mtpti5iD/redhat-docs_dataset huggingface dataset:
Chapter 9. Clustering Support for IBM iPDU Fence Device Red Hat Enterprise Linux 6.4 adds support for the IBM iPDU fence device. For more information on the parameters of this fence device, refer to the Fence Device Parameters appendix in the Red Hat Enterprise Linux 6 Cluster Administration guide. Support for Eaton Network Power Controller Fence Device Red Hat Enterprise Linux 6.4 adds support for fence_eaton_snmp , the fence agent for the Eaton over SNMP network power switch. For more information on the parameters of this fence agent, refer to the Fence Device Parameters appendix in the Red Hat Enterprise Linux 6 Cluster Administration guide. New keepalived Package Red Hat Enterprise Linux 6.4 includes the keepalived package as a Technology Preview. The keepalived package provides simple and robust facilities for load-balancing and high-availability. The load-balancing framework relies on the well-known and widely used Linux Virtual Server kernel module providing Layer 4 network load-balancing. The keepalived daemon implements a set of health checkers for load-balanced server pools according to their state. The keepalived daemon also implements the Virtual Router Redundancy Protocol (VRRP), allowing router or director failover to achieve high availability. Watchdog Recovery New fence_sanlock and checkquorum.wdmd fence agents, included in Red Hat Enterprise Linux 6.4 as a Technology Preview, provide new mechanisms to trigger the recovery of a node via a watchdog device. Tutorials on how to enable this Technology Preview will be available at https://fedorahosted.org/cluster/wiki/HomePage . Support for VMDK-based Storage Red Hat Enterprise Linux 6.4 adds support for clusters utilizing VMware's VMDK (Virtual Machine Disk) disk image technology with the multi-writer option. This allows you, for example, to use VMDK-based storage with the multi-writer option for clustered file systems such as GFS2.

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4.4. Storage and Filesystems The NFSv4 server in Red Hat Enterprise Linux 6 currently allows clients to mount using UDP and advertises NFSv4 over UDP with rpcbind. However, this configuration is not supported by Red Hat and violates the RFC 3530 standard. If a device-mapper-multipath device is still open, but all of the attached paths have been lost, the device is unable to create a new table with no paths. Consequently, the following unusual output may be returned from the multipath -ll output command: Output of this type indicates that there are no paths to the device. The erroneous lines in the output preceded by the string #:#:#:# will be removed in a future release. dracut currently only supports one FiberChannel over Ethernet (FCoE) connection to be used to boot from the root device. Consequently, booting from a root device that spans multiple FCoE devices (e.g. using RAID, LVM or similar techniques) is not possible. pvmove cannot currently be used to move mirror devices. However, it is possible to move mirror devices by issuing a sequence of two commands. For mirror images, add a new image on the destination PV and then remove the mirror image on the source PV. Mirror logs can be handled in a similar fashion:

Commands:
mpatha (3600a59a0000c2fd0003079284c122fec) dm-0, size=2.0G hwhandler='0' |-+- policy='round-robin 0' prio=0 status=enabled | `- #:#:#:# - #:# failed faulty running `-+- policy='round-robin 0' prio=0 status=enabled |- #:#:#:# - #:# failed faulty running `- #:#:#:# - #:# failed faulty running
USD> lvconvert -m +1 <vg/lv> <new PV> USD> lvconvert -m -1 <vg/lv> <old PV>
USD> lvconvert --mirrorlog core <vg/lv> USD> lvconvert --mirrorlog disk <vg/lv> <new PV>
or USD> lvconvert --mirrorlog mirrored <vg/lv> <new PV> USD> lvconvert --mirrorlog disk <vg/lv> <old PV>
Chapter 3. Configuring the OpenShift CLI Configure OpenShift CLI ( oc ) based on your preferences for working with it. 3.1. Enabling tab completion You can enable tab completion for the Bash or Zsh shells. 3.1.1. Enabling tab completion for Bash After you install the OpenShift CLI ( oc ), you can enable tab completion to automatically complete oc commands or suggest options when you press Tab. The following procedure enables tab completion for the Bash shell. Prerequisites You must have the OpenShift CLI ( oc ) installed. You must have the package bash-completion installed. Procedure Save the Bash completion code to a file: USD oc completion bash > oc_bash_completion Copy the file to /etc/bash_completion.d/ : USD sudo cp oc_bash_completion /etc/bash_completion.d/ You can also save the file to a local directory and source it from your .bashrc file instead. Tab completion is enabled when you open a new terminal. 3.1.2. Enabling tab completion for Zsh After you install the OpenShift CLI ( oc ), you can enable tab completion to automatically complete oc commands or suggest options when you press Tab. The following procedure enables tab completion for the Zsh shell. Prerequisites You must have the OpenShift CLI ( oc ) installed. Procedure To add tab completion for oc to your .zshrc file, run the following command: USD cat >>~/.zshrc<<EOF autoload -Uz compinit compinit if [ USDcommands[oc] ]; then source <(oc completion zsh) compdef _oc oc fi EOF Tab completion is enabled when you open a new terminal.

Commands:
oc completion bash > oc_bash_completion
sudo cp oc_bash_completion /etc/bash_completion.d/
cat >>~/.zshrc<<EOF autoload -Uz compinit compinit if [ USDcommands[oc] ]; then source <(oc completion zsh) compdef _oc oc fi EOF
7.177. perl-IPC-Run3 7.177.1. RHBA-2012:1440 - perl-IPC-Run3 bug fix update Updated perl-IPC-Run3 packages that fix two bugs are now available for Red Hat Enterprise Linux 6. The perl-IPC-Run3 packages provide a module to run subprocesses and redirect the stdin, stdout, and stderr functionalities to files and perl data structures. The perl-IPC-Run3 package allows to use system, qx, and open3 modules with a simple API. Bug Fix BZ# 657487 Prior to this update, binary perl-IPC-Run3 packages failed to build if the perl-Time-HiRes module was not installed. This update adds the perl-Time-HiRes package to the build-time dependencies for perl-IPC-Run3. BZ# 870089 Prior to this update, tests that called the IP-Run3 profiler failed when the internal perl-IPC-Run3 test suite was used. This update, adds run-time dependencies on perl(Getopt::Long) and perl(Time::HiRes) to the perl-IPC-Run3 package because certain IP-Run3 functions require the perl modules. Now, the IPC-Run3 profiler runs as expected. All users of perl-IPC-Run3 are advised to upgrade to these updated packages, which fix these bugs.

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Chapter 7. Rule Audit Rule audit allows the auditing of rules which have been triggered by all the rules that were activated at some point. The Rule Audit list view shows you a list of every time an event came in that matched a condition within a rulebook and triggered an action. The list shows you rules within your rulebook and each heading matches up to a rule that has been executed. 7.1. Viewing rule audit details From the Rule Audit list view you can check the event that triggered specific actions. Procedure From the navigation panel select Rule Audit . Select the desired rule, this brings you to the Details tab. From here you can view when it was created, when it was last fired, and the rulebook activation that it corresponds to. 7.2. Viewing rule audit events Procedure From the navigation panel select Rule Audit . Select the desired rule, this brings you to the Details tab. To view all the events that triggered an action, select the Events tab. This shows you the event that triggered actions. Select an event to view the Event log , along with the Source type and Timestamp . 7.3. Viewing rule audit actions Procedure From the navigation panel select Rule Audit . Select the desired rule, this brings you to the Actions tab. From here you can view executed actions that were taken. Some actions are linked out to automation controller where you can view the output.

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2.5.4. SELinux: Avoid SELinux on GFS2 Security Enhanced Linux (SELinux) is highly recommended for security reasons in most situations, but it is not supported for use with GFS2. SELinux stores information using extended attributes about every file system object, and SELinux labels on GFS2 file systems can get out of sync between cluster nodes because of how they are cached in memory. When mounting a GFS2 file system, you must ensure that SELinux will not attempt to read the seclabel element on each file system object by using one of the context options as described on the mount (8) man page; SELinux will assume that all content in the file system is labeled with the seclabel element provided in the context mount options. This will also speed up processing as it avoids another disk read of the extended attribute block that could contain seclabel elements. For example, on a system with SELinux in enforcing mode, you can use the following mount command to mount the GFS2 file system if the file system is going to contain Apache content. This label will apply to the entire file system; it remains in memory and is not written to disk. If you are not sure whether the file system will contain Apache content, you can use the labels public_content_rw_t or public_content_t , or you could define a new label altogether and define a policy around it. Note that in a Pacemaker cluster you should always use Pacemaker to manage a GFS2 file system. You can specify the mount options when you create a GFS2 file system resource, as described in Chapter 6, Configuring a GFS2 File System in a Pacemaker Cluster .

Commands:
mount -t gfs2 -o context=system_u:object_r:httpd_sys_content_t:s0 /dev/mapper/xyz/mnt/gfs2
mount -t gfs2 -o context=system_u:object_r:httpd_sys_content_t:s0 /dev/mapper/xyz/mnt/gfs2
9.4. Changing Passwords Password policies ( Chapter 19, Policy: Defining Password Policies ) and minimal access restrictions can be applied to a password change operation: Regular, non-administrative users can change only their personal passwords, and all passwords are constrained by the IdM password policies. This allows administrators to create intro passwords or to reset passwords easily, while still keeping the final password confidential. Since any password sent by an administrator to the user is temporary, there is little security risk. Changing a password as the IdM admin user overrides any IdM password policies, but the password expires immediately. This requires the user to change the password at the login. Similarly, any user who has password change rights can change a password and no password policies are applied, but the other user must reset the password at the login. Changing a password as the LDAP Directory Manager user, using LDAP tools , overrides any IdM password policies. 9.4.1. From the Web UI Open the Identity tab, and select the Users subtab. Click the name of the user for whom to reset the password. All users can change their own password; only administrators or users with delegated permissions can change other user's passwords. Scroll to the Account Settings area. Click the Reset Password link. In the pop-up box, enter and confirm the new password. 9.4.2. From the Command Line Changing a password - your own or another user's - is done using the user-mod command, as with other user account changes.

Commands:
[bjensen@ipaserver ~]USD kinit admin [bjensen@ipaserver ~]USD ipa user-mod jsmith --password
Chapter 4. Converting virtual machines to run on Red Hat Enterprise Virtualization Warning The Red Hat Enterprise Linux 6 version of the virt-v2v utility has been deprecated. Users of Red Hat Enterprise Linux 6 are advised to create a Red Hat Enterprise 7 virtual machine, and install virt-v2v in that virtual machine. The Red Hat Enterprise Linux 7 version is fully supported and documented in virt-v2v Knowledgebase articles . virt-v2v can convert virtual machines to run on Red Hat Enterprise Virtualization. Virtual machines can be converted from Xen, KVM and VMware ESX / ESX(i) environments. Before converting virtual machines to run on Red Hat Enterprise Virtualization, you must attach an export storage domain to the Red Hat Enterprise Virtualization data center being used. Section 4.2, "Attaching an export storage domain" explains the process of attaching an export storage domain. For more information on export storage domains, see the Red Hat Enterprise Virtualization Administration Guide . 4.1. Acceptable converted storage output formats It is important to note that when converting a guest virtual machine to run on Red Hat Enterprise Virtualization, not all combinations of storage format and allocation policy are supported. The supported combinations differ according to whether the Red Hat Enterprise Virtualization data center the guest will be imported into uses block (FC or iSCSI) or file (NFS) for its data storage domain. Note that virt-v2v writes to an export storage domain, and this is always required to be NFS. Note The important element for a successful virtual machine import into Red Hat Enterprise Virtualization is the type of the data domain. virt-v2v is unable to detect the data center type, so this check must be applied manually by the user. Table 4.1. Allocation Policy: Preallocated Data Domain Type Storage Format Supported NFS raw Yes qcow2 No FC/iSCSI raw Yes qcow2 No Table 4.2. Allocation Policy: Sparse Data Domain Type Storage Format Supported NFS raw Yes qcow2 Yes FC/iSCSI raw No qcow2 Yes Data format and allocation policy of the virtual machine being converted by virt-v2v will be preserved unless the output data format and allocation policy are specified using the -of and -oa parameters respectively. To import virtual machines using sparse allocation into an FC or iSCSI data center, the storage format must be converted to qcow2. This is achieved by passing the parameters -of qcow2 -oa sparse to virt-v2v . Note that converting between raw and qcow2 formats is a resource intensive operation, and roughly doubles the length of time taken for the conversion process. Important Preallocated qcow2 storage is never supported in Red Hat Enterprise Virtualization, although virt-v2v is able to write it. Import to Red Hat Enterprise Virtualization will fail.

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Chapter 349. Tika Component Available as of Camel version 2.19 The Tika : components provides the ability to detect and parse documents with Apache Tika. This component uses Apache Tika as underlying library to work with documents. In order to use the Tika component, Maven users will need to add the following dependency to their pom.xml : pom.xml <dependency> <groupId>org.apache.camel</groupId> <artifactId>camel-tika</artifactId> <version>x.x.x</version> <!-- use the same version as your Camel core version --> </dependency> The TIKA component only supports producer endpoints. 349.1. Options The Tika component has no options. The Tika endpoint is configured using URI syntax: with the following path and query parameters: 349.1.1. Path Parameters (1 parameters): Name Description Default Type operation Required Tika Operation. parse or detect TikaOperation 349.1.2. Query Parameters (5 parameters): Name Description Default Type tikaConfig (producer) Tika Config TikaConfig tikaConfigUri (producer) Tika Config Uri: The URI of tika-config.xml String tikaParseOutputEncoding (producer) Tika Parse Output Encoding - Used to specify the character encoding of the parsed output. Defaults to Charset.defaultCharset() . String tikaParseOutputFormat (producer) Tika Output Format. Supported output formats. xml: Returns Parsed Content as XML. html: Returns Parsed Content as HTML. text: Returns Parsed Content as Text. textMain: Uses the boilerpipe library to automatically extract the main content from a web page. xml TikaParseOutputFormat synchronous (advanced) Sets whether synchronous processing should be strictly used, or Camel is allowed to use asynchronous processing (if supported). false boolean 349.2. Spring Boot Auto-Configuration The component supports 2 options, which are listed below. Name Description Default Type camel.component.tika.enabled Enable tika component true Boolean camel.component.tika.resolve-property-placeholders Whether the component should resolve property placeholders on itself when starting. Only properties which are of String type can use property placeholders. true Boolean 349.3. To Detect a file's MIME Type The file should be placed in the Body. from("direct:start") .to("tika:detect"); 349.4. To Parse a File The file should be placed in the Body. from("direct:start") .to("tika:parse");

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<dependency> <groupId>org.apache.camel</groupId> <artifactId>camel-tika</artifactId> <version>x.x.x</version> <!-- use the same version as your Camel core version --> </dependency>
tika:operation
from("direct:start") .to("tika:detect");
from("direct:start") .to("tika:parse");
Chapter 2. Introduction to content creator workflows and automation execution environments 2.1. About content workflows Before Red Hat Ansible Automation Platform 2.0, an automation content developer may have needed so many Python virtual environments that they required their own automation in order to manage them. To reduce this level of complexity, Ansible Automation Platform 2.0 is moving away from virtual environments and using containers, referred to as automation execution environments, instead, as they are straightforward to build and manage and are more shareable across teams and orgs. As automation controller shifts to using automation execution environments, tools like automation content navigator and Ansible Builder ensure that you can take advantage of those automation execution environments locally within your own development system. Additional resources See the Automation Content Navigator Creator Guide for more on using automation content navigator. For more information on Ansible Builder, see Creating and Consuming Execution Environments . 2.2. Architecture overview The following list shows the arrangements and uses of tools available on Ansible Automation Platform 2.0, along with how they can be utilized: automation content navigator only - can be used today in Ansible Automation Platform 1.2 automation content navigator + downloaded automation execution environments - used directly on laptop/workstation automation content navigator + downloaded automation execution environments + automation controller - for pushing/executing locally remotely automation content navigator + automation controller + Ansible Builder + Layered custom EE - provides even more control over utilized content for how to execute automation jobs

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10. Kernel Kdump Auto Enablement Kdump is now enabled by default on systems with large amounts of memory. Specifically, kdump is enabled by default on: systems with more than 4GB of memory on architectures with a 4KB page size (i.e. x86 or x86_64), or systems with more than 8GB of memory on architectures with larger than a 4KB page size (i.e PPC64). On systems with less than the above memory configurations, kdump is not auto enabled. Refer to /usr/share/doc/kexec-tools-2.0.0/kexec-kdump-howto.txt for instructions on enabling kdump on these systems. crashkernel parameter syntax Please note that in future versions of Red Hat Enterprise Linux 6 (i.e. Red Hat Enterprise Linux 6.1 and later) the auto value setting of the crashkernel= parameter (i.e. crashkernel=auto ) will be deprecated. Barrier Implementation in the Kernel The barrier implementation in the Red Hat Enterprise Linux 6 kernel works by completely draining the I/O scheduler's queue, then issuing a preflush, a barrier, and finally a postflush request. However, since the supported file systems in Red Hat Enterprise Linux 6 all implement their own ordering guarantees, the block layer need only provide a mechanism to ensure that a barrier request is ordered with respect to other I/O already in the disk cache. This mechanism avoids I/O stalls experienced by queue draining. The block layer will be updated in future kernels to provide this more efficient mechanism of ensuring ordering. Workloads that include heavy fsync or metadata activity will see an overall improvement in disk performance. Users taking advantage of the proportional weight I/O controller will also see a boost in performance. In preparation for the block layer updates, third party file system developers need to ensure that data ordering surrounding journal commits are handled within the file system itself, since the block layer will no longer provide this functionality. These future block layer improvements will change some kernel interfaces such that symbols which are not on the kABI whitelist shall be modified. This may result in the need to recompile third party file system or storage drivers. Systemtap Tracepoints The following 3 virtual memory tracepoints are deprecated in Red Hat Enterprise Linux 6 trace_mm_background_writeout(unsigned long written) trace_mm_olddata_writeout(unsigned long written) trace_mm_balancedirty_writeout(unsigned long written) 10.1. Technology Previews Remote Audit Logging The audit package contains the user space utilities for storing and searching the audit records generated by the audit subsystem in the Linux 2.6 kernel. Within the audispd-plugins subpackage is a utility that allows for the transmission of audit events to a remote aggregating machine. This remote audit logging application, audisp-remote, is considered a Technology Preview in Red Hat Enterprise Linux 6. Linux (NameSpace) Container [LXC] Linux (NameSpace) Containers [LXC] is a Technology Preview feature in Red Hat Enterprise Linux 6 Beta that provides isolation of resources assigned to one or more processes. A process is assigned a separate user permission, networking, filesystem name space from its parent.

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C.2. Selection Criteria Operators Table C.2, "Selection Criteria Grouping Operators" describes the selection criteria grouping operators. Table C.2. Selection Criteria Grouping Operators Grouping Operator Description ( ) Used for grouping statements [ ] Used to group strings into a string list (exact match) { } Used to group strings into a string list (subset match) Table C.3, "Selection Criteria Comparison Operators" describes the selection criteria comparison operators and the field types with which they can be used. Table C.3. Selection Criteria Comparison Operators Comparison Operator Description Field Type =~ Matching regular expression regex !~ Not matching regular expression. regex = Equal to number, size, percent, string, string list, time != Not equal to number, size, percent, string, string list, time >= Greater than or equal to number, size, percent, time > Greater than number, size, percent, time <= Less than or equal to number, size, percent, time < Less than number, size, percent, time since Since specified time (same as >=) time after After specified time (same as >) time until Until specified time (same as <=) time before Before specified time (same as <) time Table C.4, "Selection Criteria Logical and Grouping Operators" describes the selection criteria logical and grouping operators. Table C.4. Selection Criteria Logical and Grouping Operators Logical and Grouping Operator Description && All fields must match , All fields must match (same as &&) || At least one field must match # At least one field must match (same as ||) ! Logical negation ( Left parenthesis (grouping operator) ) Right parenthesis (grouping operator) [ List start (grouping operator) ] List end (grouping operator) { List subset start (grouping operator) } List subset end (grouping operator)

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