- Documentation
- OpenShift Dedicated
- Support
- Support overview history bug_report picture_as_pdf
- About
- What's new
- Introduction to OpenShift Dedicated
- Architecture
- Red Hat OpenShift Cluster Manager
- Planning your environment
- Getting started
- Installing, accessing, and deleting OpenShift Dedicated clusters
- Creating a cluster on AWS
- Creating a GCP Private Service Connect enabled private cluster
- Creating a cluster on GCP with Workload Identity Federation
- Creating a cluster on GCP
- Configuring your identity providers
- Revoking privileges and access to an OpenShift Dedicated cluster
- Deleting an OpenShift Dedicated cluster
- Support
- Web console
- CLI tools
- Cluster administration
- Security and compliance
- Authentication and authorization
- Authentication and authorization overview
- Understanding authentication
- Managing user-owned OAuth access tokens
- Configuring identity providers
- Managing administration roles and users
- 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
- 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
- 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
- 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
- Placing pods on specific nodes using node selectors
- Controlling pod placement using pod topology spread constraints
- Using jobs and daemon sets
- 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
- Observability
- Observability overview
- 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
- 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
Support overview
Red Hat offers cluster administrators tools for gathering data for your cluster, monitoring, and troubleshooting.
Get support
Get support: Visit the Red Hat Customer Portal to review knowledge base articles, submit a support case, and review additional product documentation and resources.
Remote health monitoring issues
Remote health monitoring issues: OpenShift Dedicated collects telemetry and configuration data about your cluster and reports it to Red Hat by using the Telemeter Client and the Insights Operator. Red Hat uses this data to understand and resolve issues in connected cluster. OpenShift Dedicated collects data and monitors health using the following:
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Telemetry: The Telemetry Client gathers and uploads the metrics values to Red Hat every four minutes and thirty seconds. Red Hat uses this data to:
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Monitor the clusters.
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Roll out OpenShift Dedicated upgrades.
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Improve the upgrade experience.
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Insight Operator: By default, OpenShift Dedicated installs and enables the Insight Operator, which reports configuration and component failure status every two hours. The Insight Operator helps to:
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Identify potential cluster issues proactively.
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Provide a solution and preventive action in Red Hat OpenShift Cluster Manager.
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You can review telemetry information.
If you have enabled remote health reporting, Use Insights to identify issues. You can optionally disable remote health reporting.
Troubleshooting issues
A cluster administrator can monitor and troubleshoot the following OpenShift Dedicated component issues:
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Node issues: A cluster administrator can verify and troubleshoot node-related issues by reviewing the status, resource usage, and configuration of a node. You can query the following:
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Kubelet’s status on a node.
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Cluster node journal logs.
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Operator issues: A cluster administrator can do the following to resolve Operator issues:
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Verify Operator subscription status.
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Check Operator pod health.
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Gather Operator logs.
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Pod issues: A cluster administrator can troubleshoot pod-related issues by reviewing the status of a pod and completing the following:
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Review pod and container logs.
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Start debug pods with root access.
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Storage issues: A multi-attach storage error occurs when the mounting volume on a new node is not possible because the failed node cannot unmount the attached volume. A cluster administrator can do the following to resolve multi-attach storage issues:
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Enable multiple attachments by using RWX volumes.
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Recover or delete the failed node when using an RWO volume.
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Monitoring issues: A cluster administrator can follow the procedures on the troubleshooting page for monitoring. If the metrics for your user-defined projects are unavailable or if Prometheus is consuming a lot of disk space, check the following:
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Investigate why user-defined metrics are unavailable.
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Determine why Prometheus is consuming a lot of disk space.
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OpenShift CLI (
oc) issues: Investigate OpenShift CLI (oc) issues by increasing the log level.