mtpti5iD/redhat-docs_dataset huggingface dataset:
Chapter 4. Installing the JBoss Data Virtualization Development Tools 4.1. Installing JBoss Data Virtualization Development Tools Prerequisites The following software must be installed: Red Hat Developer Studio 12.0 with Integration Stack. On the Red Hat Customer Portal , click Downloads Red Hat JBoss Data Virtualization and download Red Hat Developer Studio Integration Stack 12.0.0 Stand-alone Installer . Important Make sure you use Red Hat Developer Studio 12.0.0 as it is the last version that works with Teiid Designer. Important During installation, make sure you select Red Hat Data Virtualization Development on the Select Additional Features to Install screen. An archiving tool for extracting the contents of compressed files. Open JDK (or another supported Java Virtual Machine). Procedure 4.1. Install the Latest Version of Teiid Designer Go to https://access.redhat.com/ and log in to the Customer Portal with your Red Hat login. Click Downloads Red Hat JBoss Data Virtualization . Click Download to the Red Hat JBoss Data Virtualization Teiid Designer [VERSION] Update Site Zip option and save the datavirt-teiid-designer-[VERSION]-updatesite.zip file. Start Red Hat Developer Studio . In Red Hat Developer Studio , select Help Install New Software... from the main menu. On the Available Software page, click the Add ... button. On the Add Repository dialog: Enter "Red Hat Data Virtualization Teiid Designer" (or another unique name) in the Name field. Click the Archive... button, navigate to the location where the datavirt-teiid-designer-[VERSION]-updatesite.zip file was downloaded, and click OK . Click Add . Back on the Available Software page, select Data Virtualization and all of its children from the list of available items. Click . On the Install Details page, review the items to be installed and click . Accept any additional dependencies and license agreements, then click Finish .

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5.21. c-ares 5.21.1. RHBA-2012:0922 - c-ares bug fix update Updated c-ares packages that fix several bugs are now available for Red Hat Enterprise Linux 6. The c-ares C library defines asynchronous DNS (Domain Name System) requests and provides name resolving API. Bug Fixes BZ# 730695 Previously, when searching for AF_UNSPEC or AF_INET6 address families, the c-ares library fell back to the AF_INET family if no AF_INET6 addresses were found. Consequently, IPv4 addresses were returned even if only IPv6 addresses were requested. With this update, c-ares performs the fallback only when searching for AF_UNSPEC addresses. BZ# 730693 The ares_parse_a_reply() function leaked memory when the user attempted to parse an invalid reply. With this update, the allocated memory is freed properly and the memory leak no longer occurs. BZ# 713133 A switch statement inside the ares_malloc_data() public function was missing a terminating break statement. This could result in unpredictable behavior and sometimes the application terminated unexpectedly. This update adds the missing switch statement and the ares_malloc_data() function now works as intended. BZ# 695426 When parsing SeRVice (SRV) record queries, c-ares was accessing memory incorrectly on architectures that require data to be aligned in memory. This caused the program to terminate unexpectedly with the SIGBUS signal. With this update, c-ares has been modified to access the memory correctly in the scenario described. BZ# 640944 Previously, the ares_gethostbyname manual page did not document the ARES_ENODATA error code as a valid and expected error code. With this update, the manual page has been modified accordingly. All users of c-ares are advised to upgrade to these updated packages, which fix these bugs.

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2.4.3. The Root File System and GRUB The use of the term root file system has a different meaning in regard to GRUB. It is important to remember that GRUB's root file system has nothing to do with the Linux root file system. The GRUB root file system is the top level of the specified device. For example, the image file (hd0,0)/grub/splash.xpm.gz is located within the /grub/ directory at the top-level (or root) of the (hd0,0) partition (which is actually the /boot/ partition for the system). , the kernel command is executed with the location of the kernel file as an option. Once the Linux kernel boots, it sets up the root file system that Linux users are familiar with. The original GRUB root file system and its mounts are forgotten; they only existed to boot the kernel file. Refer to the root and kernel commands in Section 2.6, "GRUB Commands" for more information.

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22.6. The Engine Vacuum Tool 22.6.1. The Engine Vacuum Tool The Engine Vacuum tool maintains PostgreSQL databases by updating tables and removing dead rows, allowing disk space to be reused. See the PostgreSQL documentation for information about the VACUUM command and its parameters. The Engine Vacuum command is engine-vacuum . You must log in as the root user and provide the administration credentials for the Red Hat Virtualization environment. Alternatively, the Engine Vacuum tool can be run while using the engine-setup command to customize an existing installation: The Yes option runs the Engine Vacuum tool in full vacuum verbose mode. 22.6.2. Engine Vacuum Modes Engine Vacuum has two modes: Standard Vacuum Frequent standard vacuuming is recommended. Standard vacuum removes dead row versions in tables and indexes and marks the space as available for future reuse. Frequently updated tables should be vacuumed on a regular basis. However, standard vacuum does not return the space to the operating system. Standard vacuum, with no parameters, processes every table in the current database. Full Vacuum Full vacuum is not recommended for routine use, but should only be run when a significant amount of space needs to be reclaimed from within the table. Full vacuum compacts the tables by writing a new copy of the table file with no dead space, thereby enabling the operating system to reclaim the space. Full vacuum can take a long time. Full vacuum requires extra disk space for the new copy of the table, until the operation completes and the old copy is deleted. Because full vacuum requires an exclusive lock on the table, it cannot be run in parallel with other uses of the table. 22.6.3. Syntax for the engine-vacuum Command The basic syntax for the engine-vacuum command is: Running the engine-vacuum command with no options performs a standard vacuum. There are several parameters to further refine the engine-vacuum command. General Options -h --help Displays information on how to use the engine-vacuum command. -a Runs a standard vacuum, analyzes the database, and updates the optimizer statistics. -A Analyzes the database and updates the optimizer statistics, without vacuuming. -f Runs a full vacuum. -v Runs in verbose mode, providing more console output. -t table_name Vacuums a specific table or tables.

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engine-setup [ INFO ] Stage: Environment customization Perform full vacuum on the engine database engine@localhost? This operation may take a while depending on this setup health and the configuration of the db vacuum process. See https://www.postgresql.org/docs/10/static/sql-vacuum.html (Yes, No) [No]:
engine-vacuum
engine-vacuum option
engine-vacuum -f -v -t vm_dynamic -t vds_dynamic
3.3. ext4 3.3.1. Migration from ext3 Moving to ext4 must be done with a freshly formatted ext4 file system. Migrating in place from ext3 to ext4 is not supported and will not produce many of the benefits ext4 offers, since the data currently residing on the partition will not make use of the extents features and other changes. Red Hat recommends that customers who cannot migrate to a cleanly formatted ext4 file system remain on their existing ext3 file system.

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2.5.5. OProfile The OProfile system-wide profiler is a low-overhead monitoring tool. OProfile makes use of the processor's performance monitoring hardware [8] to determine the nature of performance-related problems. Performance monitoring hardware is part of the processor itself. It takes the form of a special counter, incremented each time a certain event (such as the processor not being idle or the requested data not being in cache) occurs. Some processors have more than one such counter and allow the selection of different event types for each counter. The counters can be loaded with an initial value and produce an interrupt whenever the counter overflows. By loading a counter with different initial values, it is possible to vary the rate at which interrupts are produced. In this way it is possible to control the sample rate and, therefore, the level of detail obtained from the data being collected. At one extreme, setting the counter so that it generates an overflow interrupt with every event provides extremely detailed performance data (but with massive overhead). At the other extreme, setting the counter so that it generates as few interrupts as possible provides only the most general overview of system performance (with practically no overhead). The secret to effective monitoring is the selection of a sample rate sufficiently high to capture the required data, but not so high as to overload the system with performance monitoring overhead. Warning You can configure OProfile so that it produces sufficient overhead to render the system unusable. Therefore, you must exercise care when selecting counter values. For this reason, the opcontrol command supports the --list-events option, which displays the event types available for the currently-installed processor, along with suggested minimum counter values for each. It is important to keep the tradeoff between sample rate and overhead in mind when using OProfile. 2.5.5.1. OProfile Components Oprofile consists of the following components: Data collection software Data analysis software Administrative interface software The data collection software consists of the oprofile.o kernel module, and the oprofiled daemon. The data analysis software includes the following programs: op_time Displays the number and relative percentages of samples taken for each executable file oprofpp Displays the number and relative percentage of samples taken by either function, individual instruction, or in gprof -style output op_to_source Displays annotated source code and/or assembly listings op_visualise Graphically displays collected data These programs make it possible to display the collected data in a variety of ways. The administrative interface software controls all aspects of data collection, from specifying which events are to be monitored to starting and stopping the collection itself. This is done using the opcontrol command. [8] OProfile can also use a fallback mechanism (known as TIMER_INT) for those system architectures that lack performance monitoring hardware.

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Chapter 21. KafkaAuthorizationSimple schema reference Used in: KafkaClusterSpec Full list of KafkaAuthorizationSimple schema properties Simple authorization in AMQ Streams uses the AclAuthorizer plugin, the default Access Control Lists (ACLs) authorization plugin provided with Apache Kafka. ACLs allow you to define which users have access to which resources at a granular level. Configure the Kafka custom resource to use simple authorization. Set the type property in the authorization section to the value simple , and configure a list of super users. Access rules are configured for the KafkaUser , as described in the ACLRule schema reference . 21.1. superUsers A list of user principals treated as super users, so that they are always allowed without querying ACL rules. An example of simple authorization configuration apiVersion: kafka.strimzi.io/v1beta2 kind: Kafka metadata: name: my-cluster namespace: myproject spec: kafka: # ... authorization: type: simple superUsers: - CN=client_1 - user_2 - CN=client_3 # ... Note The super.user configuration option in the config property in Kafka.spec.kafka is ignored. Designate super users in the authorization property instead. For more information, see Kafka broker configuration . 21.2. KafkaAuthorizationSimple schema properties The type property is a discriminator that distinguishes use of the KafkaAuthorizationSimple type from KafkaAuthorizationOpa , KafkaAuthorizationKeycloak , KafkaAuthorizationCustom . It must have the value simple for the type KafkaAuthorizationSimple . Property Description type Must be simple . string superUsers List of super users. Should contain list of user principals which should get unlimited access rights. string array

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apiVersion: kafka.strimzi.io/v1beta2 kind: Kafka metadata: name: my-cluster namespace: myproject spec: kafka: # authorization: type: simple superUsers: - CN=client_1 - user_2 - CN=client_3 #
Chapter 8. Message delivery 8.1. Sending messages To send a message, create a client, connection and a sender Example: Sending messages Connection connection = client.connect(serverHost, serverPort, options); SenderOptions senderOptions = new SenderOptions(); Sender sender = connection.openSender(address, senderOptions); Message<String> message = Message.create("Hello World!"); Tracker tracker = sender.send(message); For more information, see the Send.java example . 8.2. Tracking sent messages When the message is sent a Tracker is returned which can be used to track the message or settle it if not using auto settlement Example: waiting for the broker to settle the message tracker.awaitSettlement(); Example: settling the messsage tracker.settle(); 8.3. Receiving messages To receive a message, create a connection, client and receiver. Example: Receiving messages Connection connection = client.connect(serverHost, serverPort, options); Receiver receiver = connection.openReceiver(address); Delivery delivery = receiver.receive(); Message<object> received = delivery.message(); The Receiver.accept() call tells the remote peer that the message was received and processed. For more information, see the Receive.java example . 8.4. Acknowledging received messages The Delivery object can be used to accept, reject modify the delivery. Example: Acknowledging received messages ---- delivery.accept() ---- Example: Rejecting received messages ---- delivery.reject() ---- Example: Releasing received messages ---- delivery.Release() ----

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Connection connection = client.connect(serverHost, serverPort, options); SenderOptions senderOptions = new SenderOptions(); Sender sender = connection.openSender(address, senderOptions); Message<String> message = Message.create("Hello World!"); Tracker tracker = sender.send(message);
tracker.awaitSettlement();
tracker.settle();
Connection connection = client.connect(serverHost, serverPort, options); Receiver receiver = connection.openReceiver(address); Delivery delivery = receiver.receive(); Message<object> received = delivery.message();
---- delivery.accept() ----
---- delivery.reject() ----
---- delivery.Release() ----
3.3. RHEA-2011:1653 - new package: libunistring A new libunistring package is now available for Red Hat Enterprise Linux 6. This portable C library implements the UTF-8, UTF-16 and UTF-32 Unicode string types, together with functions for character processing (names, classifications, and properties) and functions for string processing (iteration, formatted output, width, word breaks, line breaks, normalization, case folding, and regular expressions). This enhancement update adds the libunistring package to Red Hat Enterprise Linux 6. The libunistring package has been added as a dependency for the System Security Services Daemon (SSSD) in order to process internationalized HBAC rules on FreeIPA servers. (BZ# 726463 ) All users who require libunistring should install this new package.

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Chapter 48. Using the standalone library perspective You can use the library perspective of Business Central to select a project you want to edit. You can also perform all the authoring functions on the selected project. The standalone library perspective can be used in two ways, with and without using the header=UberfireBreadcrumbsContainer parameter. The difference is that the address with the header parameter will display a breadcrumb trail on top of the library perspective. Using this link you can create additional Spaces for your projects. Procedure Log in to Business Central. In a web browser, enter the appropriate web address: For accessing the standalone library perspective without the header parameter http://localhost:8080/business-central/kie-wb.jsp?standalone=true&perspective=LibraryPerspective The standalone library perspective without the breadcrumb trail opens in the browser. For accessing the standalone library perspective with the header parameter http://localhost:8080/business-central/kie-wb.jsp?standalone=true&perspective=LibraryPerspective&header=UberfireBreadcrumbsContainer The standalone library perspective with the breadcrumb trail opens in the browser.

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Chapter 4. Executing tasks using Red Hat Insights You can execute tasks on remote systems in the Red Hat Hybrid Cloud Console directly from Red Hat Insights Tasks. Tasks you can execute are: RHEL pre-upgrade analysis utility tasks. Pre-conversion analysis utility tasks. Convert to RHEL from CentOS Linux 7. Note Prerequisites and actions required to execute specific Insights tasks will vary. Here are general instructions to execute a task. Prerequisites You are logged in to the Red Hat Hybrid Cloud Console. You are a member of a User Access group with the Tasks administrator role. You have connected systems and addressed dependencies for Remote Host Configuration (rhc), rhc-worker-playbook and ansible-core , as needed. See You have addressed dependencies for Satellite 6.11+. Services in the Insights Automation Toolkit have similar dependency requirements that must be met before Red Hat Insights users can execute playbooks for remediations and tasks. Procedure Navigate to Automation Toolkit > Tasks . Select a task to execute and click Run Task . Optional: Edit the default task name to customize it for your needs. Note After you execute the task, you will not be able to change the task name again. Make note of any task-specific prerequisites shown in the brief description of the task. Select the systems on which to execute the task. You can use filters to search and filter systems by: Name Operating System Tag Click Execute task . The task executes on the selected systems. You might see a pop-up that shows that your task is running. Click View Progress to view the task details page which shows how the task is executing on each of your selected systems. Review Status and Message details. If shown, click the Show more icon beside the system name to find more information about messages. Click Tasks to go to the task detail view to see more information about how the task executed on the selected systems. Click the Activity tab to see the status of all the task you have executed. Tasks are in chronological order, by the most recent date and time. Note A Completed status indicates that the task executed, but does not indicate that the task accomplished its goal. Optional: Click the task you executed to return to the task detail view to see more information about how the task executed on the selected systems. Steps You might need to resolve errors, such as an error that occurs because you need to install a software package on your systems before a task can successfully execute. After you resolve those errors, you can execute the task again on the same systems. Optional: To execute a task again, click Run Task again. The previously selected systems are still selected, and you can also add additional systems, if needed.

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1.3.7. Updating a Working Copy To update a working copy and get the latest changes from a CVS repository, change to the directory with the working copy and run the following command: cvs update Example 1.23. Updating a working copy Imagine that the directory with your working copy of a CVS repository has the following contents: Also imagine that somebody recently added ChangeLog to the repository, removed the TODO file from it, and made some changes to Makefile . To update this working copy, type:

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project]USD ls AUTHORS CVS doc INSTALL LICENSE Makefile README src TODO
myproject]USD cvs update cvs update: Updating . U ChangeLog U Makefile cvs update: TODO is no longer in the repository cvs update: Updating doc cvs update: Updating src
Chapter 71. Running the test scenarios After creating a test scenario template and defining the test scenarios, you can run the tests to validate your business rules and data. Procedure To run defined test scenarios, do any of the following tasks: To execute all the available test scenarios in your project inside multiple assets, in the upper-right corner of your project page, click Test . Figure 71.1. Run all the test scenarios from the project view To execute all available test scenarios defined in a .scesim file, at the top of the Test Scenario designer, click the Run Test icon. To run a single test scenario defined in a single .scesim file, right-click the row of the test scenario you want to run and select Run scenario . The Test Report panel displays the overview of the tests and the scenario status. After the tests execute, if the values entered in the test scenario table do not match with the expected values, then the corresponding cells are highlighted. If tests fail, you can do the following tasks to troubleshoot the failure: To review the error message in the pop-up window, hover your mouse cursor over the highlighted cell. To open the Alerts panel at the bottom of the designer or the project view for the error messages, click View Alerts . Make the necessary changes and run the test again until the scenario passes.

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Chapter 1. Use Case Considerations Because Amazon Web Services is an image-only service, there are common Satellite use cases that do not work, or require extra configuration in an Amazon Web Service environment. If you plan to use Satellite on AWS, ensure that the use case scenarios that you want to use are available in an AWS environment. 1.1. Use Cases Known to Work You can perform the following Red Hat Satellite use cases on AWS: Managing Red Hat Subscriptions Importing Content Managing Errata Registering a Host Manually Red Hat Insights Realm Integration via IdM OpenSCAP Remote Execution Subscriptions Not all Red Hat subscriptions are eligible to run in public cloud environments. For more information about subscription eligibility, see the Red Hat Cloud Access Page . You can create additional organizations and then import additional manifests to the organizations. For more information, see Creating an Organization in Administering Red Hat Satellite . Multi-homed Satellite and Capsule Multi-homed Satellite is not supported. Multi-homed Capsule is supported, to implement this, you can configure Capsules with a load balancer. For more information, see Configuring Capsules with a Load Balancer . You must do this when Satellite Server or Capsule Server has different internal and external DNS host names and there is no site-to-site VPN connection between the locations where you deploy Satellite Server and Capsule Server. On demand content sources You can use the On demand download policy to reduce the storage footprint of the server that runs Satellite. When you set the download policy to On Demand , content syncs to Satellite Server or Capsule Server when a content host requests it. For more information, see Importing Content in Managing content . 1.2. Use Cases that Do Not Work In AWS, you cannot manage the DHCP. Because of this, most of Satellite Server's kickstart and PXE provisioning models are unusable. This includes: PXE Provisioning Discovery and Discovery Rules ISO Provisioning methods. PXE-Less Discovery (iPXE) Per-host ISO Generic ISO Full-host ISO

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