mtpti5iD/redhat-docs_dataset huggingface dataset:
5.66. fence-virt 5.66.1. RHBA-2012:0800 - fence-virt bug fix update Updated fence-virt packages that fix four bugs are now available for Red Hat Enterprise Linux 6. The fence-virt packages provide a fencing agent for virtual machines as well as a host agent which processes fencing requests. Bug Fixes BZ# 753974 Prior to this update, the libvirt-qpid plug-in did not handle exceptions correctly. As a consequence, the fence_virtd daemon could unexpectedly terminate with a segmentation fault if the connection to the specified qpid daemon failed. This update modifies the exception handling. Now, the fencing operation works as expected. BZ# 758392 Prior to this update, the hashing utility sha_verify did not handle errors correctly when a key file could not be read. As a consequence, the fence_virtd daemon could unexpectedly terminate with a segmentation fault when receiving a fencing request if fence_virtd failed to read the specified key file during startup. This update modifies the error handling if a key file cannot be read. Now, fence_virtd no longer terminates under these conditions. BZ# 761215 Prior to this update, the XML example for serial mode in the fence_virt.conf(5) man page contained an incorrect closing tag. This update corrects this tag. BZ# 806949 Prior to this update, the libvirt-qpid plug-in was linked directly against the qpid libraries instead of only the qmfv2 library. As a consequence, newer versions of the qpid libraries could not be used with the libvirt-qpid plug-in. This update no longer links against the qpid libraries directly. Now, also newer qpid libraries can be used with libvirt-qpid. BZ# 809101 Prior to this update, the fence_virtd.conf manpage and the fence_virtd.conf generator incorrectly stated that by default, fence_virtd listened on all network interfaces. Both have been amended to state that by default, fence_virtd listens on the default network interface. All users of fence-virt are advised to upgrade to these updated packages, which fix these bugs.

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Chapter 1. Overview Red Hat OpenShift AI is an artificial intelligence (AI) platform that provides tools to rapidly train, serve, and monitor machine learning (ML) models onsite, in the public cloud, or at the edge. OpenShift AI provides a powerful AI/ML platform for building AI-enabled applications. Data scientists and MLOps engineers can collaborate to move from experiment to production in a consistent environment quickly. You can deploy OpenShift AI on any supported version of OpenShift, whether on-premise, in the cloud, or in disconnected environments. For details on supported versions, see Red Hat OpenShift AI: Supported Configurations . 1.1. Data science workflow For the purpose of getting you started with OpenShift AI, Figure 1 illustrates a simplified data science workflow. The real world process of developing ML models is an iterative one. The simplified data science workflow for predictive AI use cases includes the following tasks: Defining your business problem and setting goals to solve it. Gathering, cleaning, and preparing data. Data often has to be federated from a range of sources, and exploring and understanding data plays a key role in the success of a data science project. Evaluating and selecting ML models for your business use case. Train models for your business use case by tuning model parameters based on your set of training data. In practice, data scientists train a range of models, and compare performance while considering tradeoffs such as time and memory constraints. Integrate models into an application, including deployment and testing. After model training, the step of the workflow is production. Data scientists are often responsible for putting the model in production and making it accessible so that a developer can integrate the model into an application. Monitor and manage deployed models. Depending on the organization, data scientists, data engineers, or ML engineers must monitor the performance of models in production, tracking prediction and performance metrics. Refine and retrain models. Data scientists can evaluate model performance results and refine models to improve outcome by excluding or including features, changing the training data, and modifying other configuration parameters. 1.2. About this guide This guide assumes you are familiar with data science and ML Ops concepts. It describes the following tasks to get you started with using OpenShift AI: Log in to the OpenShift AI dashboard Create a data science project If you have data stored in Object Storage, configure a connection to more easily access it Create a workbench and choose an IDE, such as JupyterLab or code-server, for your data scientist development work Learn where to get information about the steps: Developing and training a model Automating the workflow with pipelines Implementing distributed workloads Testing your model Deploying your model Monitoring and managing your model See also OpenShift AI tutorial: Fraud detection example . It provides step-by-step guidance for using OpenShift AI to develop and train an example model in JupyterLab, deploy the model, and refine the model by using automated pipelines.

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Chapter 27. Desktop Stylus of Dell Canvas 27 fixed Previously, Dell Canvas 27 contained a Wacom tablet in which the ranges were offset by default. As a consequence, the stylus mapped to the upper left quarter of the screen. Red Hat Enterprise Linux 7.5 supports the stylus of the Dell Canvas 27, making sure coordinates are accurately reported. As a result, the cursor is placed directly under the tip of the stylus as required. (BZ#1507821) llvmpipe crashes on IBM Power Systems On the little-endian variant of IBM Power Systems architecture, a race-condition in GNOME Shell code previously caused that, the LLVM engine for Mesa, llvm-private , terminated unexpectedly. This update disables threading in the JavaScript engine which prevents the segmentation fault from occurring. As a result, llvm-private no longer crashes on IBM Power Systems. (BZ#1523121)

Commands:
Registry OpenShift Dedicated 4 OpenShift Dedicated can build images from your source code, deploy them, and manage their lifecycle. Red Hat OpenShift Documentation Team

Commands:
podman login registry.redhat.io Username:<your_registry_account_username> Password:<your_registry_account_password>
podman pull registry.redhat.io/<repository_name>
oc get pods -n openshift-image-registry
NAME READY STATUS RESTARTS AGE image-registry-79fb4469f6-llrln 1/1 Running 0 77m node-ca-hjksc 1/1 Running 0 73m node-ca-tftj6 1/1 Running 0 77m node-ca-wb6ht 1/1 Running 0 77m node-ca-zvt9q 1/1 Running 0 74m
oc logs deployments/image-registry -n openshift-image-registry
2015-05-01T19:48:36.300593110Z time="2015-05-01T19:48:36Z" level=info msg="version=v2.0.0+unknown" 2015-05-01T19:48:36.303294724Z time="2015-05-01T19:48:36Z" level=info msg="redis not configured" instance.id=9ed6c43d-23ee-453f-9a4b-031fea646002 2015-05-01T19:48:36.303422845Z time="2015-05-01T19:48:36Z" level=info msg="using inmemory layerinfo cache" instance.id=9ed6c43d-23ee-453f-9a4b-031fea646002 2015-05-01T19:48:36.303433991Z time="2015-05-01T19:48:36Z" level=info msg="Using OpenShift Auth handler" 2015-05-01T19:48:36.303439084Z time="2015-05-01T19:48:36Z" level=info msg="listening on :5000" instance.id=9ed6c43d-23ee-453f-9a4b-031fea646002
4.3.6. Changing the Parameters of a Volume Group The vgchange command is used to deactivate and activate volume groups, as described in Section 4.3.7, "Activating and Deactivating Volume Groups" . You can also use this command to change several volume group parameters for an existing volume group. The following command changes the maximum number of logical volumes of volume group vg00 to 128. For a description of the volume group parameters you can change with the vgchange command, see the vgchange (8) man page.

Commands:
vgchange -l 128 /dev/vg00
Chapter 18. Upgrading Red Hat Ansible Automation Platform Operator on OpenShift Container Platform The Ansible Automation Platform Operator simplifies the installation, upgrade and deployment of new Red Hat Ansible Automation Platform instances in your OpenShift Container Platform environment. 18.1. Upgrade considerations Red Hat Ansible Automation Platform version 2.0 was the first release of the Ansible Automation Platform Operator. If you are upgrading from version 2.0, continue to the Upgrading the Ansible Automation Platform Operator procedure. If you are using a version of OpenShift Container Platform that is not supported by the version of Red Hat Ansible Automation Platform to which you are upgrading, you must upgrade your OpenShift Container Platform cluster to a supported version before upgrading. Refer to the Red Hat Ansible Automation Platform Life Cycle to determine the OpenShift Container Platform version needed. For information about upgrading your cluster, refer to Updating clusters . 18.2. Prerequisites To upgrade to a newer version of Ansible Automation Platform Operator, it is recommended that you do the following: Create AutomationControllerBackup and AutomationHubBackup objects. For help with this see Creating Red Hat Ansible Automation Platform backup resources Review the release notes for the new Ansible Automation Platform version to which you are upgrading and any intermediate versions. 18.3. Upgrading the Ansible Automation Platform Operator To upgrade to the latest version of Ansible Automation Platform Operator on OpenShift Container Platform, do the following: Prodedure Log in to OpenShift Container Platform. Navigate to Operators Installed Operators . Select the Subscriptions tab. Under Upgrade status , click Upgrade Available . Click Preview InstallPlan . Click Approve .

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Chapter 2. Creating a repository A repository provides a central location for storing a related set of container images. There are two ways to create a repository in Red Hat Quay: via a push (from docker or podman ) and via the Red Hat Quay UI. These are essentially the same, whether you are using Quay.io or your own instance of Red Hat Quay. 2.1. Creating an image repository via the UI To create a repository in the Red Hat Quay UI under a user account: . Log in to the user account through the web UI. . Click the + icon in the top right of the header on the home page (or other page related to the user) and choose New Repository, as shown in the following figure: + On the Create New Repository page that appears Add the new repository name to your user name Click Repository Description and type a description of the repository In Repository Visibility, select whether you want the repository to be public or private Click the Create Repository button. The new repository is created, starting out empty. A docker pull command you could use to pull an image from this repository (minus the image name) appears on the screen. To create a repository in the Red Hat Quay UI under an organization: Log in as a user that has Admin or Write permission to the organization. From the Repositories view, select the organization name from the right column under Users and Organizations. The page for the organization appears, similar to the page shown in Figure 2.x: Click +Create New Repository in the upper-right part of the page. On the Create New Repository page that appears: Add the new repository name to the organization name Click Repository Description and type a description of the repository In Repository Visibility, select whether you want the repository to be public or private Click the Create Repository button. The new repository is created, starting out empty. A docker pull command you could use to pull an image from this repository (minus the image name) appears on the screen. 2.2. Creating an image repository via docker or podman Assuming you have the proper credentials, pushing an image to a repository that does not yet exist in your Red Hat Quay instance will create that repository as it pushes the image to that repository. Either the docker or podman commands will work for these examples. Tag the image: With an image available from docker or podman on your local system, tag that image with the new repository name and image name. Here are examples for pushing images to Quay.io or your own Red Hat Quay setup (for example, reg.example.com). For the examples, replace namespace with your Red Hat Quay user name or organization and repo_name with the name of the repository you want to create: Push to the appropriate registry. For example: Note To create an application repository, follow the same procedure you did for creating a container image repository.

Commands:
sudo podman tag myubi-minimal quay.io/namespace/repo_name sudo podman tag myubi-standard reg.example.com/namespace/repo_name
sudo podman push quay.io/namespace/repo_name sudo podman push reg.example.com/namespace/repo_name
32.2. User and Group Management Tools Managing users and groups can be a tedious task; this is why Red Hat Enterprise Linux provides tools and conventions to make them easier to manage. The easiest way to manage users and groups is through the graphical application, User Manager ( system-config-users ). For more information on User Manager , refer to Section 32.1, "User and Group Configuration" . The following command line tools can also be used to manage users and groups: useradd , usermod , and userdel - Industry-standard methods of adding, deleting and modifying user accounts groupadd , groupmod , and groupdel - Industry-standard methods of adding, deleting, and modifying user groups gpasswd - Industry-standard method of administering the /etc/group file pwck , grpck - Tools used for the verification of the password, group, and associated shadow files pwconv , pwunconv - Tools used for the conversion of passwords to shadow passwords and back to standard passwords 32.2.1. Command Line Configuration If you prefer command line tools or do not have the X Window System installed, use this section to configure users and groups.

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36.2. Rescue Mode on Power Systems servers You can use the installation disks in rescue mode, in case your system does not boot. Rescue mode gives you access to the disk partitions on your system so you can make any changes necessary to rescue your installation. After the Language Selection screen ( Section 15.2, "Language Selection" ), the installation program attempts to mount the disk partitions on your system. It then presents you with a shell prompt where you can make the changes you need. These changes may include storing the kernel and command line into the IPL source, as described in the Installation Complete section ( Section 16.21, "Installation Complete" ). When your changes are complete, you can exit the shell using exit 0 . This causes a reboot from the C side. To reboot from the A or B side or from *NWSSTG, you should vary off the system instead of exiting the shell. 36.2.1. Special Considerations for Accessing the SCSI Utilities from Rescue Mode If your system uses Native DASD disks, you may need access to the SCSI utilities from rescue mode. These utilities are located on the driver disc CD. The driver disc CD cannot be mounted from rescue mode unless special steps are taken. These steps are described below. If you have a second CD-ROM drive assigned to your Linux system, you can mount the driver disc CD in the second drive. If you have only one CD-ROM drive, you must set up an NFS boot, using the following steps: Boot from the CD-ROM with the linux rescue askmethod command. This allows you to manually select NFS as the source of your rescue media instead of defaulting to the CD-ROM drive. Copy the first installation disc onto a file system of another Linux system. Make this copy of the installation disc available through NFS or FTP. Vary off or power down the system you need to rescue. Set its IPL parameters as instructed for booting the Installation discs in rescue mode, except that the IPL source should point to the copy of boot.img on your IFS (from step 1, above). Make sure the installation disc is not in your DVD drive. IPL the Linux system. Follow the prompts as described in Section 36.2, "Rescue Mode on Power Systems servers" . An additional prompt for the installation source appears. Select NFS or FTP (as appropriate) and complete the following network configuration screen. When the Linux system has booted into rescue mode, the CD-ROM drive is available for use and you can mount the driver media to access the SCSI utilities.

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Chapter 43. ContainerTemplate schema reference Used in: CruiseControlTemplate , EntityOperatorTemplate , JmxTransTemplate , KafkaBridgeTemplate , KafkaClusterTemplate , KafkaConnectTemplate , KafkaExporterTemplate , KafkaMirrorMakerTemplate , KafkaNodePoolTemplate , ZookeeperClusterTemplate Full list of ContainerTemplate schema properties You can set custom security context and environment variables for a container. The environment variables are defined under the env property as a list of objects with name and value fields. The following example shows two custom environment variables and a custom security context set for the Kafka broker containers: # ... template: kafkaContainer: env: - name: EXAMPLE_ENV_1 value: example.env.one - name: EXAMPLE_ENV_2 value: example.env.two securityContext: runAsUser: 2000 # ... Environment variables prefixed with KAFKA_ are internal to Streams for Apache Kafka and should be avoided. If you set a custom environment variable that is already in use by Streams for Apache Kafka, it is ignored and a warning is recorded in the log. 43.1. ContainerTemplate schema properties Property Property type Description env ContainerEnvVar array Environment variables which should be applied to the container. securityContext SecurityContext Security context for the container. volumeMounts VolumeMount array Additional volume mounts which should be applied to the container.

Commands:
template: kafkaContainer: env: - name: EXAMPLE_ENV_1 value: example.env.one - name: EXAMPLE_ENV_2 value: example.env.two securityContext: runAsUser: 2000
Chapter 22. JXPath Overview The JXPath language enables you to invoke Java beans using the Apache Commons JXPath language. The JXPath language has a similar syntax to XPath, but instead of selecting element or attribute nodes from an XML document, it invokes methods on an object graph of Java beans. If one of the bean attributes returns an XML document (a DOM/JDOM instance), however, the remaining portion of the path is interpreted as an XPath expression and is used to extract an XML node from the document. In other words, the JXPath language provides a hybrid of object graph navigation and XML node selection. Adding JXPath package To use JXPath in your routes you need to add a dependency on camel-jxpath to your project as shown in Example 22.1, "Adding the camel-jxpath dependency" . Example 22.1. Adding the camel-jxpath dependency Variables Table 22.1, "JXPath variables" lists the variables that are accessible when using JXPath. Table 22.1. JXPath variables Variable Type Value this org.apache.camel.Exchange The current Exchange in org.apache.camel.Message The IN message out org.apache.camel.Message The OUT message Options Table 22.2, "JXPath option" describes the option for JXPath. Table 22.2. JXPath option Option Type Description lenient boolean Camel 2.11/2.10.5: Allows to turn lenient on the JXPathContext. When turned on this option allows the JXPath expression to evaluate against expressions and message bodies which might be invalid or missing data. See more details at the JXPath Documentation . This option is false, by default. Examples The following example route uses JXPath: The following simple example uses a JXPath expression as a predicate in a Message Filter: JXPath injection You can use Bean Integration to invoke a method on a bean and use various languages, such as JXPath, to extract a value from the message and bind it to a method parameter. For example: Loading the script from an external resource Available as of Camel 2.11 You can externalize the script and have Camel load it from a resource such as "classpath:" , "file:" , or "http:" . Use the following syntax: For example, to reference a file on the classpath:

Commands:
<!-- Maven POM File --> <properties> <camel-version>2.23.2.fuse-7_13_0-00013-redhat-00001</camel-version> </properties> <dependencies> <dependency> <groupId>org.apache.camel</groupId> <artifactId>camel-jxpath</artifactId> <version>USD{camel-version}</version> </dependency> </dependencies>
<camelContext> <route> <from uri="activemq:MyQueue"/> <filter> <jxpath>in/body/name = 'James'</xpath> <to uri="mqseries:SomeOtherQueue"/> </filter> </route> </camelContext>
from("direct:start"). filter().jxpath("in/body/name='James'"). to("mock:result");
public class Foo { @MessageDriven(uri = "activemq:my.queue") public void doSomething(@JXPath("in/body/foo") String correlationID, @Body String body) { // process the inbound message here } }
"resource:scheme:location"
.setHeader("myHeader").jxpath("resource:classpath:myjxpath.txt")
10.9. Creating a Snapshot of Geo-replicated Volume The Red Hat Gluster Storage Snapshot feature enables you to create point-in-time copies of Red Hat Gluster Storage volumes, which you can use to protect data. You can create snapshots of Geo-replicated volumes. For information on prerequisites, creating, and restoring snapshots of geo-replicated volume, see Chapter 8, Managing Snapshots . Creation of a snapshot when geo-replication session is live is not supported and creation of snapshot in this scenario will display the following error: . You must ensure to pause the geo-replication session before creating snapshot and resume geo-replication session after creating the snapshot. Information on restoring geo-replicated volume is also available in the Managing Snapshots chapter.

Commands:
gluster snapshot create snap1 master snapshot create: failed: geo-replication session is running for the volume master. Session needs to be stopped before taking a snapshot. Snapshot command failed
16.8. Configuring Multiple Subtrees and Filters in Windows Synchronization Windows Synchronization is designed to synchronize between multiple pairs of subtrees on the Directory Server (DS) and Active Directory (AD). By using filters, only specified entries under a subtree are synchronized. Multiple Subtrees in Windows Synchronization To synchronize among multiple subtree pairs, configure the Directory Server and the Active Directory subtrees in the winSyncSubtreePair parameter in the Windows sync agreement. For example to set multiple the ou=OU1,dc=DSexample,dc=com and ou=OU1,DC=ADexample,DC=com subtree: If winSyncSubtreePair is not set, the nsds7WindowsReplicaSubtree AD subtree parameter and the nsds7DirectoryReplicaSubtree DS subtree parameter are used for the synchronization target checks instead. Otherwise, these two parameters are ignored. Filters in Windows Synchronization You can set a filter that selects data to be synchronized in the following parameters: --win-filter sets an additional filter on the Active Directory server, --ds-filter parameter sets an additional filter on Directory Server. The following example configures that the example_agreement synchronizes entries that contain user and group attributes:

Commands:
dsconf -D "cn=Directory Manager" ldap://server.example.com repl-winsync-agmt set --subtree-pair="ou=OU1,dc=DSexample,dc=com:ou=OU1,DC=ADexample,DC=com" --suffix=" dc=example,dc=com " example-agreement
dsconf -D "cn=Directory Manager" ldap://server.example.com repl-winsync-agmt set --win-filter=" (|(cn=*user*)(cn=*group*)) " --ds-filter=" (|(uid=*user*)(cn=*group*)) " example_agreement