Chapter 7. Setting up Data Grid services Use Data Grid Operator to create clusters of either Cache service or Data Grid service pods. 7.1. Service types Services are stateful applications, based on the Data Grid Server image, that provide flexible and robust in-memory data storage. When you create Data Grid clusters you specify either DataGrid or Cache as the service type with the spec.service.type field. DataGrid service type Deploy Data Grid clusters with full configuration and capabilities. Cache service type Deploy Data Grid clusters with minimal configuration. Red Hat recommends the DataGrid service type for clusters because it lets you: Back up data across global clusters with cross-site replication. Create caches with any valid configuration. Add file-based cache stores to save data in a persistent volume. Query values across caches using the Data Grid Query API. Use advanced Data Grid features and capabilities. Important The Cache service type was designed to provide a convenient way to create a low-latency data store with minimal configuration. Additional development on the Infinispan CRD has shown that the DataGrid CR offers a better approach to achieving this goal, ultimately giving users more choice and less deployment overhead. For this reason, the Cache service type is planned for removal in the version of the Infinispan CRD and is no longer under active development. The DataGrid service type continues to benefit from new features and improved tooling to automate complex operations such as cluster upgrades and data migration. 7.2. Creating Data Grid service pods To use custom cache definitions along with Data Grid capabilities such as cross-site replication, create clusters of Data Grid service pods. Procedure Create an Infinispan CR that sets spec.service.type: DataGrid and configures any other Data Grid service resources. apiVersion: infinispan.org/v1 kind: Infinispan metadata: name: infinispan spec: replicas: 2 version: <Data Grid_version> service: type: DataGrid Important You cannot change the spec.service.type field after you create pods. To change the service type, you must delete the existing pods and create new ones. Apply your Infinispan CR to create the cluster. 7.2.1. Data Grid service CR This topic describes the Infinispan CR for Data Grid service pods. apiVersion: infinispan.org/v1 kind: Infinispan metadata: name: infinispan annotations: infinispan.org/monitoring: 'true' spec: replicas: 6 version: 8.4.6-1 upgrades: type: Shutdown service: type: DataGrid container: storage: 2Gi # The ephemeralStorage and storageClassName fields are mutually exclusive. ephemeralStorage: false storageClassName: my-storage-class sites: local: name: azure expose: type: LoadBalancer locations: - name: azure url: openshift://api.azure.host:6443 secretName: azure-token - name: aws clusterName: infinispan namespace: rhdg-namespace url: openshift://api.aws.host:6443 secretName: aws-token security: endpointSecretName: endpoint-identities endpointEncryption: type: Secret certSecretName: tls-secret container: extraJvmOpts: "-XX:NativeMemoryTracking=summary" cpu: "2000m:1000m" memory: "2Gi:1Gi" logging: categories: org.infinispan: debug org.jgroups: debug org.jgroups.protocols.TCP: error org.jgroups.protocols.relay.RELAY2: error expose: type: LoadBalancer configMapName: "my-cluster-config" configListener: enabled: true affinity: podAntiAffinity: preferredDuringSchedulingIgnoredDuringExecution: - weight: 100 podAffinityTerm: labelSelector: matchLabels: app: infinispan-pod clusterName: infinispan infinispan_cr: infinispan topologyKey: "kubernetes.io/hostname" Field Description metadata.name Names your Data Grid cluster. metadata.annotations.infinispan.org/monitoring Automatically creates a ServiceMonitor for your cluster. spec.replicas Specifies the number of pods in your cluster. spec.version Specifies the Data Grid Server version of your cluster. spec.upgrades.type Controls how Data Grid Operator upgrades your Data Grid cluster when new versions become available. spec.service.type Configures the type Data Grid service. A value of DataGrid creates a cluster with Data Grid service pods. spec.service.container Configures the storage resources for Data Grid service pods. spec.service.sites Configures cross-site replication. spec.security.endpointSecretName Specifies an authentication secret that contains Data Grid user credentials. spec.security.endpointEncryption Specifies TLS certificates and keystores to encrypt client connections. spec.container Specifies JVM, CPU, and memory resources for Data Grid pods. spec.logging Configures Data Grid logging categories. spec.expose Controls how Data Grid endpoints are exposed on the network. spec.configMapName Specifies a ConfigMap that contains Data Grid configuration. spec.configListener.enabled Creates a listener pod in each Data Grid cluster that allows Data Grid Operator to reconcile server-side modifications with Data Grid resources such as the Cache CR. The listener pod consumes minimal resources and is enabled by default. Setting a value of false removes the listener pod and disables bi-directional reconciliation. You should do this only if you do not need declarative Kubernetes representations of Data Grid resources created through the Data Grid Console, CLI, or client applications. spec.configListener.logging.level Configures the logging level for the ConfigListener deployments. The default level is info . You can change it to debug or error . spec.affinity Configures anti-affinity strategies that guarantee Data Grid availability. 7.3. Allocating storage resources You can allocate storage for Data Grid service pods but not Cache service pods. By default, Data Grid Operator allocates 1Gi for the persistent volume claim. However you should adjust the amount of storage available to Data Grid service pods so that Data Grid can preserve cluster state during shutdown. Important If available container storage is less than the amount of available memory, data loss can occur. Procedure Allocate storage resources with the spec.service.container.storage field. Configure either the ephemeralStorage field or the storageClassName field as required. Note These fields are mutually exclusive. Add only one of them to your Infinispan CR. Apply the changes. Ephemeral storage Name of a StorageClass object Field Description spec.service.container.storage Specifies the amount of storage for Data Grid service pods. spec.service.container.ephemeralStorage Defines whether storage is ephemeral or permanent. Set the value to true to use ephemeral storage, which means all data in storage is deleted when clusters shut down or restart. The default value is false , which means storage is permanent. spec.service.container.storageClassName Specifies the name of a StorageClass object to use for the persistent volume claim (PVC). If you include this field, you must specify an existing storage class as the value. If you do not include this field, the persistent volume claim uses the storage class that has the storageclass.kubernetes.io/is-default-class annotation set to true . 7.3.1. Persistent volume claims Data Grid Operator creates a persistent volume claim (PVC) and mounts container storage at: /opt/infinispan/server/data Caches When you create caches, Data Grid permanently stores their configuration so your caches are available after cluster restarts. This applies to both Cache service and Data Grid service pods. Data Data is always volatile in clusters of Cache service pods. When you shutdown the cluster, you permanently lose the data. Use a file-based cache store, by adding the <file-store/> element to your Data Grid cache configuration, if you want Data Grid service pods to persist data during cluster shutdown. 7.4. Allocating CPU and memory Allocate CPU and memory resources to Data Grid pods with the Infinispan CR. Note Data Grid Operator requests 1Gi of memory from the OpenShift scheduler when creating Data Grid pods. CPU requests are unbounded by default. Procedure Allocate the number of CPU units with the spec.container.cpu field. Allocate the amount of memory, in bytes, with the spec.container.memory field. The cpu and memory fields have values in the format of <limit>:<requests> . For example, cpu: "2000m:1000m" limits pods to a maximum of 2000m of CPU and requests 1000m of CPU for each pod at startup. Specifying a single value sets both the limit and request. Apply your Infinispan CR. If your cluster is running, Data Grid Operator restarts the Data Grid pods so changes take effect. 7.5. Setting JVM options Pass additional JVM options to Data Grid pods at startup. Procedure Configure JVM options with the spec.container filed in your Infinispan CR. Apply your Infinispan CR. If your cluster is running, Data Grid Operator restarts the Data Grid pods so changes take effect. JVM options Field Description spec.container.extraJvmOpts Specifies additional JVM options for the Data Grid Server. spec.container.routerExtraJvmOpts Specifies additional JVM options for the Gossip router. spec.container.cliExtraJvmOpts Specifies additional JVM options for the Data Grid CLI. 7.6. Configuring pod probes Optionally configure the values of the Liveness, Readiness and Startup probes used by Data Grid pods. The Data Grid Operator automatically configures the probe values to sensible defaults. We only recommend providing your own values once you have determined that the default values do not match your requirements. Procedure Configure probe values using the spec.service.container.*Probe fields: spec: service: container: readinessProbe: failureThreshold: 1 initialDelaySeconds: 1 periodSeconds: 1 successThreshold: 1 timeoutSeconds: 1 livenessProbe: failureThreshold: 1 initialDelaySeconds: 1 periodSeconds: 1 successThreshold: 1 timeoutSeconds: 1 startupProbe: failureThreshold: 1 initialDelaySeconds: 1 periodSeconds: 1 successThreshold: 1 timeoutSeconds: 1 Important If no value is specified for a given probe value, then the Data Grid Operator default is used. Apply your Infinispan CR. If your cluster is running, Data Grid Operator restarts the Data Grid pods in order for the changes to take effect. 7.7. Configuring pod priority Create one or more priority classes to indicate the importance of a pod relative to other pods. Pods with higher priority are scheduled ahead of pods with lower priority, ensuring prioritization of pods running critical workloads, especially when resources become constrained. Prerequisites Have cluster-admin access to OpenShift. Procedure Define a PriorityClass object by specifying its name and value. high-priority.yaml apiVersion: scheduling.k8s.io/v1 kind: PriorityClass metadata: name: high-priority value: 1000000 globalDefault: false description: "Use this priority class for high priority service pods only." Create the priority class. Reference the priority class name in the pod configuration. Infinispan CR kind: Infinispan ... spec: scheduling: affinity: ... priorityClassName: "high-priority" ... You must reference an existing priority class name, otherwise the pod is rejected. Apply the changes. Additional resources Including pod priority in pod scheduling decisions 7.8. FIPS mode for your Infinispan CR The Red Hat OpenShift Container Platform can use certain Federal Information Processing Standards (FIPS) components that ensure OpenShift clusters meet the requirements of a FIPS compliance audit. If you enabled FIPS mode on your OpenShift cluster then the Data Grid Operator automatically enables FIPS mode for your Infinispan custom resource (CR). Important Client certificate authentication is not currently supported with FIPS mode. Attempts to create Infinispan CR with spec.security.endpointEncryption.clientCert set to a value other than None will fail. Additional resources Support for FIPS cryptography Red Hat OpenShift Container Platform 7.9. Adjusting log levels Change levels for different Data Grid logging categories when you need to debug issues. You can also adjust log levels to reduce the number of messages for certain categories to minimize the use of container resources. Procedure Configure Data Grid logging with the spec.logging.categories field in your Infinispan CR. Apply the changes. Retrieve logs from Data Grid pods as required. 7.9.1. Logging reference Find information about log categories and levels. Table 7.1. Log categories Root category Description Default level org.infinispan Data Grid messages info org.jgroups Cluster transport messages info Table 7.2. Log levels Log level Description trace Provides detailed information about running state of applications. This is the most verbose log level. debug Indicates the progress of individual requests or activities. info Indicates overall progress of applications, including lifecycle events. warn Indicates circumstances that can lead to error or degrade performance. error Indicates error conditions that might prevent operations or activities from being successful but do not prevent applications from running. Garbage collection (GC) messages Data Grid Operator does not log GC messages by default. You can direct GC messages to stdout with the following JVM options: extraJvmOpts: "-Xlog:gc*:stdout:time,level,tags" 7.10. Creating Cache service pods Create Data Grid clusters with Cache service pods for a volatile, low-latency data store with minimal configuration. Important Cache service pods provide volatile storage only, which means you lose all data when you modify your Infinispan CR or update the version of your Data Grid cluster. Procedure Create an Infinispan CR that sets spec.service.type: Cache and configures any other Cache service resources. apiVersion: infinispan.org/v1 kind: Infinispan metadata: name: infinispan spec: replicas: 2 version: <Data Grid_version> service: type: Cache Apply your Infinispan CR to create the cluster. 7.10.1. Cache service CR This topic describes the Infinispan CR for Cache service pods. Field Description metadata.name Names your Data Grid cluster. metadata.annotations.infinispan.org/monitoring Automatically creates a ServiceMonitor for your cluster. spec.replicas Specifies the number of pods in your cluster. If you enable autoscaling capabilities, this field specifies the initial number of pods. spec.version Specifies the Data Grid Server version of your cluster. spec.upgrades.type Controls how Data Grid Operator upgrades your Data Grid cluster when new versions become available. spec.service.type Configures the type Data Grid service. A value of Cache creates a cluster with Cache service pods. spec.service.replicationFactor Sets the number of copies for each entry across the cluster. The default for Cache service pods is two, which replicates each cache entry to avoid data loss. spec.autoscale Enables and configures automatic scaling. spec.security.endpointSecretName Specifies an authentication secret that contains Data Grid user credentials. spec.security.endpointEncryption Specifies TLS certificates and keystores to encrypt client connections. spec.container Specifies JVM, CPU, and memory resources for Data Grid pods. spec.logging Configures Data Grid logging categories. spec.expose Controls how Data Grid endpoints are exposed on the network. spec.affinity Configures anti-affinity strategies that guarantee Data Grid availability. 7.11. Automatic scaling Data Grid Operator can monitor the default cache on Cache service pods to automatically scale clusters up or down, by creating or deleting pods based on memory usage. Important Automatic scaling is available for clusters of Cache service pods only. Data Grid Operator does not perform automatic scaling for clusters of Data Grid service pods. When you enable automatic scaling, you define memory usage thresholds that let Data Grid Operator determine when it needs to create or delete pods. Data Grid Operator monitors statistics for the default cache and, when memory usage reaches the configured thresholds, scales your clusters up or down. Maximum threshold This threshold sets an upper boundary for the amount of memory that pods in your cluster can use before scaling up or performing eviction. When Data Grid Operator detects that any node reaches the maximum amount of memory that you configure, it creates a new node if possible. If Data Grid Operator cannot create a new node then it performs eviction when memory usage reaches 100 percent. Minimum threshold This threshold sets a lower boundary for memory usage across your Data Grid cluster. When Data Grid Operator detects that memory usage falls below the minimum, it shuts down pods. Default cache only Autoscaling capabilities work with the default cache only. If you plan to add other caches to your cluster, you should not include the autoscale field in your Infinispan CR. In this case you should use eviction to control the size of the data container on each node. 7.11.1. Configuring automatic scaling If you create clusters with Cache service pods, you can configure Data Grid Operator to automatically scale clusters. Procedure Add the spec.autoscale resource to your Infinispan CR to enable automatic scaling. Note Set a value of true for the autoscale.disabled field to disable automatic scaling. Configure thresholds for automatic scaling with the following fields: Field Description spec.autoscale.maxMemUsagePercent Specifies a maximum threshold, as a percentage, for memory usage on each node. spec.autoscale.maxReplicas Specifies the maximum number of Cache service pods for the cluster. spec.autoscale.minMemUsagePercent Specifies a minimum threshold, as a percentage, for cluster memory usage. spec.autoscale.minReplicas Specifies the minimum number of Cache service pods for the cluster. For example, add the following to your Infinispan CR: Apply the changes. 7.12. Adding labels and annotations to Data Grid resources Attach key/value labels and annotations to pods and services that Data Grid Operator creates and manages. Labels help you identify relationships between objects to better organize and monitor Data Grid resources. Annotations are arbitrary non-identifying metadata for client applications or deployment and management tooling. Note Red Hat subscription labels are automatically applied to Data Grid resources. Procedure Open your Infinispan CR for editing. Attach labels and annotations to Data Grid resources in the metadata.annotations section. Define values for annotations directly in the metadata.annotations section. Define values for labels with the metadata.labels field. Apply your Infinispan CR. Custom annotations apiVersion: infinispan.org/v1 kind: Infinispan metadata: annotations: infinispan.org/targetAnnotations: service-annotation1, service-annotation2 infinispan.org/podTargetAnnotations: pod-annotation1, pod-annotation2 infinispan.org/routerAnnotations: router-annotation1, router-annotation2 service-annotation1: value service-annotation2: value pod-annotation1: value pod-annotation2: value router-annotation1: value router-annotation2: value Custom labels apiVersion: infinispan.org/v1 kind: Infinispan metadata: annotations: infinispan.org/targetLabels: service-label1, service-label2 infinispan.org/podTargetLabels: pod-label1, pod-label2 labels: service-label1: value service-label2: value pod-label1: value pod-label2: value # The operator does not attach these labels to resources. my-label: my-value environment: development 7.13. Adding labels and annotations with environment variables Set environment variables for Data Grid Operator to add labels and annotations that automatically propagate to all Data Grid pods and services. Procedure Add labels and annotations to your Data Grid Operator subscription with the spec.config.env field in one of the following ways: Use the oc edit subscription command. Use the Red Hat OpenShift Console. Navigate to Operators > Installed Operators > Data Grid Operator . From the Actions menu, select Edit Subscription . Labels and annotations with environment variables spec: config: env: - name: INFINISPAN_OPERATOR_TARGET_LABELS value: | {"service-label1":"value", service-label1":"value"} - name: INFINISPAN_OPERATOR_POD_TARGET_LABELS value: | {"pod-label1":"value", "pod-label2":"value"} - name: INFINISPAN_OPERATOR_TARGET_ANNOTATIONS value: | {"service-annotation1":"value", "service-annotation2":"value"} - name: INFINISPAN_OPERATOR_POD_TARGET_ANNOTATIONS value: | {"pod-annotation1":"value", "pod-annotation2":"value"} 7.14. Defining environment variables in the Data Grid Operator subscription You can define environment variables in your Data Grid Operator subscription either when you create or edit the subscription. Note If you are using the Red Hat OpenShift Console, you must first install the Data Grid Operator and then edit the existing subscription. spec.config.env field Includes the name and value fields to define environment variables. ADDITIONAL_VARS variable Includes the names of environment variables in a format of JSON array. Environment variables within the value of the ADDITIONAL_VARS variable automatically propagate to each Data Grid Server pod managed by the associated Operator. Prerequisites Ensure the Operator Lifecycle Manager (OLM) is installed. Have an oc client. Procedure Create a subscription definition YAML for your Data Grid Operator: Use the spec.config.env field to define environment variables. Within the ADDITIONAL_VARS variable, include environment variable names in a JSON array. subscription-datagrid.yaml For example, use the environment variables to set the local time zone: subscription-datagrid.yaml Create a subscription for Data Grid Operator: Verification Retrieve the environment variables from the subscription-datagrid.yaml : steps Use the oc edit subscription command to modify the environment variable: To ensure the changes take effect on your Data Grid clusters, you must recreate the existing clusters. Terminate the pods by deleting the StatefulSet associated with the existing Infinispan CRs. In the Red Hat OpenShift Console, navigate to Operators > Installed Operators > Data Grid Operator . From the Actions menu, select Edit Subscription .

Commands:
apiVersion: infinispan.org/v1 kind: Infinispan metadata: name: infinispan spec: replicas: 2 version: <Data Grid_version> service: type: DataGrid
apiVersion: infinispan.org/v1 kind: Infinispan metadata: name: infinispan annotations: infinispan.org/monitoring: 'true' spec: replicas: 6 version: 8.4.6-1 upgrades: type: Shutdown service: type: DataGrid container: storage: 2Gi # The ephemeralStorage and storageClassName fields are mutually exclusive. ephemeralStorage: false storageClassName: my-storage-class sites: local: name: azure expose: type: LoadBalancer locations: - name: azure url: openshift://api.azure.host:6443 secretName: azure-token - name: aws clusterName: infinispan namespace: rhdg-namespace url: openshift://api.aws.host:6443 secretName: aws-token security: endpointSecretName: endpoint-identities endpointEncryption: type: Secret certSecretName: tls-secret container: extraJvmOpts: "-XX:NativeMemoryTracking=summary" cpu: "2000m:1000m" memory: "2Gi:1Gi" logging: categories: org.infinispan: debug org.jgroups: debug org.jgroups.protocols.TCP: error org.jgroups.protocols.relay.RELAY2: error expose: type: LoadBalancer configMapName: "my-cluster-config" configListener: enabled: true affinity: podAntiAffinity: preferredDuringSchedulingIgnoredDuringExecution: - weight: 100 podAffinityTerm: labelSelector: matchLabels: app: infinispan-pod clusterName: infinispan infinispan_cr: infinispan topologyKey: "kubernetes.io/hostname"
spec: service: type: DataGrid container: storage: 2Gi ephemeralStorage: true
spec: service: type: DataGrid container: storage: 2Gi storageClassName: my-storage-class
spec: container: cpu: "2000m:1000m" memory: "2Gi:1Gi"
spec: container: extraJvmOpts: "-<option>=<value>" routerExtraJvmOpts: "-<option>=<value>" cliExtraJvmOpts: "-<option>=<value>"
spec: service: container: readinessProbe: failureThreshold: 1 initialDelaySeconds: 1 periodSeconds: 1 successThreshold: 1 timeoutSeconds: 1 livenessProbe: failureThreshold: 1 initialDelaySeconds: 1 periodSeconds: 1 successThreshold: 1 timeoutSeconds: 1 startupProbe: failureThreshold: 1 initialDelaySeconds: 1 periodSeconds: 1 successThreshold: 1 timeoutSeconds: 1
apiVersion: scheduling.k8s.io/v1 kind: PriorityClass metadata: name: high-priority value: 1000000 globalDefault: false description: "Use this priority class for high priority service pods only."
create -f high-priority.yaml
kind: Infinispan spec: scheduling: affinity: priorityClassName: "high-priority"
spec: logging: categories: org.infinispan: debug org.jgroups: debug
logs -f USDPOD_NAME
extraJvmOpts: "-Xlog:gc*:stdout:time,level,tags"
apiVersion: infinispan.org/v1 kind: Infinispan metadata: name: infinispan spec: replicas: 2 version: <Data Grid_version> service: type: Cache
apiVersion: infinispan.org/v1 kind: Infinispan metadata: name: infinispan annotations: infinispan.org/monitoring: 'true' spec: replicas: 2 version: 8.4.6-1 upgrades: type: Shutdown service: type: Cache replicationFactor: 2 autoscale: maxMemUsagePercent: 70 maxReplicas: 5 minMemUsagePercent: 30 minReplicas: 2 security: endpointSecretName: endpoint-identities endpointEncryption: type: Secret certSecretName: tls-secret container: extraJvmOpts: "-XX:NativeMemoryTracking=summary" cpu: "2000m:1000m" memory: "2Gi:1Gi" logging: categories: org.infinispan: trace org.jgroups: trace expose: type: LoadBalancer affinity: podAntiAffinity: preferredDuringSchedulingIgnoredDuringExecution: - weight: 100 podAffinityTerm: labelSelector: matchLabels: app: infinispan-pod clusterName: infinispan infinispan_cr: infinispan topologyKey: "kubernetes.io/hostname"
spec: service: type: Cache autoscale: disabled: false maxMemUsagePercent: 70 maxReplicas: 5 minMemUsagePercent: 30 minReplicas: 2
apiVersion: infinispan.org/v1 kind: Infinispan metadata: annotations: infinispan.org/targetAnnotations: service-annotation1, service-annotation2 infinispan.org/podTargetAnnotations: pod-annotation1, pod-annotation2 infinispan.org/routerAnnotations: router-annotation1, router-annotation2 service-annotation1: value service-annotation2: value pod-annotation1: value pod-annotation2: value router-annotation1: value router-annotation2: value
apiVersion: infinispan.org/v1 kind: Infinispan metadata: annotations: infinispan.org/targetLabels: service-label1, service-label2 infinispan.org/podTargetLabels: pod-label1, pod-label2 labels: service-label1: value service-label2: value pod-label1: value pod-label2: value # The operator does not attach these labels to resources. my-label: my-value environment: development
edit subscription datagrid -n openshift-operators
spec: config: env: - name: INFINISPAN_OPERATOR_TARGET_LABELS value: | {"service-label1":"value", service-label1":"value"} - name: INFINISPAN_OPERATOR_POD_TARGET_LABELS value: | {"pod-label1":"value", "pod-label2":"value"} - name: INFINISPAN_OPERATOR_TARGET_ANNOTATIONS value: | {"service-annotation1":"value", "service-annotation2":"value"} - name: INFINISPAN_OPERATOR_POD_TARGET_ANNOTATIONS value: | {"pod-annotation1":"value", "pod-annotation2":"value"}
apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: datagrid namespace: openshift-operators spec: channel: 8.4.x installPlanApproval: Automatic name: datagrid source: redhat-operators sourceNamespace: openshift-marketplace config: env: - name: ADDITIONAL_VARS value: "[\"VAR_NAME\", \"ANOTHER_VAR\"]" - name: VAR_NAME value: USD(VAR_NAME_VALUE) - name: ANOTHER_VAR value: USD(ANOTHER_VAR_VALUE)
kind: Subscription spec: config: env: - name: ADDITIONAL_VARS value: "[\"TZ\"]" - name: TZ value: "JST-9"
apply -f subscription-datagrid.yaml
get subscription datagrid -n openshift-operators -o jsonpath='{.spec.config.env[*].name}'
edit subscription datagrid -n openshift-operators