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Merge pull request #71797 from aireilly/TELCODOCS-1731
TELCODOCS-1731 - Update low latency tuning docs
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_topic_maps/_topic_map.yml

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File: what-huge-pages-do-and-how-they-are-consumed-by-apps
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Distros: openshift-origin,openshift-enterprise
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- Name: Low latency tuning
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File: cnf-low-latency-tuning
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Dir: low_latency_tuning
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Distros: openshift-origin,openshift-enterprise
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- Name: Performing latency tests for platform verification
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File: cnf-performing-platform-verification-latency-tests
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Topics:
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- Name: Understanding low latency
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File: cnf-understanding-low-latency
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- Name: Tuning nodes for low latency with the performance profile
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File: cnf-tuning-low-latency-nodes-with-perf-profile
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- Name: Provisioning real-time and low latency workloads
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File: cnf-provisioning-low-latency-workloads
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- Name: Debugging low latency tuning
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File: cnf-debugging-low-latency-tuning-status
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- Name: Performing latency tests for platform verification
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File: cnf-performing-platform-verification-latency-tests
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- Name: Improving cluster stability in high latency environments using worker latency profiles
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File: scaling-worker-latency-profiles
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- Name: Creating a performance profile
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File: cnf-create-performance-profiles
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Distros: openshift-origin,openshift-enterprise
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- Name: Workload partitioning
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File: enabling-workload-partitioning

edge_computing/ztp-advanced-policy-config.adoc

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[role="_additional-resources"]
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.Additional resources
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* xref:../scalability_and_performance/cnf-low-latency-tuning.adoc#cnf-understanding-workload-hints_cnf-master[Understanding workload hints]
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* xref:../scalability_and_performance/cnf-low-latency-tuning.adoc#configuring-workload-hints_cnf-master[Configuring workload hints manually]
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* xref:../scalability_and_performance/low_latency_tuning/cnf-tuning-low-latency-nodes-with-perf-profile.adoc#configuring-workload-hints_cnf-low-latency-perf-profile[Configuring node power consumption and realtime processing with workload hints]
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include::modules/ztp-using-pgt-to-configure-performance-mode.adoc[leveloffset=+2]
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[role="_additional-resources"]
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.Additional resources
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* xref:../scalability_and_performance/cnf-low-latency-tuning.adoc#node-tuning-operator-pod-power-saving-config_cnf-master[Enabling critical workloads for power saving configurations]
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* xref:../scalability_and_performance/low_latency_tuning/cnf-tuning-low-latency-nodes-with-perf-profile.adoc#cnf-configuring-power-saving-for-nodes_cnf-low-latency-perf-profile[Configuring power saving for nodes that run colocated high and low priority workloads]
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* xref:../edge_computing/ztp-reference-cluster-configuration-for-vdu.adoc#ztp-du-configuring-host-firmware-requirements_sno-configure-for-vdu[Configuring host firmware for low latency and high performance]
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installing/installing-preparing.adoc

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[id="installing-preparing-cluster-for-workloads"]
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== Preparing your cluster for workloads
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Depending on your workload needs, you might need to take extra steps before you begin deploying applications. For example, after you prepare infrastructure to support your application xref:../cicd/builds/build-strategies.adoc#build-strategies[build strategy], you might need to make provisions for xref:../scalability_and_performance/cnf-low-latency-tuning.adoc#cnf-low-latency-tuning[low-latency] workloads or to xref:../nodes/pods/nodes-pods-secrets.adoc#nodes-pods-secrets[protect sensitive workloads]. You can also configure xref:../observability/monitoring/enabling-monitoring-for-user-defined-projects.adoc#enabling-monitoring-for-user-defined-projects[monitoring] for application workloads.
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Depending on your workload needs, you might need to take extra steps before you begin deploying applications. For example, after you prepare infrastructure to support your application xref:../cicd/builds/build-strategies.adoc#build-strategies[build strategy], you might need to make provisions for xref:../scalability_and_performance/low_latency_tuning/cnf-tuning-low-latency-nodes-with-perf-profile.adoc#cnf-low-latency-perf-profile[low-latency] workloads or to xref:../nodes/pods/nodes-pods-secrets.adoc#nodes-pods-secrets[protect sensitive workloads]. You can also configure xref:../observability/monitoring/enabling-monitoring-for-user-defined-projects.adoc#enabling-monitoring-for-user-defined-projects[monitoring] for application workloads.
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If you plan to run xref:../windows_containers/enabling-windows-container-workloads.adoc#enabling-windows-container-workloads[Windows workloads], you must enable xref:../networking/ovn_kubernetes_network_provider/configuring-hybrid-networking.adoc#configuring-hybrid-networking[hybrid networking with OVN-Kubernetes] during the installation process; hybrid networking cannot be enabled after your cluster is installed.
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[id="supported-installation-methods-for-different-platforms"]

installing/installing_openstack/installing-openstack-nfv-preparing.adoc

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* Consult the following references after you deploy your cluster to improve its performance:
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** xref:../../networking/hardware_networks/using-dpdk-and-rdma.adoc#nw-openstack-ovs-dpdk-testpmd-pod_using-dpdk-and-rdma[A test pod template for clusters that use OVS-DPDK on OpenStack].
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** xref:../../networking/hardware_networks/add-pod.adoc#nw-openstack-sr-iov-testpmd-pod_add-pod[A test pod template for clusters that use SR-IOV on OpenStack].
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** xref:../../scalability_and_performance/cnf-create-performance-profiles.adoc#installation-openstack-ovs-dpdk-performance-profile_cnf-create-performance-profiles[A performance profile template for clusters that use OVS-DPDK on OpenStack].
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** xref:../../scalability_and_performance/low_latency_tuning/cnf-tuning-low-latency-nodes-with-perf-profile.adoc#installation-openstack-ovs-dpdk-performance-profile_cnf-low-latency-perf-profile[A performance profile template for clusters that use OVS-DPDK on OpenStack]
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.
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// Module included in the following assemblies:
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//
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// * scalability_and_performance/low_latency_tuning/cnf-understanding-low-latency.adoc
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:_mod-docs-content-type: CONCEPT
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[id="cnf-about-hyper-threading-for-low-latency-and-real-time-applications_{context}"]
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= About Hyper-Threading for low latency and real-time applications
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Hyper-Threading is an Intel processor technology that allows a physical CPU processor core to function as two logical cores, executing two independent threads simultaneously. Hyper-Threading allows for better system throughput for certain workload types where parallel processing is beneficial. The default {product-title} configuration expects Hyper-Threading to be enabled.
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For telecommunications applications, it is important to design your application infrastructure to minimize latency as much as possible. Hyper-Threading can slow performance times and negatively affect throughput for compute-intensive workloads that require low latency. Disabling Hyper-Threading ensures predictable performance and can decrease processing times for these workloads.
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[NOTE]
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====
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Hyper-Threading implementation and configuration differs depending on the hardware you are running {product-title} on. Consult the relevant host hardware tuning information for more details of the Hyper-Threading implementation specific to that hardware. Disabling Hyper-Threading can increase the cost per core of the cluster.
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====

modules/cnf-about-irq-affinity-setting.adoc

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// Module included in the following assemblies:
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//
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// scalability_and_performance/cnf-low-latency-tuning.adoc
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// * scalability_and_performance/cnf-low-latency-tuning.adoc
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// * scalability_and_performance/low_latency_tuning/cnf-tuning-low-latency-nodes-with-perf-profile.adoc
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[id="about_irq_affinity_setting_{context}"]
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= About support of IRQ affinity setting
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= Finding the effective IRQ affinity setting for a node
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Some IRQ controllers lack support for IRQ affinity setting and will always expose all online CPUs as the IRQ mask. These IRQ controllers effectively run on CPU 0.
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----
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Some drivers use `managed_irqs`, whose affinity is managed internally by the kernel and userspace cannot change the affinity. In some cases, these IRQs might be assigned to isolated CPUs. For more information about `managed_irqs`, see link:https://access.redhat.com/solutions/4819541[Affinity of managed interrupts cannot be changed even if they target isolated CPU].
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Some drivers use `managed_irqs`, whose affinity is managed internally by the kernel and userspace cannot change the affinity. In some cases, these IRQs might be assigned to isolated CPUs. For more information about `managed_irqs`, see link:https://access.redhat.com/solutions/4819541[Affinity of managed interrupts cannot be changed even if they target isolated CPU].

modules/cnf-about-the-profile-creator-tool.adoc

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// Module included in the following assemblies:
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// Epic CNF-792 (4.8)
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// * scalability_and_performance/cnf-create-performance-profiles.adoc
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//
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[id="cnf-about-the-profile-creator-tool_{context}"]

modules/cnf-about_hyperthreading_for_low_latency_and_real_time_applications.adoc

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modules/cnf-adjusting-nic-queues-with-the-performance-profile.adoc

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//
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$ oc apply -f <your_profile_name>.yaml
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modules/cnf-allocating-multiple-huge-page-sizes.adoc

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// CNF-538 Promote Multiple Huge Pages Sizes for Pods and Containers to beta
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----

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