enable-autoscaling --min-replicas=2 --max-replicas=5
Disabling autoscaling nodes on a cluster
You can disable autoscaling on worker nodes to increase or decrease the number of nodes available by editing the machine pool definition for an existing cluster.
You can disable autoscaling on a cluster using OpenShift Cluster Manager console or the Red Hat OpenShift Service on AWS CLI.
|
Additionally, you can configure autoscaling on the default machine pool when you create the cluster using interactive mode. |
Disabling autoscaling nodes in an existing cluster using Red Hat OpenShift Cluster Manager
Disable autoscaling for worker nodes in the machine pool definition from OpenShift Cluster Manager console.
Procedure
-
From OpenShift Cluster Manager, navigate to the Clusters page and select the cluster with autoscaling that must be disabled.
-
On the selected cluster, select the Machine pools tab.
-
Click the Options menu
at the end of the machine pool with autoscaling and select Scale. -
On the "Edit node count" dialog, deselect the Enable autoscaling checkbox.
-
Select Apply to save these changes and disable autoscaling from the cluster.
Disabling autoscaling nodes in an existing cluster using the ROSA CLI
Disable autoscaling for worker nodes in the machine pool definition using the Red Hat OpenShift Service on AWS (ROSA) CLI, rosa.
Procedure
-
Enter the following command:
$ rosa edit machinepool --cluster=<cluster_name> <machinepool_ID> --enable-autoscaling=false --replicas=<number>ExampleDisable autoscaling on the
defaultmachine pool on a cluster namedmycluster:$ rosa edit machinepool --cluster=mycluster default --enable-autoscaling=false --replicas=3