mtpti5iD/redhat-docs_dataset huggingface dataset:
Chapter 3. Identity providers In the Quarkus Security framework, identity providers play a crucial role in authentication and authorization by verifying user identities. IdentityProvider creates a SecurityIdentity instance, which gets used during user authentication to verify and authorize access requests to your Quarkus application. IdentityProvider converts the authentication credentials provided by HttpAuthenticationMechanism to a SecurityIdentity instance. Some extensions, for example, OIDC , OAuth2 , and SmallRye JWT , have inline IdentityProvider implementations specific to the supported authentication flow. For example, quarkus-oidc uses its own IdentityProvider to convert a token to a SecurityIdentity instance. If you use Basic or form-based authentication, you must add an IdentityProvider instance to convert a username and password to a SecurityIdentity instance. To get started with security in Quarkus, consider combining the Quarkus built-in Basic HTTP authentication with the Jakarta Persistence identity provider to enable role-based access control (RBAC). For more information about Basic authentication, its mechanisms, and related identity providers, see the following resources: Quarkus Security with Jakarta Persistence Getting started with Security by using Basic authentication and Jakarta Persistence Form-based authentication Using security with JDBC Using security with an LDAP realm Quarkus Security overview

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Chapter 6. Uninstalling power monitoring Important Power monitoring is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope . You can uninstall power monitoring by deleting the Kepler instance and then the Power monitoring Operator in the OpenShift Container Platform web console. 6.1. Deleting Kepler You can delete Kepler by removing the Kepler instance of the Kepler custom resource definition (CRD) from the OpenShift Container Platform web console. Prerequisites You have access to the OpenShift Container Platform web console. You are logged in as a user with the cluster-admin role. Procedure In the Administrator perspective of the web console, go to Operators Installed Operators . Click Power monitoring for Red Hat OpenShift from the Installed Operators list and go to the Kepler tab. Locate the Kepler instance entry in the list. Click for this entry and select Delete Kepler . In the Delete Kepler? dialog, click Delete to delete the Kepler instance. 6.2. Uninstalling the Power monitoring Operator If you installed the Power monitoring Operator by using OperatorHub, you can uninstall it from the OpenShift Container Platform web console. Prerequisites You have access to the OpenShift Container Platform web console. You are logged in as a user with the cluster-admin role. Procedure Delete the Kepler instance. Warning Ensure that you have deleted the Kepler instance before uninstalling the Power monitoring Operator. Go to Operators Installed Operators . Locate the Power monitoring for Red Hat OpenShift entry in the list. Click for this entry and select Uninstall Operator . In the Uninstall Operator? dialog, click Uninstall to uninstall the Power monitoring Operator.

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8.86. libXcursor 8.86.1. RHBA-2013:0906 - libXcursor bug fix update Updated libXcursor packages that fix one bug are now available for Red Hat Enterprise Linux 6. The X.Org's X11 libXcursor package provides a runtime library for cursor management, designed to help locate and load cursors. Bug Fix BZ#949586 In the last rebuild of libXcursor, the Icon Theme was changed to Adwaita, which was not available in Red Hat Enterprise Linux 6. To fix this bug, the Icon Theme has been changed back to dmz-aa for Red Hat Enterprise Linux 6. Users of libXcursor are advised to upgrade to these updated packages, which fix this bug.

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8.6. Managed Resources You can set a resource to unmanaged mode, which indicates that the resource is still in the configuration but Pacemaker does not manage the resource. The following command sets the indicated resources to unmanaged mode. The following command sets resources to managed mode, which is the default state. You can specify the name of a resource group with the pcs resource manage or pcs resource unmanage command. The command will act on all of the resources in the group, so that you can set all of the resources in a group to managed or unmanaged mode with a single command and then manage the contained resources individually.

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pcs resource unmanage resource1 [ resource2 ]
pcs resource manage resource1 [ resource2 ]
5.9.6.2. Removing Storage The process of removing storage from a Red Hat Enterprise Linux system is relatively straightforward. Here are the steps that are specific to Red Hat Enterprise Linux: Remove the disk drive's partitions from /etc/fstab Unmount the disk drive's active partitions Erase the contents of the disk drive The following sections cover these topics in more detail. 5.9.6.2.1. Remove the Disk Drive's Partitions From /etc/fstab Using the text editor of your choice, remove the line(s) corresponding to the disk drive's partition(s) from the /etc/fstab file. You can identify the proper lines by one of the following methods: Matching the partition's mount point against the directories in the second column of /etc/fstab Matching the device's file name against the file names in the first column of /etc/fstab Note Be sure to look for any lines in /etc/fstab that identify swap partitions on the disk drive to be removed; they can be easily overlooked.

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Chapter 3. Storage classes and storage pools The OpenShift Container Storage operator installs a default storage class depending on the platform in use. This default storage class is owned and controlled by the operator and it cannot be deleted or modified. However, you can create a custom storage class if you want the storage class to have a different behavior. You can create multiple storage pools which map to storage classes that provide the following features: Enable applications with their own high availability to use persistent volumes with two replicas, potentially improving application performance. Save space for persistent volume claims using storage classes with compression enabled. Note Multiple storage classes and multiple pools are not supported for external mode OpenShift Container Storage clusters. Note With a minimal cluster of a single device set, only two new storage classes can be created. Every storage cluster expansion allows two new additional storage classes. 3.1. Creating storage classes and pools You can create a storage class using an existing pool or you can create a new pool for the storage class while creating it. Prerequisites Ensure that the OpenShift Container Storage cluster is in Ready state. Procedure Log in to OpenShift Web Console. Click Storage Storage Classes . Click Create Storage Class . Enter the storage class Name and Description . Select either Delete or Retain for the Reclaim Policy. By default, Delete is selected. Select RBD Provisioner which is the plugin used for provisioning the persistent volumes. You can either create a new pool or use an existing one. Create a new pool Enter a name for the pool. Choose 2-way-Replication or 3-way-Replication as the Data Protection Policy. Select Enable compression if you need to compress the data. Enabling compression can impact application performance and might prove ineffective when data to be written is already compressed or encrypted. Data written before enabling compression will not be compressed. Click Create to create the storage pool. Click Finish after the pool is created. Click Create to create the storage class. Use an existing pool Choose a pool from the list. Click Create to create the storage class with the selected pool.

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Chapter 32. Storage kernel component, BZ#1170328 When the Internet Small Computer System Interface (iSCSI) target is set up using the iSCSI Extensions for RDMA (iSER) interface, an attempt to run a discovery over iSER fails. Consequently, in some cases, the target panics. Users are advised to not use iSER for discovery but use iSER only for the login phase. kernel component, BZ#1185396 When using the server as an iSER-enabled iSCSI target and connection losses occur repeatedly, the target can stop responding. Consequently, the kernel becomes unresponsive. To work around this issue, minimize iSER connection losses or revert to non-iSER iSCSI mode. kernel component, BZ#1061871, BZ#1201247 When a storage array returns a CHECK CONDITION status but the sense data is invalid, the Small Computer Systems Interface (SCSI) mid-layer code retries the I/O operation. If subsequent I/O operations receive the same result, I/O operations are retried indefinitely. For this bug, no workaround is currently available.

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Providing feedback on Red Hat documentation We appreciate your input on our documentation. Tell us how we can make it better. Providing documentation feedback in Jira Use the Create Issue form to provide feedback on the documentation. The Jira issue will be created in the Red Hat OpenStack Platform Jira project, where you can track the progress of your feedback. Ensure that you are logged in to Jira. If you do not have a Jira account, create an account to submit feedback. Click the following link to open a the Create Issue page: Create Issue Complete the Summary and Description fields. In the Description field, include the documentation URL, chapter or section number, and a detailed description of the issue. Do not modify any other fields in the form. Click Create .

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Chapter 1. Overview of HawtIO Important Technology Preview features are not supported with Red Hat production service-level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend implementing any Technology Preview features in production environments. This Technology Preview feature provides early access to upcoming product innovations, enabling you to test functionality and provide feedback during the development process. For more information about support scope, see Technology Preview Features Support Scope . HawtIO is a diagnostic Console for the Red Hat build of Apache Camel and Red Hat build of AMQ. It is a pluggable Web diagnostic console built with modern Web technologies such as React and PatternFly . HawtIO provides a central interface to examine and manage the details of one or more deployed HawtIO-enabled containers. HawtIO is available when you install HawtIO standalone or use HawtIO on OpenShift. The integrations that you can view and manage in HawtIO depend on the plugins that are running. You can monitor HawtIO and system resources, perform updates, and start or stop services. The pluggable architecture is based on Webpack Module Federation and is highly extensible; you can dynamically extend HawtIO with your plugins or automatically discover plugins inside the JVM. HawtIO has built-in plugins already to make it highly useful out of the box for your JVM application. The plugins include Apache Camel, Connect, JMX, Logs, Runtime, Quartz, and Spring Boot. HawtIO is primarily designed to be used with Camel Quarkus and Camel Spring Boot. It's also a tool for managing microservice applications. HawtIO is cloud-native; it's ready to go over the cloud! You can deploy it to Kubernetes and OpenShift with the HawtIO Operator . Benefits of HawtIO can be listed as follows: Runtime management of JVM via JMX, especially that of Camel applications and AMQ broker, with specialized views Visualization and debugging/tracing of Camel routes Simple managing and monitoring of application metrics

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24.5. Performance Tuning Click on the Performance Tuning tab to configure the maximum number of child server processes you want and to configure the Apache HTTP Server options for client connections. The default settings for these options are appropriate for most situations. Altering these settings may affect the overall performance of your Web server. Figure 24.11. Performance Tuning Set Max Number of Connections to the maximum number of simultaneous client requests that the server can handle. For each connection, a child httpd process is created. After this maximum number of processes is reached, no one else can connect to the Web server until a child server process is freed. You can not set this value to higher than 256 without recompiling. This option corresponds to the MaxClients directive. Connection Timeout defines, in seconds, the amount of time that your server waits for receipts and transmissions during communications. Specifically, Connection Timeout defines how long your server waits to receive a GET request, how long it waits to receive TCP packets on a POST or PUT request, and how long it waits between ACKs responding to TCP packets. By default, Connection Timeout is set to 300 seconds, which is appropriate for most situations. This option corresponds to the TimeOut directive. Set the Max requests per connection to the maximum number of requests allowed per persistent connection. The default value is 100, which should be appropriate for most situations. This option corresponds to the MaxRequestsPerChild directive. If you check the Allow unlimited requests per connection option, the MaxKeepAliveRequests directive is set to 0 and unlimited requests are allowed. If you uncheck the Allow Persistent Connections option, the KeepAlive directive is set to false. If you check it, the KeepAlive directive is set to true, and the KeepAliveTimeout directive is set to the number that is selected as the Timeout for Connection value. This directive sets the number of seconds your server waits for a subsequent request, after a request has been served, before it closes the connection. Once a request has been received, the Connection Timeout value applies instead. Setting the Persistent Connections to a high value may cause the server to slow down, depending on how many users are trying to connect to it. The higher the number, the more server processes are waiting for another connection from the last client that connected to it.

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Chapter 15. Accessing the RADOS Object Gateway S3 endpoint Users can access the RADOS Object Gateway (RGW) endpoint directly. In versions of Red Hat OpenShift Data Foundation, RGW service needed to be manually exposed to create RGW public route. As of OpenShift Data Foundation version 4.7, the RGW route is created by default and is named rook-ceph-rgw-ocs-storagecluster-cephobjectstore .

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Chapter 10. Servers and Services Restored performance of 32-bit version of GMP In a update of RHEL 6.9, a performance regression was accidentally introduced to the 32-bit version of the GNU Multiple Precision Arithmetic Library (GMP) for AMD and Intel architecture. As a consequence, the 32-bit version of the GMP suffered marginally decreased performance. A fix has been deployed and GMP peformance has been restored to values. (BZ#1430873)

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Chapter 7. Setting up to Develop Applications Using Python The Python language version 2.7.5 is available as part of Red Hat Enterprise Linux. Newer versions of the Python interpreter and libraries (including a newer version of Python 2.7) are available as Red Hat Software Collections packages. Install the package with the desired version according to the table below. Python versions corresponding to Red Hat Software Collections packages Version Package Python 2.7 python27 Python 3.6 rh-python36 Python 3.8 rh-python38 The python27 software collection is an updated version of the Python 2 packages in RHEL 7. Install the Eclipse integrated development environment which supports development in the Python language. Eclipse is available as part of Red Hat Developer Tools. For the actual installation procedure, see Using Eclipse . Additional Resources Red Hat Software Collections Hello-World - Python Red Hat Software Collections

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yum install package
Chapter 2. Installing and configuring the MTR plugin You can install the MTR plugin and configure it to use the MTR CLI for analysis execution. 2.1. Installing in a connected environment You need a connected environment to install the MTR plugin. The MTR plugin has been tested with the Eclipse IDE for Java Enterprise Developers 2023-03. Prerequisites The following are the prerequisites for the Migration Toolkit for Runtimes (MTR) installation: Java Development Kit (JDK) is installed. MTR supports the following JDKs: OpenJDK 11 OpenJDK 17 Oracle JDK 11 Oracle JDK 17 Eclipse TemurinTM JDK 11 Eclipse TemurinTM JDK 17 8 GB RAM macOS installation: the value of maxproc must be 2048 or greater. Eclipse IDE for Java Enterprise Developers 2023-03 JBoss Tools, installed from the Eclipse Marketplace Mylyn SDK and frameworks , installed with Eclipse Note Eclipse is pre-configured for Java 17, and the plugin operates directly with Java 17. You can also run the plugin with Java 11, which requires setting the JRE version to Java 11 when creating up a new Eclipse project or importing an existing one. See step 6 below. Procedure Launch Eclipse. From the menu bar, select Help Install New Software . to the Work with field, click Add . In the Name field, enter MTR . In the Location field, enter https://marketplace.eclipse.org/content/migration-toolkit-runtimes-mtr and click OK . Select the Java version to use. If using Java 11, in the JRE list, select JavaSE 11 . If using Java 17, leave the JRE selection unchanged. Select all the JBoss Tools - MTR check boxes and click . Review the installation details and click . Accept the terms of the license agreement and click Finish . Restart Eclipse. 2.2. Configuring the MTR plugin to use the MTR CLI for analysis execution You can configure the MTR plugin to use the MTR CLI for analysis execution. Prerequisites You have downloaded the MTR CLI from the Developers Website or Customer Portal and installed it locally. Procedure Click the Configure MTR icon to open the configuration settings. Populate the CLI field with the path to the parent directory of the CLI. Click Apply .

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Chapter 3. Red Hat build of OpenJDK 8.0.442 release notes The latest Red Hat build of OpenJDK 8 release might include new features. Additionally, the latest release might enhance, deprecate, or remove features that originated from earlier Red Hat build of OpenJDK 8 releases. Note For all the other changes and security fixes, see OpenJDK 8u442 Released . Red Hat build of OpenJDK new features and enhancements Review the following release notes to understand new features and feature enhancements that Red Hat build of OpenJDK 8.0.442 provides: Option for jar command to avoid overwriting files when extracting an archive In earlier Red Hat build of OpenJDK releases, when the jar tool extracted files from an archive, the jar tool overwrote any existing files with the same name in the target directory. Red Hat build of OpenJDK 8.0.442 adds a new ‐k option that you can use to ensure that the jar tool does not overwrite existing files. For example: Note In Red Hat build of OpenJDK 8.0.442, the jar tool retains the old behavior by default. If you do not explicitly specify the ‐k option, the jar tool automatically overwrites any existing files with the same name. See JDK-8335912 (JDK Bug System) and JDK bug system reference ID: JDK-8337499.

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jar xkf myfile.jar
Chapter 1. Load Balancing Solution Architecture You can configure Satellite Server to use a load balancer to distribute client requests and network load across multiple Capsule Servers. This results in an overall performance improvement on Capsule Servers. This guide outlines how to prepare Satellite Server and Capsule Server for load balancing, and provides guidelines on how to configure a load balancer and register clients in a load-balanced setup. A load-balanced setup consists of the following components: Satellite Server Two or more Capsule Servers A load balancer Multiple clients Figure 1.1. Satellite Load Balancing Solution Architecture In a load-balanced setup, nearly all Capsule functionality continues to work as expected when one Capsule Server is down, for planned or unplanned maintenance. Load balancer works with the following services and features: Registration using subscription-manager Content Management with yum repositories Optional: Puppet Note In the load-balanced setup, a load balancer distributes load only for the services and features mentioned above. If other services, such as provisioning or virt-who, are running on the individual Capsules, you must access them directly through Capsules and not through the load balancer. Managing Puppet Limitations Puppet Certificate Authority (CA) management does not support certificate signing in a load-balanced setup. Puppet CA stores certificate information, such as the serial number counter and CRL, on the file system. Multiple writer processes that attempt to use the same data can corrupt it. To manage this Puppet limitation, complete the following steps: Configure Puppet certificate signing on one Capsule Server, typically the first system where you configure Capsule Server for load balancing. Configure the clients to send CA requests to port 8141 on a load balancer. Configure a load balancer to redirect CA requests from port 8141 to port 8140 on the system where you configure Capsule Server to sign Puppet certificates.

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Chapter 2. Configuring the Fujitsu ETERNUS device Configure storage pools and ports on the device before you define the Fujitsu ETERNUS device as a Block Storage back end. Consult your device documentation for details on each step: Procedure Configure a LAN connection between the Controller nodes that host the Block Storage service and the MNT ports of the ETERNUS device. Configure a SAN connection between the Compute nodes and CA ports of the ETERNUS device. Log in to the ETERNUS device using an account with the Admin role. Enable the SMI-S of ETERNUS DX. Set the SSH key Add a user account with software role. Register an Advanced Copy Feature license and configure the copy table size. Create a storage pool for volumes. You use this pool later in the EternusPool setting in Section 3.1, "Creating driver definitions for each Fujitsu ETERNUS back end" . Optional: Create a separate storage pool for volume snapshots. This pool represents the EternusSnapPool setting in Section 3.1, "Creating driver definitions for each Fujitsu ETERNUS back end" . Optional: Create a Snap Data Pool Volume (SDPV) to enable Snap Data Pool (SDP) for the create a snapshot function. Tip Skip this step if you use a Thin Provision Pool for EternusSnapPool . Configure storage ports to be used by the Block Storage service. Set the storage ports ports to CA mode. To enable host-affinity for the storage ports, enter the following command from the ETERNUS CLI for each port: Replace <PROTO> with the storage protocol, such as fc or iscsi . Replace <CM#> and <CA#> with the name of the controller enclosure where the port is located. Replace <PORT> with the port number. Use the following commands to generate the SSH key on the undercloud, and upload the eternus.ietf file to the ETERNUS device. Note Save the eternus file for later use. For security reasons, do not copy or move it from the undercloud or overcloud.

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set <PROTO>-parameters -host-affinity enable -port <CM#> <CA#> <PORT>
ssh-keygen -t rsa -N "" -f ./eternus ssh-keygen -e -f ./eternus.pub > ./eternus.ietf