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. Create a `PerformanceProfile` appropriate for the environment's hardware and topology as described in the table in "Understanding workload hints". Adjust the profile to match the expected workload. In this example, we tune for the lowest possible latency.
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. Add the `highPowerConsumption` and `realtime` workload hints. Both are set to `true` here.
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[source,yaml]
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----
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apiVersion: performance.openshift.io/v2
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kind: PerformanceProfile
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metadata:
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name: workload-hints
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spec:
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...
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workloadHints:
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highPowerConsumption: true <1>
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realtime: true <2>
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----
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<1> If `highPowerConsumption` is `true`, the node is tuned for very low latency at the cost of increased power consumption.
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<2> Disables some debugging and monitoring features that can affect system latency.
Copy file name to clipboardExpand all lines: modules/cnf-understanding-low-latency.adoc
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@@ -42,8 +42,22 @@ set values, installing a kernel, and reconfiguring the machine. But this method
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requires setting up four different Operators and performing many configurations
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that, when done manually, is complex and could be prone to mistakes.
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-
{product-title}provides a Performance Addon Operator to implement automatic
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{product-title}uses the Node Tuning Operator to implement automatic
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tuning to achieve low latency performance for OpenShift applications.
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The cluster administrator uses this performance profile configuration that makes
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it easier to make these changes in a more reliable way. The administrator can
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specify whether to update the kernel to kernel-rt, reserve CPUs for cluster and operating system housekeeping duties, including pod infra containers, and isolate CPUs for application containers to run the workloads.
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{product-title} also supports workload hints for the Node Tuning Operator that can tune the `PerformanceProfile` to meet the demands of different industry environments. Workload hints are available for `highPowerConsumption` (very low latency at the cost of increased power consumption) and `realtime` (priority given to optimum latency). A combination of `true/false` settings for these hints can be used to deal with application-specific workload profiles and requirements.
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Workload hints simplify the fine-tuning of performance to industry sector settings. Instead of a “one size fits all” approach, workload hints can cater to usage patterns such as placing priority on:
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* Low latency
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* Real-time capability
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* Efficient use of power
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In an ideal world, all of those would be prioritized: in real life, some come at the expense of others. The Node Tuning Operator is now aware of the workload expectations and better able to meet the demands of the workload. The cluster admin can now specify into which use case that workload falls. The Node Tuning Operator uses the `PerformanceProfile` to fine tune the performance settings for the workload.
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The environment in which an application is operating influences its behavior. For a typical data center with no strict latency requirements, only minimal default tuning is needed that enables CPU partitioning for some high performance workload pods.
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For data centers and workloads where latency is a higher priority, measures are still taken to optimize power consumption.
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The most complicated cases are clusters close to latency-sensitive equipment such as manufacturing machinery and software-defined radios. This last class of deployment is often referred to as Far edge. For Far edge deployments, ultra-low latency is the ultimate priority, and is achieved at the expense of power management.
The following table describes how combinations of power consumption and real-time settings impact on latency.
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[NOTE]
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====
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The following workload hints can be configured manually. See "Creating a performance profile" for further information. You can also work with workload hints using the Performance Profile Creator. See "Creating a performance profile" for further information.
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====
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[cols="1,1,1,1",options="header"]
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|===
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| Performance Profile creator setting| Hint | Environment | Description
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| Default
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a|[source,terminal]
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----
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workloadHints:
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highPowerConsumption: false
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realtime: false
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----
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| High throughput cluster without latency requirements
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| Performance achieved through CPU partitioning only.
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| Low-latency
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a|[source,terminal]
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----
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workloadHints:
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highPowerConsumption: false
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realtime: true
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----
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| Regional datacenters
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| Both energy savings and low-latency are desirable: compromise between power management, latency and throughput.
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| Ultra-low-latency
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a|[source,terminal]
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----
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workloadHints:
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highPowerConsumption: true
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realtime: true
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----
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| Far edge clusters, latency critical workloads
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| Optimized for absolute minimal latency and maximum determinism at the cost of increased power consumption.
* For information on using the Performance Profile Creator (PPC) to generate a performance profile, see xref:../scalability_and_performance/cnf-create-performance-profiles.adoc#cnf-create-performance-profiles[Creating a performance profile].
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