mtpti5iD/redhat-docs_dataset huggingface dataset:
B.73. postgresql B.73.1. RHSA-2010:0908 - Moderate: postgresql security update Updated postgresql packages that fix one security issue are now available for Red Hat Enterprise Linux 6. The Red Hat Security Response Team has rated this update as having moderate security impact. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) associated with each description below. PostgreSQL is an advanced object-relational database management system (DBMS). PL/Perl and PL/Tcl allow users to write PostgreSQL functions in the Perl and Tcl languages. The PostgreSQL SECURITY DEFINER parameter, which can be used when creating a new PostgreSQL function, specifies that the function will be executed with the privileges of the user that created it. CVE-2010-3433 It was discovered that a user could utilize the features of the PL/Perl and PL/Tcl languages to modify the behavior of a SECURITY DEFINER function created by a different user. If the PL/Perl or PL/Tcl language was used to implement a SECURITY DEFINER function, an authenticated database user could use a PL/Perl or PL/Tcl script to modify the behavior of that function during subsequent calls in the same session. This would result in the modified or injected code also being executed with the privileges of the user who created the SECURITY DEFINER function, possibly leading to privilege escalation. These updated postgresql packages upgrade PostgreSQL to version 8.4.5. Refer to the PostgreSQL Release Notes for a list of changes: http://www.postgresql.org/docs/8.4/static/release.html All PostgreSQL users are advised to upgrade to these updated packages, which correct this issue. If the postgresql service is running, it will be automatically restarted after installing this update.

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Chapter 2. Multicluster storage health To view the overall storage health status across all the clusters with OpenShift Data Foundation and manage its capacity, you must first enable the multicluster dashboard on the Hub cluster. 2.1. Enabling multicluster dashboard on Hub cluster You can enable the multicluster dashboard on the install screen either before or after installing ODF Multicluster Orchestrator with the console plugin. Prerequisites Ensure that you have installed OpenShift Container Platform version 4.15 and have administrator privileges. Ensure that you have installed Multicluster Orchestrator 4.15 operator with plugin for console enabled. Ensure that you have installed Red Hat Advanced Cluster Management for Kubernetes (RHACM) 2.10 from Operator Hub. For instructions on how to install, see Installing RHACM . Ensure you have enabled observability on RHACM. See Enabling observability guidelines . Procedure Create the configmap file named observability-metrics-custom-allowlist.yaml and add the name of the custom metric to the metrics_list.yaml parameter. You can use the following YAML to list the OpenShift Data Foundation metrics on Hub cluster. For details, see Adding custom metrics . Run the following command in the open-cluster-management-observability namespace: After observability-metrics-custom-allowlist yaml is created, RHACM will start collecting the listed OpenShift Data Foundation metrics from all the managed clusters. If you want to exclude specific managed clusters from collecting the observability data, add the following cluster label to your clusters: observability: disabled . To view the multicluster health, see chapter verifying multicluster storage dashboard . 2.2. Verifying multicluster storage health on hub cluster Prerequisites Ensure that you have enabled multicluster monitoring. For instructions, see chapter Enabling multicluster dashboard . Procedure In the OpenShift web console of Hub cluster, ensure All Clusters is selected. Navigate to Data Services and click Storage System . On the Overview tab, verify that there are green ticks in front of OpenShift Data Foundation and Systems . This indicates that the operator is running and all storage systems are available. In the Status card, Click OpenShift Data Foundation to view the operator status. Click Systems to view the storage system status. The Storage system capacity card shows the following details: Name of the storage system Cluster name Graphical representation of total and used capacity in percentage Actual values for total and used capacity in TiB

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kind: ConfigMap apiVersion: v1 metadata: name: observability-metrics-custom-allowlist Namespace: open-cluster-management-observability data: metrics_list.yaml: | names: - odf_system_health_status - odf_system_map - odf_system_raw_capacity_total_bytes - odf_system_raw_capacity_used_bytes matches: - __name__="csv_succeeded",exported_namespace="openshift-storage",name=~"odf-operator.*"
oc apply -n open-cluster-management-observability -f observability-metrics-custom-allowlist.yaml
7.7. Synchronous and Asynchronous Distribution To elicit meaningful return values from certain public API methods, it is essential to use synchronized communication when using distribution mode. Example 7.1. Communication Mode example For example, with three nodes in a cluster, node A , B and C , and a key K that maps nodes A and B . Perform an operation on node C that requires a return value, for example Cache.remove(K) . To execute successfully, the operation must first synchronously forward the call to both node A and B , and then wait for a result returned from either node A or B . If asynchronous communication was used, the usefulness of the returned values cannot be guaranteed, despite the operation behaving as expected. 23149%2C+Administration+and+Configuration+Guide-6.628-06-2017+13%3A51%3A02JBoss+Data+Grid+6Documentation6.6.1 Report a bug

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Chapter 38. Unregistering from Red Hat Subscription Management Services A system can only be registered with one subscription service. If you need to change which service your system is registered with or need to delete the registration in general, then the method to unregister depends on which type of subscription service the system was originally registered with. 38.1. Systems Registered with Red Hat Subscription Management Several different subscription services use the same, certificate-based framework to identify systems, installed products, and attached subscriptions. These services are Customer Portal Subscription Management (hosted), Subscription Asset Manager (on-premise subscription service), and CloudForms System Engine (on-premise subscription and content delivery services). These are all part of Red Hat Subscription Management . For all services within Red Hat Subscription Management, the systems are managed with the Red Hat Subscription Manager client tools. To unregister a system registered with a Red Hat Subscription Management server, use the unregister command. Note This command must be run as root.

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subscription-manager unregister --username=name
Appendix A. Revision History Revision History Revision 2-7.400 2013-10-31 Rudiger Landmann Rebuild with publican 4.0.0 Revision 2-7 2012-07-18 Anthony Towns Rebuild for Publican 3.0 Revision 1.0-0 Tue Sep 23 2008 Don Domingo migrated to new automated build system

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Chapter 3. Extensions to JDBC 3.1. Prepared Statements JBoss Data Virtualization provides org.teiid.jdbc.TeiidPreparedStatement , a custom interface for the standard java.sql.PreparedStatement , and implementations org.teiid.jdbc.CallableStatementImpl and org.teiid.jdbc.PreparedStatementImpl . Prepared statements can be important in speeding up common statement execution, since they allow the server to skip parsing, resolving, and planning of the statement. The following points should be considered when using prepared statements: It is not necessary to pool client-side JBoss Data Virtualization prepared statements, because JBoss Data Virtualization performs plan caching on the server side. The number of cached plans is configurable. The plans are purged in order of least recently used (LRU). Cached plans are not distributed through a cluster. A new plan must be created for each cluster member. Plans are cached for the entire VDB or for just a particular session. The scope of a plan is detected automatically based upon the functions evaluated during its planning process. Runtime updates of costing information do not yet cause re-planning. At this time only session-scoped temporary table or internally materialized tables update their costing information. Stored procedures executed through a callable statement have their plans cached in the same way as a prepared statement. Bind variable types in function signatures, for example where t.col = abs(?) , can be determined if the function has only one signature or if the function is used in a predicate where the return type can be determined. In more complex situations it may be necessary to add a type hint with a cast or convert, for example upper(convert(?, string)) .

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8.102. kdesdk 8.102.1. RHBA-2014:0485 - kdesdk bug fix update Updated kdesdk packages that fix two bugs are now available for Red Hat Enterprise Linux 6. The kdesdk packages contain the KDE Software Development Kit (SDK) which is a collection of applications and tools used by developers. These applications and tools include - cervisia: a CVS frontend; kate: an advanced text editor; kbugbuster: a tool to manage the KDE bug report system; kcachegrind: a browser for data produced by profiling tools (for example cachegrind); kompare: a diff tool; kuiviewer: a tool for displaying a designer's UI files; lokalize: a computer-aided translation system focusing on productivity and performance; and umbrello: a UML modeller and UML diagram tool. Bug Fixes BZ# 857002 Previously, the umbrello UML modeller used logic based on recursive calls. As a consequence if a user created a diagram that had dependency graph cycles, umbrello entered an infinite loop and terminated unexpectedly with a segmentation fault. With this update, the application logic has been changed to use stack-based parent resolution. As a result, umbrello no longer terminates in the described scenario. BZ# 908709 Prior to this update, the kompare utility hid underscore characters located at the bottom of a highlighted difference block when using certain fonts. This update fixes this bug. As a result, kompare correctly displays underscore characters in the described situation. Users of kdesdk are advised to upgrade to these updated packages, which fix these bugs.

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18.8. Date & Time To configure time zone, date, and optionally settings for network time, select Date & Time at the Installation Summary screen. There are three ways for you to select a time zone: Using your mouse, click on the interactive map to select a specific city. A red pin appears indicating your selection. You can also scroll through the Region and City drop-down menus at the top of the screen to select your time zone. Select Etc at the bottom of the Region drop-down menu, then select your time zone in the menu adjusted to GMT/UTC, for example GMT+1 . If your city is not available on the map or in the drop-down menu, select the nearest major city in the same time zone. Alternatively you can use a Kickstart file, which will allow you to specify some additional time zones which are not available in the graphical interface. See the timezone command in timezone (required) for details. Note The list of available cities and regions comes from the Time Zone Database (tzdata) public domain, which is maintained by the Internet Assigned Numbers Authority (IANA). Red Hat cannot add cities or regions into this database. You can find more information at the official website, available at http://www.iana.org/time-zones . Specify a time zone even if you plan to use NTP (Network Time Protocol) to maintain the accuracy of the system clock. If you are connected to the network, the Network Time switch will be enabled. To set the date and time using NTP, leave the Network Time switch in the ON position and click the configuration icon to select which NTP servers Red Hat Enterprise Linux should use. To set the date and time manually, move the switch to the OFF position. The system clock should use your time zone selection to display the correct date and time at the bottom of the screen. If they are still incorrect, adjust them manually. Note that NTP servers might be unavailable at the time of installation. In such a case, enabling them will not set the time automatically. When the servers become available, the date and time will update. Once you have made your selection, click Done to return to the Installation Summary screen. Note To change your time zone configuration after you have completed the installation, visit the Date & Time section of the Settings dialog window.

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Chapter 10. Planning for Installation on IBM Power Systems This chapter outlines the decisions and preparations you will need to make when deciding how to proceed with the installation. 10.1. Upgrade or Install? While automated in-place upgrades are now supported, the support is currently limited to AMD64 and Intel 64 systems. If you have an existing installation of a release of Red Hat Enterprise Linux on an IBM Power Systems server, you must perform a clean install to migrate to Red Hat Enterprise Linux 7. A clean install is performed by backing up all data from the system, formatting disk partitions, performing an installation of Red Hat Enterprise Linux from installation media, and then restoring any user data.

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12.2. Installing from a Different Source You can install Red Hat Enterprise Linux from the ISO images stored on hard disk, or from a network using NFS, FTP, HTTP, or HTTPS methods. Experienced users frequently use one of these methods because it is often faster to read data from a hard disk or network server than from a DVD. The following table summarizes the different boot methods and recommended installation methods to use with each: Table 12.1. Boot Methods and Installation Sources Boot method Installation source Full installation media (DVD) The boot media itself Minimal boot media (CD or DVD) Full installation DVD ISO image or the installation tree extracted from this image, placed in a network location or on a hard drive Network boot Full installation DVD ISO image or the installation tree extracted from this image, placed in a network location

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7.118. libqb 7.118.1. RHBA-2013:0323 - libqb bug fix and enhancement update Updated libqb packages that fix several bugs and add various enhancements are now available for Red Hat Enterprise Linux 6. The libqb packages provide a library with the primary purpose of providing high performance client server reusable features, such as high performance logging, tracing, inter-process communication, and polling. Note The libqb packages have been upgraded to upstream version 0.14.2, which provides a number of bug fixes and enhancements over the version. (BZ#845275) Bug Fix BZ# 869446 Previously, a timeout argument given to the qb_ipcc_recv() API function was not passed to poll() while waiting for a reply. Consequently, this function could consume nearly 100% CPU resources and affect the pacemaker utility. This bug has been fixed by passing the timeout value to poll() in qb_ipcc_recv(). As a result, the timeout period is honored as expected and pacemaker works correctly in such a case. All libqb users are advised to upgrade to these updated packages, which fix these bugs and add these enhancements. 7.118.2. RHBA-2013:1431 - libqb bug fix and enhancement update Updated libqb packages that fix several bugs and add various enhancements are now available for Red Hat Enterprise Linux 6. The libqb packages provide a library with the primary purpose of providing high performance client server reusable features, such as high performance logging, tracing, inter-process communication, and polling. Note The libqb packages have been upgraded to upstream version 0.16.0, which provides a number of bug fixes and enhancements over the version. One of the notable changes fixes a bug in the qb_log_from_external_source() function, that caused the Pacemaker's policy engine to terminate unexpectedly. The engine now works as expected. (BZ# 1001491 ) Users of libqb are advised to upgrade to these updated packages, which fix these bugs and add these enhancements.

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22.5. Basic Example: Performing a Recovery An administrator, John Smith, has to create a disaster recovery plan for his directory deployment. Example Corp. has three physical offices, in San Francisco, Dallas, and Arlington. Each site has 10 servers which replicate to each other locally, and then one server at each site replicates to another server at the other two sites. Each site has business-critical customer data stored in its directory, as well as human resources data. Several external applications require access to the data to perform operations like billing. John Smith's first step is to perform a site survey. He is looking for three things: what his directory usage is (clients that access it and traffic loads across the sites), what his current assets are, and what assets he may need to acquire. This is much like the initial site survey he performed when deploying Red Hat Directory Server. His step is identifying potential disaster scenarios. Two of the three sites are highly vulnerable to natural disasters (San Francisco and Dallas). All three sites could face normal interruptions, like outages for power or Internet access. Additionally, since each site suppliers its own local data, each site is vulnerable to losing a server instance or machine. John Smith then breaks his disaster recovery plan into three parts: Plan A covers losing a single instance of Directory Server Plan B covers some kind of data corruption or attack Plan C covers losing an entire office For plans A and B, John Smith decides to use a hot recovery to immediately switch functionality from a single instance to the backup. Each server is backed up daily, using a cron job, and then the archive is copied over and restored on a virtual machine. The virtual machine is kept on a different subnet, but can be switched over immediately if its peer ever does offline. John Smith uses simple SNMP traps to track each Directory Server instance's availability. Plan C is more extensive. Along with replication between sites and the local backups, he decides to mail a physical copy of each site's backup, for every local instance, once a week to the other two colocation facilities. He also keep a spare server with adequate Internet access and software licenses to restore an entire site, using virtual machines, one of the other different colocation facilities. He designates the Arlington site as the primary recovery location because that is where most of the IT staff is located, then San Francisco and last Dallas, based on the distribution of personnel. For every event, the IT administrator at all three sites will be notified, and the manager assumes the responsibilities of setting up the virtual machines, restoring the Directory Server instances from the physical backups, and rerouting client traffic. John Smith schedules to review and update the plan quarterly to account for any new hardware or application changes. Once a year, all three sites have to run through the procedure of recovering and deploying the other two sites, according to the procedures in Disaster Plan C.

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5.89. gnome-packagekit 5.89.1. RHBA-2012:1229 - gnome-packagekit bug fix update Updated gnome-packagekit packages that fix a bug are now available for Red Hat Enterprise Linux 6. The gnome-packagekit packages provide session applications for the PackageKit API. Bug Fix BZ# 839197 Previously, it was possible for the user to log out of the system or shut it down while the PackageKit update tool was running and writing to the RPM database (rpmdb). Consequently, rpmdb could become damaged and inconsistent due to the unexpected termination and cause various problems with subsequent operation of the rpm, yum, and PackageKit utilities. This update modifies PackageKit to not allow shutting down the system when a transaction writing to rpmdb is active, thus fixing this bug. Users of gnome-packagekit are advised to upgrade to these updated packages, which fix this bug.

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Chapter 5. Enhancements Streams for Apache Kafka 2.9 adds a number of enhancements. 5.1. Streams for Apache Kafka 5.1.1. Kafka 3.9.0 enhancements For an overview of the enhancements introduced with Kafka 3.9.0, refer to the Kafka 3.9.0 Release Notes. 5.1.2. Configuration mechanism for quotas management The Strimzi Quotas plugin moves to GA (General Availability). Use the plugin properties to set throughput and storage limits on brokers in your Kafka cluster configuration. Warning If you have previously used the Strimzi Quotas plugin in releases prior to Streams for Apache Kafka 2.8, update your Kafka cluster configuration to use the latest properties to avoid reconciliation issues when upgrading. For more information, see Setting limits on brokers using the Kafka Static Quota plugin .

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Chapter 26. Probe schema reference Used in: CruiseControlSpec , EntityTopicOperatorSpec , EntityUserOperatorSpec , KafkaBridgeSpec , KafkaClusterSpec , KafkaConnectSpec , KafkaExporterSpec , KafkaMirrorMaker2Spec , KafkaMirrorMakerSpec , TlsSidecar , ZookeeperClusterSpec Property Description failureThreshold Minimum consecutive failures for the probe to be considered failed after having succeeded. Defaults to 3. Minimum value is 1. integer initialDelaySeconds The initial delay before first the health is first checked. Default to 15 seconds. Minimum value is 0. integer periodSeconds How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. integer successThreshold Minimum consecutive successes for the probe to be considered successful after having failed. Defaults to 1. Must be 1 for liveness. Minimum value is 1. integer timeoutSeconds The timeout for each attempted health check. Default to 5 seconds. Minimum value is 1. integer

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Deploying OpenShift Data Foundation using Red Hat OpenShift Service on AWS with hosted control planes Red Hat OpenShift Data Foundation 4.17 Instructions for deploying OpenShift Data Foundation using Red Hat OpenShift Service on AWS (ROSA) with hosted control planes (HCP) Red Hat Storage Documentation Team Abstract Read this document for instructions about how to install Red Hat OpenShift Data Foundation using Red Hat OpenShift Container Platform on ROSA with hosted control planes (HCP).

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