apiVersion: v1
kind: ConfigMap
# ...
data:
config.yaml: |
dataReporting:
obfuscation:
- workload_names
# ...- Documentation
- OpenShift Dedicated
- Support
- Remote health monitoring with connected clusters
- Using Insights Operator history bug_report picture_as_pdf
OpenShift docs are moving and will soon only be available at docs.redhat.com, the home of all Red Hat product documentation. Explore the new docs experience today.
- 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
- 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
- Revoking privileges and access to an OpenShift Dedicated cluster
- 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
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Using the Insights Operator
The Insights Operator periodically gathers configuration and component failure status and, by default, reports that data every two hours to Red Hat. This information enables Red Hat to assess configuration and deeper failure data than is reported through Telemetry. Users of OpenShift Dedicated can display the report in the Insights Advisor service on Red Hat Hybrid Cloud Console.
Additional resources
-
For more information on using Insights Advisor to identify issues with your cluster, see Using Insights to identify issues with your cluster.
Understanding Insights Operator alerts
The Insights Operator declares alerts through the Prometheus monitoring system to the Alertmanager. You can view these alerts in the Alerting UI in the OpenShift Dedicated web console by using one of the following methods:
-
In the Administrator perspective, click Observe → Alerting.
-
In the Developer perspective, click Observe → <project_name> → Alerts tab.
Currently, Insights Operator sends the following alerts when the conditions are met:
| Alert | Description |
|---|---|
|
Insights Operator is disabled. |
|
Simple content access is not enabled in Red Hat Subscription Management. |
|
Insights has an active recommendation for the cluster. |
Obfuscating Deployment Validation Operator data
Cluster administrators can configure the Insight Operator to obfuscate data from the Deployment Validation Operator (DVO), if the Operator is installed. When the workload_names value is added to the insights-config ConfigMap object, workload names—rather than UIDs—are displayed in Insights for Openshift, making them more recognizable for cluster administrators.
Prerequisites
-
Remote health reporting is enabled, which is the default.
-
You are logged in to the OpenShift Dedicated web console with the "cluster-admin" role.
-
The insights-config
ConfigMapobject exists in theopenshift-insightsnamespace. -
The cluster is self managed and the Deployment Validation Operator is installed.
Procedure
-
Go to Workloads → ConfigMaps and select Project: openshift-insights.
-
Click on the insights-config
ConfigMapobject to open it. -
Click Actions and select Edit ConfigMap.
-
Click the YAML view radio button.
-
In the file, set the
obfuscationattribute with theworkload_namesvalue. -
Click Save. The insights-config config-map details page opens.
-
Verify that the value of the
config.yamlobfuscationattribute is set to- workload_names.