mtpti5iD/redhat-docs_dataset huggingface dataset:
Chapter 1. Monitoring APIs 1.1. Alertmanager [monitoring.coreos.com/v1] Description Alertmanager describes an Alertmanager cluster. Type object 1.2. AlertmanagerConfig [monitoring.coreos.com/v1beta1] Description AlertmanagerConfig configures the Prometheus Alertmanager, specifying how alerts should be grouped, inhibited and notified to external systems. Type object 1.3. AlertRelabelConfig [monitoring.openshift.io/v1] Description AlertRelabelConfig defines a set of relabel configs for alerts. Compatibility level 1: Stable within a major release for a minimum of 12 months or 3 minor releases (whichever is longer). Type object 1.4. AlertingRule [monitoring.openshift.io/v1] Description AlertingRule represents a set of user-defined Prometheus rule groups containing alerting rules. This resource is the supported method for cluster admins to create alerts based on metrics recorded by the platform monitoring stack in OpenShift, i.e. the Prometheus instance deployed to the openshift-monitoring namespace. You might use this to create custom alerting rules not shipped with OpenShift based on metrics from components such as the node_exporter, which provides machine-level metrics such as CPU usage, or kube-state-metrics, which provides metrics on Kubernetes usage. The API is mostly compatible with the upstream PrometheusRule type from the prometheus-operator. The primary difference being that recording rules are not allowed here - only alerting rules. For each AlertingRule resource created, a corresponding PrometheusRule will be created in the openshift-monitoring namespace. OpenShift requires admins to use the AlertingRule resource rather than the upstream type in order to allow better OpenShift specific defaulting and validation, while not modifying the upstream APIs directly. You can find upstream API documentation for PrometheusRule resources here: https://github.com/prometheus-operator/prometheus-operator/blob/main/Documentation/api.md Compatibility level 1: Stable within a major release for a minimum of 12 months or 3 minor releases (whichever is longer). Type object 1.5. PodMonitor [monitoring.coreos.com/v1] Description PodMonitor defines monitoring for a set of pods. Type object 1.6. Probe [monitoring.coreos.com/v1] Description Probe defines monitoring for a set of static targets or ingresses. Type object 1.7. Prometheus [monitoring.coreos.com/v1] Description Prometheus defines a Prometheus deployment. Type object 1.8. PrometheusRule [monitoring.coreos.com/v1] Description PrometheusRule defines recording and alerting rules for a Prometheus instance Type object 1.9. ServiceMonitor [monitoring.coreos.com/v1] Description ServiceMonitor defines monitoring for a set of services. Type object 1.10. ThanosRuler [monitoring.coreos.com/v1] Description ThanosRuler defines a ThanosRuler deployment. Type object

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1.10.3. Security As stated earlier in this chapter, security cannot be an afterthought, and security under Red Hat Enterprise Linux is more than skin-deep. Authentication and access controls are deeply-integrated into the operating system and are based on designs gleaned from long experience in the UNIX community. For authentication, Red Hat Enterprise Linux uses PAM -- Pluggable Authentication Modules. PAM makes it possible to fine-tune user authentication via the configuration of shared libraries that all PAM-aware applications use, all without requiring any changes to the applications themselves. Access control under Red Hat Enterprise Linux uses traditional UNIX-style permissions (read, write, execute) against user, group, and "everyone else" classifications. Like UNIX, Red Hat Enterprise Linux also makes use of setuid and setgid bits to temporarily confer expanded access rights to processes running a particular program, based on the ownership of the program file. Of course, this makes it critical that any program to be run with setuid or setgid privileges must be carefully audited to ensure that no exploitable vulnerabilities exist. Red Hat Enterprise Linux also includes support for access control lists . An access control list (ACL) is a construct that allows extremely fine-grained control over what users or groups may access a file or directory. For example, a file's permissions may restrict all access by anyone other than the file's owner, yet the file's ACL can be configured to allow only user bob to write and group finance to read the file. Another aspect of security is being able to keep track of system activity. Red Hat Enterprise Linux makes extensive use of logging, both at a kernel and an application level. Logging is controlled by the system logging daemon syslogd , which can log system information locally (normally to files in the /var/log/ directory) or to a remote system (which acts as a dedicated log server for multiple computers.) Intrusion detection sytems (IDS) are powerful tools for any Red Hat Enterprise Linux system administrator. An IDS makes it possible for system administrators to determine whether unauthorized changes were made to one or more systems. The overall design of the operating system itself includes IDS-like functionality. Because Red Hat Enterprise Linux is installed using the RPM Package Manager (RPM), it is possible to use RPM to verify whether any changes have been made to the packages comprising the operating system. However, because RPM is primarily a package management tool, its abilities as an IDS are somewhat limited. Even so, it can be a good first step toward monitoring a Red Hat Enterprise Linux system for unauthorized modifications.

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Chapter 26. Virtualization Nested virtualization As a Technology Preview, Red Hat Enterprise Linux 7.2 offers nested virtualization. This feature enables KVM to launch guests that can act as hypervisors and create their own guests. The virt-p2v tool Red Hat Enterprise Linux 7.2 offers the virt-p2v tool as a Technology Preview. virt-p2v (physical to virtual) is a CD-ROM, ISO or PXE image that the user can boot on a physical machine, and that creates a KVM virtual machine with disk contents identical to the physical machine. USB 3.0 support for KVM guests USB 3.0 host adapter (xHCI) emulation for KVM guests remains a Technology Preview in Red Hat Enterprise Linux 7.2. VirtIO-1 support Virtio drivers have been updated to Kernel 4.1 to provide VirtIO 1.0 Device Support. Open Virtual Machine Firmware The Open Virtual Machine Firmware (OVMF) is available as a Technology Preview in Red Hat Enterprise Linux 7. OVMF is a UEFI secure boot environment for AMD64 and Intel 64 guests. However, OVMF is not bootable with virtualization components available in RHEL 7. Note that OVMF is fully supported in RHEL 8.

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Appendix B. Sharing reports with non-administrators Users without administrator privileges can view collected logs and metrics as read-only users. The following example creates a user named user name with view (read-only) permissions. Procedure Log in to the Metrics Store virtual machine. Create a new user: Log in to the openshift-logging project: Assign a view role to the user: Create a password for the user:

Commands:
oc create user username # oc create identity allow_all: username # oc create useridentitymapping allow_all: username username
oc project openshift-logging
oc adm policy add-role-to-user view user name
oc login --username= user name --password= password
Chapter 21. Supportability and Maintenance ABRT 2.1 Red Hat Enterprise Linux 7 includes the Automatic Bug Reporting Tool ( ABRT ) 2.1, which features an improved user interface and the ability to send mReports , lightweight anonymous problem reports suitable for machine processing, such as gathering crash statistics. The set of supported languages, for which ABRT is capable of detecting problems, has been extended with the addition of Java and Ruby in ABRT 2.1. In order to use ABRT , ensure that the abrt-desktop or the abrt-cli package is installed on your system. The abrt-desktop package provides a graphical user interface for ABRT , and the abrt-cli package contains a tool for using ABRT on the command line. You can also install both. To install the package containing the graphical user interface for ABRT , run the following command as the root user: To install the package that provides the command line ABRT tool, use the following command: Note that while both of the above commands cause the main ABRT system to be installed, you may need to install additional packages to obtain support for detecting crashes in software programmed using various languages. See the Automatic Bug Reporting Tool (ABRT) chapter of the Red Hat Enterprise Linux 7 System Administrator's Guide for information on additional packages available with the ABRT system. Upon installation, the abrtd daemon, which is the core of the ABRT crash-detecting service, is configured to start at boot time. You can use the following command to verify its current status: In order to discover as many software bugs as possible, administrators should configure ABRT to automatically send reports of application crashes to Red Hat. To enable the autoreporting feature, issue the following command as root : Additional Information on ABRT Red Hat Enterprise Linux 7 System Administrator's Guide - The Automatic Bug Reporting Tool (ABRT) chapter of the Administrator's Guide for Red Hat Enterprise Linux 7 contains detailed information on installing, configuring, and using the ABRT service.

Commands:
~]# yum install abrt-desktop
~]# yum install abrt-cli
~]USD systemctl is-active abrtd.service active
~]# abrt-auto-reporting enabled
4.2. Creating an Image Builder blueprint in the web console interface To describe the customized system image, create a blueprint first. Prerequisites You have opened the Image Builder interface of the RHEL 7 web console in a browser. Procedure 1. Click Create Blueprint in the top right corner. Figure 4.3. Creating a Blueprint A pop-up appears with fields for the blueprint name and description . 2. Fill in the name of the blueprint, its description, then click Create. The screen changes to blueprint editing mode . 3. Add components that you want to include in the system image: i. On the left, enter all or part of the component name in the Available Components field and press Enter. Figure 4.4. Searching for Available Componentes The search is added to the list of filters under the text entry field, and the list of components below is reduced to these that match the search. If the list of components is too long, add further search terms in the same way. ii. The list of components is paged. To move to other result pages, use the arrows and entry field above the component list. iii. Click on name of the component you intend to use to display its details. The right pane fills with details of the components, such as its version and dependencies. iv. Select the version you want to use in the Component Options box, with the Version Release dropdown. v. Click Add in the top left. vi. If you added a component by mistake, remove it by clicking the ... button at the far right of its entry in the right pane, and select Remove in the menu. Note If you do not intend to select version for some components, you can skip the component details screen and version selection by clicking the + buttons on the right side of the component list. 4. To save the blueprint, click Commit in the top right. A dialog with a summary of the changes pops up. Click Commit . A small pop-up on the right informs you of the saving progress and then the result. 5. To exit the editing screen, click Back to Blueprints in the top left. The Image Builder view opens, listing existing blueprints.

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Providing feedback on Red Hat build of OpenJDK documentation To report an error or to improve our documentation, log in to your Red Hat Jira account and submit an issue. If you do not have a Red Hat Jira account, then you will be prompted to create an account. Procedure Click the following link to create a ticket . Enter a brief description of the issue in the Summary . Provide a detailed description of the issue or enhancement in the Description . Include a URL to where the issue occurs in the documentation. Clicking Submit creates and routes the issue to the appropriate documentation team.

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Chapter 10. Creating an XFS file system As a system administrator, you can create an XFS file system on a block device to enable it to store files and directories. 10.1. Creating an XFS file system with mkfs.xfs This procedure describes how to create an XFS file system on a block device. Procedure To create the file system: If the device is a regular partition, an LVM volume, an MD volume, a disk, or a similar device, use the following command: Replace block-device with the path to the block device. For example, /dev/sdb1 , /dev/disk/by-uuid/05e99ec8-def1-4a5e-8a9d-5945339ceb2a , or /dev/my-volgroup/my-lv . In general, the default options are optimal for common use. When using mkfs.xfs on a block device containing an existing file system, add the -f option to overwrite that file system. To create the file system on a hardware RAID device, check if the system correctly detects the stripe geometry of the device: If the stripe geometry information is correct, no additional options are needed. Create the file system: If the information is incorrect, specify stripe geometry manually with the su and sw parameters of the -d option. The su parameter specifies the RAID chunk size, and the sw parameter specifies the number of data disks in the RAID device. For example: Use the following command to wait for the system to register the new device node: Additional resources mkfs.xfs(8) man page on your system

Commands:
mkfs.xfs block-device
mkfs.xfs block-device
mkfs.xfs -d su= 64k ,sw= 4 /dev/sda3
udevadm settle
1.8.2. Three-Tier LVS Topology Figure 1.22, "Three-Tier LVS Topology" shows a typical three-tier LVS configuration. In the example, the active LVS router routes the requests from the public network (Internet) to the second tier - real servers. Each real server then accesses a shared data source of a Red Hat cluster in the third tier over the private network. Figure 1.22. Three-Tier LVS Topology This topology is suited well for busy FTP servers, where accessible data is stored on a central, highly available server and accessed by each real server via an exported NFS directory or Samba share. This topology is also recommended for websites that access a central, high-availability database for transactions. Additionally, using an active-active configuration with a Red Hat cluster, you can configure one high-availability cluster to serve both of these roles simultaneously.

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Appendix A. Component Versions This appendix is a list of components and their versions in the Red Hat Enterprise Linux 6.7 release. Table A.1. Component Versions Component Version Kernel 2.6.32-573 QLogic qla2xxx driver 8.07.00.16.06.7-k QLogic ql2xxx firmware ql2100-firmware-1.19.38-3.1 ql2200-firmware-2.02.08-3.1 ql23xx-firmware-3.03.27-3.1 ql2400-firmware-7.03.00-1 ql2500-firmware-7.03.00-1 Emulex lpfc driver 10.6.0.20 iSCSI initiator utils iscsi-initiator-utils-6.2.0.873-14 DM-Multipath device-mapper-multipath-libs-0.4.9-87 LVM lvm2-2.02.118-2

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Chapter 2. Deploying Red Hat build of OpenJDK application in containers You can deploy Red Hat build of OpenJDK applications in containers and have them run when the container is loaded. Procedure Copy the application JAR to the /deployments directory in the image JAR file. For example, the following shows a brief Dockerfile that adds an application called testubi.jar to the Red Hat build of OpenJDK 11 UBI8 image:

Commands:
FROM registry.access.redhat.com/ubi8/openjdk-11 COPY target/testubi.jar /deployments/testubi.jar
Chapter 12. Configuring OpenShift connection timeout By default, the OpenShift route is configured to time out HTTP requests that are longer than 30 seconds. This may cause session timeout issues in Business Central resulting in the following behaviors: "Unable to complete your request. The following exception occurred: (TypeError) : Cannot read property 'indexOf' of null." "Unable to complete your request. The following exception occurred: (TypeError) : b is null." A blank page is displayed when clicking the Project or Server links in Business Central. All Business Central templates already include extended timeout configuration. To configure longer timeout on Business Central OpenShift routes, add the haproxy.router.openshift.io/timeout: 60s annotation on the target route: - kind: Route apiVersion: v1 id: "USDAPPLICATION_NAME-rhpamcentr-http" metadata: name: "USDAPPLICATION_NAME-rhpamcentr" labels: application: "USDAPPLICATION_NAME" annotations: description: Route for Business Central's http service. haproxy.router.openshift.io/timeout: 60s spec: host: "USDBUSINESS_CENTRAL_HOSTNAME_HTTP" to: name: "USDAPPLICATION_NAME-rhpamcentr" For a full list of global route-specific timeout annotations, see the OpenShift Documentation .

Commands:
- kind: Route apiVersion: v1 id: "USDAPPLICATION_NAME-rhpamcentr-http" metadata: name: "USDAPPLICATION_NAME-rhpamcentr" labels: application: "USDAPPLICATION_NAME" annotations: description: Route for Business Central's http service. haproxy.router.openshift.io/timeout: 60s spec: host: "USDBUSINESS_CENTRAL_HOSTNAME_HTTP" to: name: "USDAPPLICATION_NAME-rhpamcentr"
Chapter 1. About Serverless 1.1. OpenShift Serverless overview OpenShift Serverless provides Kubernetes native building blocks that enable developers to create and deploy serverless, event-driven applications on OpenShift Container Platform. OpenShift Serverless is based on the open source Knative project , which provides portability and consistency for hybrid and multi-cloud environments by enabling an enterprise-grade serverless platform. Note Because OpenShift Serverless releases on a different cadence from OpenShift Container Platform, the OpenShift Serverless documentation is now available as a separate documentation set at Red Hat OpenShift Serverless .

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Preface As a data scientist, you can organize your data science work into a single project. A data science project in OpenShift AI can consist of the following components: Workbenches Creating a workbench allows you to work with models in your preferred IDE, such as JupyterLab. Cluster storage For data science projects that require data retention, you can add cluster storage to the project. Connections Adding a connection to your project allows you to connect data inputs to your workbenches. Pipelines Standardize and automate machine learning workflows to enable you to further enhance and deploy your data science models. Models and model servers Deploy a trained data science model to serve intelligent applications. Your model is deployed with an endpoint that allows applications to send requests to the model.

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Chapter 4. Alerts 4.1. Setting up alerts For internal Mode clusters, various alerts related to the storage metrics services, storage cluster, disk devices, cluster health, cluster capacity, and so on are displayed in the Block and File, and the object dashboards. These alerts are not available for external Mode. Note It might take a few minutes for alerts to be shown in the alert panel, because only firing alerts are visible in this panel. You can also view alerts with additional details and customize the display of Alerts in the OpenShift Container Platform. For more information, see Managing alerts .

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6.5. Role-Based Credential Map Identity Login Module Warning RoleBasedCredentialMap is now deprecated. In some cases, access to data sources is defined by roles, and users are assigned these roles, taking on the privileges that come with having them. JBoss Data Virtualization provides a login module called RoleBasedCredentialMap for this purpose. An administrator can define a role-based authentication module where, given the role of the user from the primary login module, this module will hold a credential for that role. Each role is associated with a set of credentials. If a user has multiple roles, the first role that has the required credential will be used.

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2.5. XA Transactions If the requesting application can participate in XA transactions, then your Connection object must override the getXAResource() method and provide the XAResource object for the application. To participate in crash recovery you must also extend the BasicResourceAdapter class and implement the public XAResource[] getXAResources(ActivationSpec[] specs) method. Red Hat JBoss Data Virtualization can make XA-capable resource adapters participate in distributed transactions. If they are not XA-capable, the datasource can participate in distributed queries but not distributed transactions. Transaction semantics are determined by how you configured "connection-factory" in a "resource-adapter" (that is, jta=true/false).

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19.2. Configuring Near Caches Near caching can be enabled and disabled via configuration without making any changes to the Hot Rod Client application. To enable near caching, configure the near caching mode (Eager or Lazy) on the client and optionally specify the number of entries to be kept in the cache. Near cache mode is configured using the NearCacheMode enumeration. The following example demonstrates how to configure Lazy near cache mode. Example 19.1. Configuring Lazy Near Cache Mode The following example demonstrates how to configure Eager near cache mode. Example 19.2. Configuring Eager Near Cache Mode Note Near cache size is unlimited by default but it can be changed to set a maximum size in terms of number of entries for the near cache. When the maximum size is reached, near cached entries are evicted using a least-recently-used (LRU) algorithm. Example 19.3. Configuring Near Cache Maximum Size Here, 100 is the maximum number of entries to keep in the near cache. Note This configuration also results in a disabled near cache mode when no mode is specified. 23155%2C+Developer+Guide-6.630-06-2017+15%3A00%3A55JBoss+Data+Grid+6Documentation6.6.1 Report a bug

Commands:
import org.infinispan.client.hotrod.configuration.ConfigurationBuilder; import org.infinispan.client.hotrod.configuration.NearCacheMode; ... ConfigurationBuilder lazy = new ConfigurationBuilder(); lazy.nearCache().mode(NearCacheMode.LAZY).maxEntries(10);
import org.infinispan.client.hotrod.configuration.ConfigurationBuilder; import org.infinispan.client.hotrod.configuration.NearCacheMode; ConfigurationBuilder eager = new ConfigurationBuilder(); eager.nearCache().mode(NearCacheMode.EAGER)..maxEntries(10);
import org.infinispan.client.hotrod.configuration.ConfigurationBuilder; ConfigurationBuilder builder = new ConfigurationBuilder(); builder.nearCache().maxEntries(100);
Chapter 7. Users and Permissions Table 7.1. Users and Permissions Subcommand Description and tasks user org Create a user: Add a role to a user: user-group Create a user group: Add a role to a user group: role Create a role: filter Create a filter and add it to a role:

Commands:
hammer user create --login user_name --mail user_mail --auth-source-id 1 --organization-ids org_ID1,org_ID2,
hammer user add-role --id user_id --role role_name
hammer user-group create --name ug_name
hammer user-group add-role --id ug_id --role role_name
hammer role create --name role_name
hammer filter create --role role_name --permission-ids perm_ID1,perm_ID2,