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covery for microsoft sql server on persistent disk disaster recovery for microsoft sql server on hyperdisk deploying microsoft sql server for multi regional disaster recovery back up sql server databases to a google cloud storage bucket back up sql server databases using instant snapshots cloning a microsoft sql server database on compute engine load test sql server using hammerdb redis deployment options for redis on google cloud containers containers on compute engine deploy containers on vms and managed instance groups configure options to run your container transition from the container startup agent prepare for the shutdown of the container startup agent prevent the creation of vms that use the container metadata migrate containers that were deployed on vms during vm creation openshift workloads openshift on google cloud overview plan for openshift on google cloud overview of cluster services for openshift automatic configuration validation for openshift clusters built in integrations for openshift best practices for high availability with openshift disaster recovery for openshift on google cloud disaster recovery strategies for active passive and active inactive setups with openshift microsoft windows windows workloads best practices for windows server vms setting up active directory best practices for running active directory on google cloud deploy microsoft sharepoint server on compute engine deploying microsoft exchange server 2016 on compute engine windows server perform an in place upgrade of windows server run windows server failover clustering ibm spectrum symphony integrate ibm spectrum symphony with google cloud install the compute engine symphony provider install the google kubernetes symphony provider troubleshoot ibm spectrum symphony others load testing distributed load testing using kubernetes ssh port forwarding and load testing analytics monte carlo methods using apache spark machine learning run tensorflow inference workloads with tensorrt5 and nvidia t4 gpu monitor monitor logs view audit logs view usage reports view compute engine operations migrate from activity logs to audit logs view activity logs monitor resources monitor vm and sole tenant node usage observe and monitor vms monitor gpu performance monitor gpu performance on linux vms monitor gpu performance on windows vms monitor disks monitor disk health monitor the replica states of regional disks monitor disks list of metrics for pools monitor pools monitor reservations organize resources using labels scale autoscale groups of vms about autoscaling groups of vms create and manage autoscalers scale based on cpu utilization scale based on predictions scale based on load balancing serving capacity scale based on monitoring metrics scale based on schedules use an autoscaling policy with multiple signals manage autoscalers understand autoscaler decisions view autoscaler logs autoscale node groups reserve vm capacity choose a reservation type sharing reservations best practices for shared reservations allow a project to share reservations on demand reservations about on demand reservations create an on demand reservation for a single project for multiple projects combine an on demand reservation with a cud modify an on demand reservation delete an on demand reservation future reservations about future reservations create a reservation request for a single project for multiple projects modify a reservation request delete a reservation request future reservations in calendar mode about future reservations in calendar mode create a reservation request in calendar mode delete a reservation request in calendar mode view reservations or reservation requests consume a reservation prevent vms from consuming reservations load balancing about load balancing and scaling add an instance group to a load balancer request routing to a multi region external https load balancer cross region load balancing for microsoft iis backends set up internal tcp udp load balancing build reliable and scalable applications use autohealing for highly available applications use load balancing for highly available applications use autoscaling for highly scalable applications globally autoscale a web service on compute engine patterns for scalable and resilient applications patterns for using floating ip addresses on compute engine optimize resource utilization use recommendations to manage resources apply machine type recommendations to vms configure machine type recommendations apply machine type recommendations to migs view and apply idle resources recommendations view and understand vm insights view and understand mig insights manage idle vm recommendations idle vm recommendations overview view and apply idle vm recommendations configure idle vm recommendations manage reservation recommendations reservation recommendations overview view and apply idle reservation recommendations view and apply underutilized reservation recommendations configure idle reservation recommendations configure underutilized reservation recommendations overcommit cpus on sole tenant vms manual live migration about manual live migration manually live migrate vms share sole tenant node groups next generation dynamic resource management cost savings get discounts for committed usage about commitments and committed use discounts cuds resource based cuds purchase resource based commitments without attached reservations with attached reservations for os licenses manage resource based commitments renew commitments automatically extend commitment terms merge and split commitments upgrade commitments share resource based cuds across projects get discounts for sustained usage disk performance optimize hyperdisk performance optimize persistent disk performance optimize local ssd performance workload performance set the number of threads per core customize the number of visible cpu cores analyze the cpu performance using the pmu pmu overview enable the pmu in vms manage the pmu in vms network performance network bandwidth use google virtual nic use irdma network driver use idpf network interface configure a vm with higher bandwidth reduce latency by using compact placement policies optimize tcp network communication optimize tcp network performance optimize tcp network resiliency benchmark higher bandwidth vms optimize app latency with load balancing use dpdk to improve network performance network performance and gpu vms networking and gpu machines use higher network bandwidth patterns for using multiple host nics troubleshoot general tips troubleshoot connectivity troubleshoot rdp troubleshoot ssh troubleshoot os login troubleshoot vms troubleshoot vm operations troubleshoot vm creation troubleshoot resource availability errors troubleshoot bulk api vm creation troubleshoot vm reboots and shutdowns troubleshoot vm suspension troubleshoot vm updates troubleshoot unresponsive vms troubleshoot vm startup troubleshoot fstab errors troubleshoot kernel panic collecting core dumps rescue an inaccessible vm troubleshoot cpu bus locks troubleshoot cpu soft lockups troubleshoot vm configurations troubleshoot arm vms troubleshoot gpu vms troubleshoot nvidia gpu errors generate a nvidia bug report for blackwell gpus troubleshoot nested virtualization troubleshoot using vm screenshots troubleshoot sole tenant nodes troubleshoot vm performance issues troubleshoot sudoers files troubleshoot windows vms troubleshoot windows vms collecting diagnostic information troubleshoot using the serial console troubleshoot using the serial console viewing serial port output troubleshoot instance groups troubleshoot managed instance groups migs troubleshoot os management troubleshoot licenses troubleshoot image import and export troubleshooting sles pay as you go registration troubleshooting ubuntu pro registration troubleshoot metadata server troubleshoot metadata server troubleshoot networking issues troubleshoot common networking issues troubleshoot network drivers troubleshoot vm performance issues troubleshoot storage troubleshoot disk creation troubleshoot full disks and disk resizing troubleshoot disk encryption troubleshoot nvme disks troubleshoot instant snapshots troubleshoot standard snapshots troubleshoot reservations and commitments troubleshoot reservation creation troubleshoot reservation consumption troubleshooting reservation monitoring troubleshoot reservation updates troubleshoot future reservation creation and updates troubleshoot automatic commitment renewal troubleshoot quota errors troubleshoot concurrent operation quota errors troubleshoot workload authentication troubleshoot default service accounts troubleshoot workload to workload authentication ai and ml application development application hosting compute data analytics and pipelines databases distributed hybrid and multicloud industry solutions migration networking observability and monitoring security storage access and resources management costs and usage management infrastructure as code sdk languages frameworks and tools home documentation compute compute engine guides send feedback install drivers for nvidia rtx virtual workstations vws stay organized with collections save and categorize content based on your preferences linux windows if you need gpus for hardware accelerated graphics on a remote desktop or for gaming you can create virtual workstations that use nvidia rtx virtual workstations vws formerly known as nvidia grid nvidia rtx virtual workstations are ideal for running workloads that use apis such as vulkan opengl or direct3d on a cloud remote desktop when you select a gpu that supports visualization for a virtual workstation you can add an nvidia rtx virtual workstation license to your vm for more information about pricing see gpu pricing to set up an nvidia rtx virtual workstation you need to do the following create a vm that has a visualization capable gpu attached and virtual workstation enabled for g2 and g4 vms see create a gpu vm for graphics workloads for n1 vms see create an n1 vm with attached gpus install a driver for the virtual workstation after you create your virtual workstation you can connect to it using a remote desktop protocol such as windows remote desktop protocol rdp hp anyware or vmware horizon view before you begin if you haven t already set up authentication authentication verifies your identity for access to google cloud services and apis to run code or samples from a local development environment you can authenticate to compute engine by selecting one of the following options select the tab for how you plan to use the samples on this page console when you use the google cloud console to access google cloud services and apis you don t need to set up authentication gcloud install the google cloud cli after installation initialize the google cloud cli by running the following command gcloud init if you re using an external identity provider idp you must first sign in to the gcloud cli with your federated identity note if you installed the gcloud cli previously make sure you have the latest version by running gcloud components update set a default region and zone rest to use the rest api samples on this page in a local development environment you use the credentials you provide to the gcloud cli install the google cloud cli if you re using an external identity provider idp you must first sign in to the gcloud cli with your federated identity for more information see authenticate for using rest in the google cloud authentication documentation recommended minimum nvidia virtual gpu software nvidia rtx virtual workstations vws are supported on the following machine series g4 you can enable nvidia rtx pro 6000 vws on these machine types g2 you can enable nvidia l4 vws on these machine types n1 you can enable nvidia t4 v100 or p100 vws gpus on these machine types the following table provides the recommended nvidia virtual gpu software software for these machine types nvidia vgpu software version supported machine series and gpu model recommended nvidia driver linux recommended nvidia driver windows vgpu branch type vgpu software eos date 20 g4 rtx pro 6000 g2 l4 n1 t4 p100 latest r595 driver latest r595 driver production branch march 2027 19 g4 rtx pro 6000 g2 l4 n1 t4 v100 p100 latest r580 driver latest r580 driver long term support branch july 2028 limitations for ubuntu 24 04 nvidia rtx virtual workstations the available nvidia grid driver versions might not fully support direct rendering infrastructure 3 dri3 this lack of full support can affect gpu acceleration for certain desktop applications and virtual desktop environments such as virtual network computing vnc and chromium if you need to run these applications use ubuntu 22 04 automated driver installation you can use an open source script from github to automate the installation of rtx virtual workstation drivers this is the same script used for regular driver installation it automatically detects that your instance has rtx virtual workstation enabled and installs the correct driver linux use these instructions to install gpu drivers on a running compute instance supported operating systems the linux installation script was tested on the following operating systems debian 12 and 13 red hat enterprise linux rhel 8 9 and 10 rocky linux 8 9 and 10 ubuntu 22 and 24 if you use this script on other operating systems the installation might fail this script can install nvidia driver as well as cuda toolkit to install the gpu drivers and cuda toolkit complete the following steps if you have version 2 38 0 or later of the ops agent collecting gpu metrics on your compute instance you must stop the agent before you can install or upgrade your gpu drivers using this installation script to stop the ops agent run the following command sudo systemctl stop google cloud ops agent ensure that python 3 is installed on your operating system download the installation script curl l https storage googleapis com compute gpu installation us installer latest cuda_installer pyz output cuda_installer pyz run the installation script sudo python3 cuda_installer pyz install_driver the script takes several minutes to run it might restart your compute instance when the compute instance restarts run the script again with the same parameters to continue the installation verify the installation see verify the gpu driver install you can also use this tool to install the cuda toolkit to install the cuda toolkit run the following command sudo python3 cuda_installer pyz install_cuda the script takes several minutes to run it might restart your compute instance if the compute instance restarts run the script again to continue the installation verify the cuda toolkit installation python3 cuda_installer pyz verify_cuda after you complete the installation you must reboot the compute instance linux startup script use these instructions to install gpu drivers during startup of a compute instance suppor...