Red Hat Summit Red Hat SummitApoyoConsolaDesarrolladoresIniciar una pruebaContacto

Este contenido no está disponible en el idioma seleccionado.

Chapter 4. Configuring Resource Isolation on Hyper-Converged Nodes

With the Red Hat OpenStack Platform implementation of HCI, the director creates hyper-converged nodes by colocating Ceph OSD and Compute services. However, without any further tuning this colocation also risks resource contention between Ceph and Compute services, as neither are aware of each other’s presence on the same host. Resource contention can result in degradation of service. This, in turn, offsets any benefits provided by hyper-convergence.

To prevent contention, you need to configure resource isolation for both Ceph and Compute services. The following subsections describe how to do so.

4.1. Reserve CPU and Memory Resources for Compute
Copiar enlace

By default, the Compute service parameters do not take into account the colocation of Ceph OSD services on the same node. Hyper-converged nodes need to be tuned in order to address this to maintain stability and maximize the number of possible instances. To do this, you need to set resource constraints for the Compute service on hyper-converged nodes. You can configure this through a plan environment file.

Plan environment files define workflows, which the director can execute through the OpenStack Workflow (Mistral) service. The director also provides a default plan environment file specifically for configuring resource constraints on hyper-converged nodes, namely:

/usr/share/openstack-tripleo-heat-templates/plan-samples/plan-environment-derived-params.yaml

Use the -p parameter to invoke this plan environment file during deployment (as in, to your openstack overcloud deploy command). This plan environment file will direct OpenStack Workflow to:

  1. Retrieve hardware introspection data (collected during Inspecting the Hardware of Nodes),
  2. Calculate optimal CPU and memory constraints for Compute on hyper-converged nodes based on that data, and
  3. Autogenerate the necessary parameters to configure those constraints.

The ~/plan-samples/plan-environment-derived-params.yaml plan environment file defines several CPU and memory allocation workload profile defined under hci_profile_config. The hci_profile parameter sets which workload profile is enabled; for example, if you are using NFV, set hci_profile: nfv_default.

You can also define a custom profile in your own plan environment file using the same syntax. For example, to define a new profile named my_workload:

The average_guest_memory_size_in_mb and average_guest_cpu_utilization_percentage parameters in each workload profile will calculate values for the reserved_host_memory and cpu_allocation_ratio settings of Compute. These values are calculated based on Red Hat recommendations, and are similar to calculations made manually in previous releases (in particular, Reserve CPU and Memory Resources for Compute).

4.1.1. Override Calculated Settings for Memory or CPU Allocation
Copiar enlace

You can override the Compute settings automatically defined by OpenStack Workflow through another environment file. This is useful if you want to only override either reserved_host_memory or cpu_allocation_ratio and let OpenStack Workflow define the other. Consider the following snippet: 

parameter_defaults:
  ComputeHCIParameters:
    NovaReservedHostMemory: 181000 #
1 

  ComputeHCIExtraConfig:
    nova::cpu_allocation_ratio: 8.2 #
2
Copy to Clipboard Toggle word wrap
1
The NovaReservedHostMemory parameter sets how much RAM should be reserved for the Ceph OSD services and per-guest instance overhead on hyper-converged nodes.
2
The nova::cpu_allocation_ratio: parameter sets the ratio that the Compute scheduler should use when choosing which Compute node to deploy an instance.

The ComputeHCIParameters and ComputeHCIExtraConfig hooks apply their nested parameters to all nodes that use the ComputeHCI role (namely, all hyper-converged nodes). For more information about manually determining optimal values for NovaReservedHostMemory and nova::cpu_allocation_ratio:, see Section A.2, “Compute CPU and Memory Calculator”.

4.2. Reduce Ceph Backfill and Recovery Operations
Copiar enlace

When a Ceph OSD is removed, Ceph uses backfill and recovery operations to rebalance the cluster. Ceph does this to keep multiple copies of data according to the placement group policy. These operations use system resources. If a Ceph cluster is under load its performance will drop as it diverts resources to backfill and recovery.

To mitigate this performance effect during OSD removal, you can reduce the priority of backfill and recovery operations. Keep in mind that the trade off for this is that there are less data replicas for a longer time, which puts the data at a slightly greater risk.

To configure the priority of backfill and recovery operations, add an environment file named ceph-backfill-recovery.yaml to ~/templates containing the following: 

parameter_defaults:
  CephAnsibleExtraConfig:
    osd_recovery_op_priority: 3
1 

    osd_recovery_max_active: 3
2 

    osd_max_backfills: 1
3
Copy to Clipboard Toggle word wrap
1
The osd_recovery_op_priority sets the priority for recovery operations, relative to the OSD client OP priority.
2
The osd_recovery_max_active sets the number of active recovery requests per OSD, at one time. More requests will accelerate recovery, but the requests place an increased load on the cluster. Set this to 1 if you want to reduce latency.
3
The osd_max_backfills sets the maximum number of backfills allowed to or from a single OSD.
Important

The values used in this sample are the current defaults. You do not need to add ceph-backfill-recovery.yaml to your deployment unless you plan to use different values.

Volver arriba
Red Hat logoGithubredditYoutubeTwitter

Aprender

Pruebe, compre y venda

Comunidades

Acerca de la documentación de Red Hat

Ayudamos a los usuarios de Red Hat a innovar y alcanzar sus objetivos con nuestros productos y servicios con contenido en el que pueden confiar. Explore nuestras recientes actualizaciones.

Hacer que el código abierto sea más inclusivo

Red Hat se compromete a reemplazar el lenguaje problemático en nuestro código, documentación y propiedades web. Para más detalles, consulte el Blog de Red Hat.

Acerca de Red Hat

Ofrecemos soluciones reforzadas que facilitan a las empresas trabajar en plataformas y entornos, desde el centro de datos central hasta el perímetro de la red.

Theme

© 2025 Red Hat