Chapter 1. Configuring and deploying a Red Hat OpenStack Platform hyperconverged infrastructure Red Hat OpenStack Platform (RHOSP) hyperconverged infrastructures (HCI) consist of hyperconverged nodes. Services are colocated on these hyperconverged nodes for optimized resource usage. In a RHOSP HCI, the Compute and storage services are colocated on hyperconverged nodes. You can deploy an overcloud with only hyperconverged nodes, or a mixture of hyperconverged nodes with normal Compute and Ceph Storage nodes. Note You must use Red Hat Ceph Storage as the storage provider. Tip Use ceph-ansible 3.2 and later to automatically tune Ceph memory settings. Use BlueStore as the back end for HCI deployments, to make use of the BlueStore memory handling features. To create and deploy HCI on an overcloud, integrate with other features in your overcloud such as Network Function Virtualization, and ensure optimal performance of both Compute and Red Hat Ceph Storage services on hyperconverged nodes, you must complete the following: Prepare the predefined custom overcloud role for hyperconverged nodes, ComputeHCI . Configure resource isolation. Verify the available Red Hat Ceph Storage packages. Deploy the HCI overcloud. For HCI configuration guidance, see Configuration guidance . 1.1. Prerequisites You have deployed the undercloud. For instructions on how to deploy the undercloud, see Director Installation and Usage . Your environment can provision nodes that meet RHOSP Compute and Red Hat Ceph Storage requirements. For more information, see Basic Overcloud Deployment . You have registered all nodes in your environment. For more information, see Registering Nodes . You have tagged all nodes in your environment. For more information, see Manually Tagging the Nodes . You have cleaned the disks on nodes that you plan to use for Compute and Ceph OSD services. For more information, see Cleaning Ceph Storage Node Disks . You have prepared your overcloud nodes for registration with the Red Hat Content Delivery Network or a Red Hat Satellite server. For more information, see Ansible-based Overcloud Registration . 1.2. Preparing the overcloud role for hyperconverged nodes To designate nodes as hyperconverged, you need to define a hyperconverged role. Red Hat OpenStack Platform (RHOSP) provides the predefined role ComputeHCI for hyperconverged nodes. This role colocates the Compute and Ceph object storage daemon (OSD) services, allowing you to deploy them together on the same hyperconverged node. Procedure Log in to the undercloud as the stack user. Source the stackrc file: Generate a new custom roles data file that includes the ComputeHCI role, along with other roles you intend to use for the overcloud. The following example generates the roles data file roles_data_hci.yaml that includes the roles Controller , ComputeHCI , Compute , and CephStorage : Note The networks listed for the ComputeHCI role in the generated custom roles data file include the networks required for both Compute and Storage services, for example: Create a local copy of the network_data.yaml file to add a composable network to your overcloud. The network_data.yaml file interacts with the default network environment files, /usr/share/openstack-tripleo-heat-templates/environments/* , to associate the networks you defined for your ComputeHCI role with the hyperconverged nodes. For more information, see Adding a composable network in the Advanced Overcloud Customization guide. To improve the performance of Red Hat Ceph Storage, update the MTU setting for both the Storage and StorageMgmt networks to 9000 , for jumbo frames, in your local copy of network_data.yaml . For more information, see Configuring MTU Settings in Director and Configuring jumbo frames . Create the computeHCI overcloud flavor for hyperconverged nodes: Replace <ram_size_mb> with the RAM of the bare metal node, in MB. Replace <disk_size_gb> with the size of the disk on the bare metal node, in GB. Replace <no_vcpus> with the number of CPUs on the bare metal node. Note These properties are not used for scheduling instances. However, the Compute scheduler does use the disk size to determine the root partition size. Retrieve a list of your nodes to identify their UUIDs: Tag each bare metal node that you want to designate as hyperconverged with a custom HCI resource class: Replace <node> with the ID of the bare metal node. Associate the computeHCI flavor with the custom HCI resource class: To determine the name of a custom resource class that corresponds to a resource class of a Bare Metal service node, convert the resource class to uppercase, replace all punctuation with an underscore, and prefix with CUSTOM_ . Note A flavor can request only one instance of a bare metal resource class. Set the following flavor properties to prevent the Compute scheduler from using the bare metal flavor properties to schedule instances: Add the following parameters to the node-info.yaml file to specify the number of hyperconverged and Controller nodes, and the flavor to use for the hyperconverged and controller designated nodes: Additional resources Composable Services and Custom Roles Examining the roles_data file Assigning Nodes and Flavors to Roles 1.2.1. Defining the root disk for multi-disk clusters Director must identify the root disk during provisioning in the case of nodes with multiple disks. For example, most Ceph Storage nodes use multiple disks. By default, director writes the overcloud image to the root disk during the provisioning process. There are several properties that you can define to help director identify the root disk: model (String): Device identifier. vendor (String): Device vendor. serial (String): Disk serial number. hctl (String): Host:Channel:Target:Lun for SCSI. size (Integer): Size of the device in GB. wwn (String): Unique storage identifier. wwn_with_extension (String): Unique storage identifier with the vendor extension appended. wwn_vendor_extension (String): Unique vendor storage identifier. rotational (Boolean): True for a rotational device (HDD), otherwise false (SSD). name (String): The name of the device, for example: /dev/sdb1. Important Use the name property only for devices with persistent names. Do not use name to set the root disk for any other devices because this value can change when the node boots. You can specify the root device using its serial number. Procedure Check the disk information from the hardware introspection of each node. Run the following command to display the disk information of a node: For example, the data for one node might show three disks: Enter openstack baremetal node set --property root_device= to set the root disk for a node. Include the most appropriate hardware attribute value to define the root disk. For example, to set the root device to disk 2, which has the serial number 61866da04f380d001ea4e13c12e36ad6 , enter the following command: Note Ensure that you configure the BIOS of each node to include booting from the root disk that you choose. Configure the boot order to boot from the network first, then to boot from the root disk. Director identifies the specific disk to use as the root disk. When you run the openstack overcloud deploy command, director provisions and writes the overcloud image to the root disk. 1.3. Configuring resource isolation on hyperconverged nodes Colocating Ceph OSD and Compute services on hyperconverged nodes risks resource contention between Red Hat Ceph Storage and Compute services, as neither are aware of each other's presence on the same host. Resource contention can result in degradation of service, which offsets the benefits of hyperconvergence. You must configure resource isolation for both Ceph and Compute services to prevent contention. Procedure Optional: Override the autogenerated Compute settings by adding the following parameters to a Compute environment file: Replace <ram> with the amount of RAM to reserve for the Ceph OSD services and instance overhead on hyperconverged nodes, in MB. Replace <ratio> with the ratio that the Compute scheduler should use when choosing which Compute node to deploy an instance on. For more information on the autogenerated Compute settings, see Process for autogenerating CPU and memory resources to reserve for the Compute service . To reserve memory resources for Red Hat Ceph Storage, set the parameter is_hci to true in /home/stack/templates/storage-container-config.yaml : This allows ceph-ansible to reserve memory resources for Red Hat Ceph Storage, and reduce memory growth by Ceph OSDs, by automatically adjusting the osd_memory_target parameter setting for a HCI deployment. Warning Red Hat does not recommend directly overriding the ceph_osd_docker_memory_limit parameter. Note As of ceph-ansible 3.2, the ceph_osd_docker_memory_limit is set automatically to the maximum memory of the host, as discovered by Ansible, regardless of whether the FileStore or BlueStore back end is used. Optional: By default, ceph-ansible reserves one vCPU for each Ceph OSD. If you require more than one CPU per Ceph OSD, add the following configuration to /home/stack/templates/storage-container-config.yaml : Replace <cpu_limit> with the number of CPUs to reserve for each Ceph OSD. For more information on how to tune CPU resources based on your hardware and workload, see Red Hat Ceph Storage Hardware Selection Guide . Optional: Reduce the priority of Red Hat Ceph Storage backfill and recovery operations when a Ceph OSD is removed by adding the following parameters to a Ceph environment file: Replace <priority_value> with the priority for recovery operations, relative to the OSD client OP priority. Replace <no_active_recovery_requests> with the number of active recovery requests per OSD, at one time. Replace <max_no_backfills> with the maximum number of backfills allowed to or from a single OSD. For more information on default Red Hat Ceph Storage backfill and recovery options, see Red Hat Ceph Storage backfill and recovery operations . 1.3.1. Process for autogenerating CPU and memory resources to reserve for the Compute service Director provides a default plan environment file for configuring resource constraints on hyperconverged nodes during deployment. This plan environment file instructs the OpenStack Workflow to complete the following processes: Retrieve the hardware introspection data collected during inspection of the hardware nodes. Calculate optimal CPU and memory allocation workload for Compute on hyperconverged nodes based on that data. Autogenerate the parameters required to configure those constraints and reserve CPU and memory resources for Compute. These parameters are defined under the hci_profile_config section of the plan-environment-derived-params.yaml file. Note The average_guest_memory_size_in_mb and average_guest_cpu_utilization_percentage parameters in each workload profile are used to calculate values for the reserved_host_memory and cpu_allocation_ratio settings of Compute. You can override the autogenerated Compute settings by adding the following parameters to your Compute environment file: Autogenerated nova.conf parameter Compute environment file override Description reserved_host_memory Sets how much RAM should be reserved for the Ceph OSD services and per-guest instance overhead on hyperconverged nodes. cpu_allocation_ratio Sets the ratio that the Compute scheduler should use when choosing which Compute node to deploy an instance on. These overrides are applied to all nodes that use the ComputeHCI role, namely, all hyperconverged nodes. For more information about manually determining optimal values for NovaReservedHostMemory and NovaCPUAllocationRatio , see OpenStack Workflow Compute CPU and memory calculator . Tip You can use the following script to calculate suitable baseline NovaReservedHostMemory and NovaCPUAllocationRatio values for your hyperconverged nodes. nova_mem_cpu_calc.py Additional resources Creating an inventory of the bare-metal node hardware 1.3.2. Red Hat Ceph Storage backfill and recovery operations When a Ceph OSD is removed, Red Hat Ceph Storage uses backfill and recovery operations to rebalance the cluster. Red Hat Ceph Storage does this to keep multiple copies of data according to the placement group policy. These operations use system resources. If a Red Hat Ceph Storage cluster is under load, its performance drops 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. 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. The parameters detailed in the following table are used to configure the priority of backfill and recovery operations. Parameter Description Default value osd_recovery_op_priority Sets the priority for recovery operations, relative to the OSD client OP priority. 3 osd_recovery_max_active Sets the number of active recovery requests per OSD, at one time. More requests accelerate recovery, but the requests place an increased load on the cluster. Set this to 1 if you want to reduce latency. 3 osd_max_backfills Sets the maximum number of backfills allowed to or from a single OSD. 1 1.4. Verifying available Red Hat Ceph Storage packages To help avoid overcloud deployment failures, verify that the required packages exist on your servers. 1.4.1. Verifying the ceph-ansible package version The undercloud contains Ansible-based validations that you can run to identify potential problems before you deploy the overcloud. These validations can help you avoid overcloud deployment failures by identifying common problems before they happen. Procedure Verify that the ceph-ansible package version you want is installed: 1.4.2. Verifying packages for pre-provisioned nodes Red Hat Ceph Storage (RHCS) can service only overcloud nodes that have a certain set of packages. When you use pre-provisioned nodes, you can verify the presence of these packages. For more information about pre-provisioned nodes, see Configuring a basic overcloud with pre-provisioned nodes . Procedure Verify that the pre-provisioned nodes contain the required packages: 1.5. Deploying the HCI overcloud You must deploy the overcloud after you complete the HCI configuration. Important Do not enable Instance HA when you deploy a Red Hat OpenStack Platform (RHOSP) HCI environment. Contact your Red Hat representative if you want to use Instance HA with hyperconverged RHOSP deployments with Red Hat Ceph Storage. Prerequisites You are using a separate base environment file, or set of files, for all other Red Hat Ceph Storage settings, for example, /home/stack/templates/storage-config.yaml . For more information, see Customizing the Storage service and Appendix A. Sample environment file: creating a Ceph Storage cluster . You have defined the number of nodes you are assigning to each role in the base environment file. For more information, see Assigning nodes and flavors to roles . During undercloud installation, you set generate_service_certificate=false in the undercloud.conf file. Otherwise, you must inject a trust anchor when you deploy the overcloud, as described in Enabling SSL/TLS on Overcloud Public Endpoints . Procedure Add your new role and environment files to the stack with your other environment files and deploy your HCI overcloud: Including /usr/share/openstack-tripleo-heat-templates/environments/ceph-ansible/ceph-ansible.yaml in the deployment command adds the base environment file that deploys a containerized Red Hat Ceph cluster, with all default settings. For more information, see Deploying an Overcloud with Containerized Red Hat Ceph . Note Include the following options in the deployment command if your deployment uses single root input/output virtualization (SR-IOV). If you use the ML2/OVS mechanism driver in your deployment, specify the following options: If you use the ML2/OVN mechanism driver in your deployment, specify the following options: Tip You can also use an answers file to specify which environment files to include in your deployment. For more information, see Including environment files in an overcloud deployment in the Director Installation and Usage guide. 1.5.1. Limiting the nodes on which ceph-ansible runs You can reduce deployment update time by limiting the nodes where ceph-ansible runs. When Red Hat OpenStack Platform (RHOSP) uses config-download to configure Ceph, you can use the --limit option to specify a list of nodes, instead of running config-download and ceph-ansible across your entire deployment. This feature is useful, for example, as part of scaling up your overcloud, or replacing a failed disk. In these scenarios, the deployment can run only on the new nodes that you add to the environment. Example scenario that uses --limit in a failed disk replacement In the following example procedure, the Ceph storage node oc0-cephstorage-0 has a disk failure so it receives a new factory clean disk. Ansible needs to run on the oc0-cephstorage-0 node so that the new disk can be used as an OSD but it does not need to run on all of the other Ceph storage nodes. Replace the example environment files and node names with those appropriate to your environment. Procedure Log in to the undercloud node as the stack user and source the stackrc credentials file: Complete one of the following steps so that the new disk is used to start the missing OSD. Run a stack update and include the --limit option to specify the nodes where you want ceph-ansible to run: In this example, the Controllers are included because the Ceph mons need Ansible to change their OSD definitions. If config-download has generated an ansible-playbook-command.sh script, you can also run the script with the --limit option to pass the specified nodes to ceph-ansible : Warning You must always include the undercloud in the limit list otherwise ceph-ansible cannot be executed when you use --limit . This is necessary because the ceph-ansible execution occurs through the external_deploy_steps_tasks playbook, which runs only on the undercloud. 1.6. OpenStack Workflow Compute CPU and memory calculator The OpenStack Workflow calculates the optimal settings for CPU and memory and uses the results to populate the parameters NovaReservedHostMemory and NovaCPUAllocationRatio . NovaReservedHostMemory The NovaReservedHostMemory parameter sets the amount of memory (in MB) to reserve for the host node. To determine an appropriate value for hyper-converged nodes, assume that each OSD consumes 3 GB of memory. Given a node with 256 GB memory and 10 OSDs, you can allocate 30 GB of memory for Ceph, leaving 226 GB for Compute. With that much memory a node can host, for example, 113 instances using 2 GB of memory each. However, you still need to consider additional overhead per instance for the hypervisor . Assuming this overhead is 0.5 GB, the same node can only host 90 instances, which accounts for the 226 GB divided by 2.5 GB. The amount of memory to reserve for the host node (that is, memory the Compute service should not use) is: (In * Ov) + (Os * RA) Where: In : number of instances Ov : amount of overhead memory needed per instance Os : number of OSDs on the node RA : amount of RAM that each OSD should have With 90 instances, this give us (90*0.5) + (10*3) = 75 GB. The Compute service expects this value in MB, namely 75000. The following Python code provides this computation: NovaCPUAllocationRatio The Compute scheduler uses NovaCPUAllocationRatio when choosing which Compute nodes on which to deploy an instance. By default, this is 16.0 (as in, 16:1). This means if there are 56 cores on a node, the Compute scheduler will schedule enough instances to consume 896 vCPUs on a node before considering the node unable to host any more. To determine a suitable NovaCPUAllocationRatio for a hyper-converged node, assume each Ceph OSD uses at least one core (unless the workload is I/O-intensive, and on a node with no SSD). On a node with 56 cores and 10 OSDs, this would leave 46 cores for Compute. If each instance uses 100 per cent of the CPU it receives, then the ratio would simply be the number of instance vCPUs divided by the number of cores; that is, 46 / 56 = 0.8. However, since instances do not normally consume 100 per cent of their allocated CPUs, you can raise the NovaCPUAllocationRatio by taking the anticipated percentage into account when determining the number of required guest vCPUs. So, if we can predict that instances will only use 10 per cent (or 0.1) of their vCPU, then the number of vCPUs for instances can be expressed as 46 / 0.1 = 460. When this value is divided by the number of cores (56), the ratio increases to approximately 8. The following Python code provides this computation: 1.7. Additional resources For more detailed information about the Red Hat OpenStack Platform (RHOSP), see the following guides: Director Installation and Usage : This guide provides guidance on the end-to-end deployment of a RHOSP environment, both undercloud and overcloud. Advanced Overcloud Customization : This guide describes how to configure advanced RHOSP features through the director, such as how to use custom roles. Deploying an Overcloud with Containerized Red Hat Ceph : This guide describes how to deploy an overcloud that uses Red Hat Ceph Storage as a storage provider. Networking Guide : This guide provides details on RHOSP networking tasks.

Commands:
[stack@director ~]USD source ~/stackrc
(undercloud)USD openstack overcloud roles generate -o /home/stack/templates/roles_data_hci.yaml Controller ComputeHCI Compute CephStorage
- name: ComputeHCI description: | Compute node role hosting Ceph OSD tags: - compute networks: InternalApi: subnet: internal_api_subnet Tenant: subnet: tenant_subnet Storage: subnet: storage_subnet StorageMgmt: subnet: storage_mgmt_subnet
(undercloud)USD openstack flavor create --id auto --ram <ram_size_mb> --disk <disk_size_gb> --vcpus <no_vcpus> computeHCI
(undercloud)USD openstack baremetal node list
(undercloud)USD openstack baremetal node set --resource-class baremetal.HCI <node>
(undercloud)USD openstack flavor set --property resources:CUSTOM_BAREMETAL_HCI=1 computeHCI
(undercloud)USD openstack flavor set --property resources:VCPU=0 --property resources:MEMORY_MB=0 --property resources:DISK_GB=0 computeHCI
parameter_defaults: OvercloudComputeHCIFlavor: computeHCI ComputeHCICount: 3 Controller: control ControllerCount: 3
(undercloud)USD openstack baremetal introspection data save 1a4e30da-b6dc-499d-ba87-0bd8a3819bc0 | jq ".inventory.disks"
[ { "size": 299439751168, "rotational": true, "vendor": "DELL", "name": "/dev/sda", "wwn_vendor_extension": "0x1ea4dcc412a9632b", "wwn_with_extension": "0x61866da04f3807001ea4dcc412a9632b", "model": "PERC H330 Mini", "wwn": "0x61866da04f380700", "serial": "61866da04f3807001ea4dcc412a9632b" } { "size": 299439751168, "rotational": true, "vendor": "DELL", "name": "/dev/sdb", "wwn_vendor_extension": "0x1ea4e13c12e36ad6", "wwn_with_extension": "0x61866da04f380d001ea4e13c12e36ad6", "model": "PERC H330 Mini", "wwn": "0x61866da04f380d00", "serial": "61866da04f380d001ea4e13c12e36ad6" } { "size": 299439751168, "rotational": true, "vendor": "DELL", "name": "/dev/sdc", "wwn_vendor_extension": "0x1ea4e31e121cfb45", "wwn_with_extension": "0x61866da04f37fc001ea4e31e121cfb45", "model": "PERC H330 Mini", "wwn": "0x61866da04f37fc00", "serial": "61866da04f37fc001ea4e31e121cfb45" } ]
(undercloud)USD openstack baremetal node set --property root_device='{"serial":"<serial_number>"}' <node-uuid>
(undercloud)USD openstack baremetal node set --property root_device='{"serial": "61866da04f380d001ea4e13c12e36ad6"}' 1a4e30da-b6dc-499d-ba87-0bd8a3819bc0
parameter_defaults: ComputeHCIParameters: NovaReservedHostMemory: <ram> NovaCPUAllocationRatio: <ratio>
parameter_defaults: CephAnsibleExtraConfig: is_hci: true
parameter_defaults: CephAnsibleExtraConfig: ceph_osd_docker_cpu_limit: <cpu_limit>
parameter_defaults: CephConfigOverrides: osd_recovery_op_priority: <priority_value> osd_recovery_max_active: <no_active_recovery_requests> osd_max_backfills: <max_no_backfills>
parameter_defaults: ComputeHCIParameters: NovaReservedHostMemory: 181000
parameter_defaults: ComputeHCIParameters: NovaCPUAllocationRatio: 8.2
ansible-playbook -i /usr/bin/tripleo-ansible-inventory /usr/share/ansible/validation-playbooks/ceph-ansible-installed.yaml
ansible-playbook -i /usr/bin/tripleo-ansible-inventory /usr/share/ansible/validation-playbooks/ceph-dependencies-installed.yaml
(undercloud)USD openstack overcloud deploy --templates -e [your environment files] -r /home/stack/templates/roles_data_hci.yaml -e /usr/share/openstack-tripleo-heat-templates/environments/ceph-ansible/ceph-ansible.yaml -e /usr/share/openstack-tripleo-heat-templates/environments/network-isolation.yaml -e /usr/share/openstack-tripleo-heat-templates/environments/network-environment.yaml -e /usr/share/openstack-tripleo-heat-templates/environments/net-single-nic-with-vlans.yaml -e /home/stack/templates/storage-config.yaml -e /home/stack/templates/storage-container-config.yaml -n /home/stack/templates/network_data.yaml [-e /home/stack/templates/ceph-backfill-recovery.yaml \ ] --ntp-server pool.ntp.org
-e /usr/share/openstack-tripleo-heat-templates/environments/services/neutron-sriov.yaml -e /home/stack/templates/network-environment.yaml
-e /usr/share/openstack-tripleo-heat-templates/environments/services/neutron-ovn-sriov.yaml -e /home/stack/templates/network-environment.yaml
source stackrc
openstack overcloud deploy --templates -r /home/stack/roles_data.yaml -n /usr/share/openstack-tripleo-heat-templates/network_data_dashboard.yaml -e /usr/share/openstack-tripleo-heat-templates/environments/ceph-ansible/ceph-ansible.yaml -e ~/my-ceph-settings.yaml -e <other-environment_files> --limit oc0-controller-0:oc0-controller-2:oc0-controller-1:oc0-cephstorage-0:undercloud
./ansible-playbook-command.sh --limit oc0-controller-0:oc0-controller-2:oc0-controller-1:oc0-cephstorage-0:undercloud
left_over_mem = mem - (GB_per_OSD * osds) number_of_guests = int(left_over_mem / (average_guest_size + GB_overhead_per_guest)) nova_reserved_mem_MB = MB_per_GB * ( (GB_per_OSD * osds) + (number_of_guests * GB_overhead_per_guest))
cores_per_OSD = 1.0 average_guest_util = 0.1 # 10% nonceph_cores = cores - (cores_per_OSD * osds) guest_vCPUs = nonceph_cores / average_guest_util cpu_allocation_ratio = guest_vCPUs / cores