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ng controls manual scaling metadata description labels tags source deploy configurations supported language runtimes and base images configure automatic base image updates build environment variables build service account build worker pools invoke and trigger services invoke with https requests host a webhook target stream with websockets overview build a websocket chat service tutorial invoke asynchronously invoke services on a schedule create a workflow invoke services as part of a workflow connect a series of services from cloud functions and cloud run tutorial execute asynchronous tasks call a service from a pub sub push subscription trigger service from pub sub integrate image processing into pub sub sample tutorial trigger from events create triggers with eventarc pub sub triggers create pub sub eventarc triggers trigger functions from pub sub using eventarc trigger functions from routed log entries cloud storage triggers create triggers with cloud storage trigger services from cloud storage using eventarc trigger functions from cloud storage using eventarc firestore triggers create triggers with firestore trigger functions from events in a firestore database connect with other services using grpc best practices general development tips for services cost optimization optimize java services optimize python services optimize node js services load testing best practices understand zonal redundancy functions best practices overview configure event driven function retries execute job tasks to completion create jobs execute jobs execute jobs execute scheduled jobs execute jobs from workflows configure jobs container entrypoint cpu limits memory limits gpu gpu configuration gpu best practices environment variables container health checks volume mounts cloud storage volumes nfs volumes in memory volumes using cifs smb network file systems ephemeral disk labels maximum retries parallelism secrets service identity task timeout tags manage jobs view or delete jobs view or stop job executions best practices jobs retries and checkpoints cost optimization perform continuous background work deploy worker pools deploy worker pools deploy worker pools from source code manage worker pools view or delete worker pools view or delete worker pool revisions instance splits and rollbacks configure worker pools capacity memory limits cpu limits gpu gpu configuration gpu best practices environment container and entrypoint environment variables volume mounts cloud storage volumes nfs volumes in memory volumes using cifs smb network file systems ephemeral disk container health checks secrets service identity instance count metadata description labels scale based on external metrics autoscale worker pools with external metrics kafka autoscaler host github runners with worker pools autoscale worker pools based on prometheus metrics autoscale worker pools with pub sub pull subscriptions automate scaling with workflows cost optimization configure networking best practices for cloud run networking configure private networking send traffic to vpc network overview direct vpc register private ips for worker pools using cloud dns dual stack ipv4 and ipv6 migrate standard vpc connector to direct vpc vpc connectors send traffic to shared vpc network overview direct vpc migrate shared vpc connector to direct vpc connectors in service projects connectors in host project static outbound ip address network security restrict endpoint ingress services use vpc service controls vpc sc cloud service mesh secure security design overview authenticate requests overview allow public access custom audiences authenticate developers service to service authenticate users end user authentication tutorial secure your resources access control with iam configure iap for cloud run introduction to service identity protect services with cloud armor use binary authorization use cloud run threat detection use customer managed encryption keys manage custom constraints for projects view software supply chain security insights secure cloud run services tutorial multi tenant platforms running untrusted code monitor and log monitoring and logging overview view built in metrics write prometheus metrics write opentelemetry metrics log and view logs audit logging error reporting use distributed tracing for services run ai solutions overview explore resources ai agents overview build and deploy a2a agents overview deploy a2a agents build and deploy adk agents build and deploy n8n agents mcp servers overview build and deploy a remote mcp server tools code execution browser automation inference with gpus overview services run llm inference on cloud run gpus with ollama run agents with gemma 4 models on cloud run run opencv on cloud run with gpu acceleration run llm inference on cloud run gpus with hugging face transformers js jobs fine tune llms using gpus with cloud run jobs run batch inference using gpus with cloud run jobs gpu accelerated video transcoding with ffmpeg ai assisted development and vibe coding introduction to cloud run for ai assisted developers cookbook migrate an existing web service from app engine from cloud run functions 1st gen from aws lambda from heroku from cloud foundry migration overview choose an oci compliant strategy migrate to oci containers migrate configuration sample migration spring music from vmware tanzu from a vm using migrate to containers from kubernetes to gke troubleshoot introduction troubleshoot errors local troubleshooting tutorial known issues samples all cloud run code samples all cloud run functions code samples code samples for all products 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 application hosting cloud run guides send feedback configure custom scaling controls for services stay organized with collections save and categorize content based on your preferences preview configure custom cpu and concurrency utilization targets for cloud run service revisions this feature is subject to the pre ga offerings terms in the general service terms section of the service specific terms pre ga features are available as is and might have limited support for more information see the launch stage descriptions by default cloud run optimizes for high performance with a utilization target of 60 for both cpu and concurrency and scales the number of instances automatically to handle all incoming requests however for some use cases you might want the ability to configure which scaling factors to use such as cpu only and set custom targets for utilization cloud run provides scaling controls to give you more ownership of your service s scaling behaviors letting you make informed decisions about scaling your workload according to your requirements you can opt in for enhanced scaling behavior by retaining the default utilization targets or configure the following custom utilization targets target utilization for cpu based scaling target utilization for concurrency based scaling with scaling controls you can optimize costs and improve predictability for your services for more information about the default autoscaling behavior of cloud run services see about instance autoscaling in cloud run services configuration limits the following limits apply to custom scaling targets scaling driver default minimum configurable maximum configurable cpu target utilization 60 10 95 concurrency target utilization 60 10 95 opt in for enhanced scaling behavior cloud run s autoscaler responds closely to the targets you configure even for services with a low number of instances consider opting in to this feature for improved scaling predictability even if you intend to keep the default utilization targets of 60 for both cpu and concurrency to opt in you can use the gcloud cli or yaml when you deploy a new revision any configuration change leads to the creation of a new revision subsequent revisions will also automatically get this configuration setting unless you make explicit updates to change it gcloud set the target cpu utilization and the target concurrency utilization values of a given revision by running the following gcloud beta run services update command gcloud beta run services update service scaling cpu target 0 6 scaling concurrency target 0 6 replace service with the name of your service yaml if you are creating a new service skip this step if you are updating an existing service download its yaml configuration gcloud run services describe service format export service yaml add the run googleapis com scaling cpu target and run googleapis com scaling concurrency target attributes apiversion serving knative dev v1 kind service metadata annotations run googleapis com launch stage beta name service spec template metadata annotations run googleapis com scaling cpu target 0 6 run googleapis com scaling concurrency target 0 6 replace service with the name of your service create or update the service using the following command gcloud run services replace service yaml the gcloud run services replace command defaults to using service yaml file if present configure custom targets define custom utilization targets to optimize costs or improve performance for your workloads by configuring specific cpu and concurrency utilization targets within the configuration limits any configuration change leads to the creation of a new revision subsequent revisions will also automatically get this configuration setting unless you make explicit updates to change it you can configure scaling controls using the gcloud cli or yaml when you deploy a new revision gcloud update the target cpu utilization and the target concurrency utilization values of a given revision by running the gcloud beta run services update command to update the target cpu utilization run the following command gcloud beta run services update service scaling cpu target cpu_target replace the following service the name of your service cpu_target the target for cpu utilization specify a value from 0 1 to 0 95 you can only configure up to two digits after the decimal point to update the target concurrency utilization run the following command gcloud beta run services update service scaling concurrency target concurrency_target replace the following service the name of your service concurrency_target the target for concurrency utilization specify a value from 0 1 to 0 95 you can only configure up to two digits after the decimal point to update both the target cpu and the concurrency utilization run the following command gcloud beta run services update service scaling cpu target cpu_target scaling concurrency target concurrency_target replace the following service the name of your service cpu_target the target for cpu utilization specify a value from 0 1 to 0 95 you can only configure up to two digits after the decimal point concurrency_target the target for concurrency utilization specify a value from 0 1 to 0 95 you can only configure up to two digits after the decimal point yaml if you are creating a new service skip this step if you are updating an existing service download its yaml configuration gcloud run services describe service format export service yaml to update the target cpu and concurrency utilization add the run googleapis com scaling cpu target and run googleapis com scaling concurrency target attributes apiversion serving knative dev v1 kind service metadata annotations run googleapis com launch stage beta name service spec template metadata annotations run googleapis com scaling cpu target cpu_target run googleapis com scaling concurrency target concurrency_target replace the following service the name of your service cpu_target the target for cpu utilization specify a value from 0 1 to 0 95 you can only configure up to two digits after the decimal point concurrency_target the target for concurrency utilization specify a value from 0 1 to 0 95 you can only configure up to two digits after the decimal point create or update the service using the following command gcloud run services replace service yaml the gcloud run services replace command defaults to using service yaml file if present disable scaling controls you can disable either cpu utilization or concurrency utilization targets but not both one scaling driver must always be active to opt out of scaling controls restore the default utilization values instead of disabling them when you disable a scaling driver cloud run ignores that metric while making scaling decisions you can disable scaling controls using the gcloud cli or yaml when you deploy a new revision gcloud you can disable either the target cpu utilization or the target concurrency utilization by running the gcloud beta run services update command to scale only by cpu disable the concurrency target by running the following command gcloud beta run services update service scaling concurrency target disabled replace service with the name of your service to scale only by concurrency disable the cpu target by running the following command gcloud beta run services update service scaling cpu target disabled replace service with the name of your service yaml if you are creating a new service skip this step if you are updating an existing service download its yaml configuration gcloud run services describe service format export service yaml to scale only by cpu disable the concurrency target by setting the run googleapis com scaling concurrency target attribute to disabled apiversion serving knative dev v1 kind service metadata annotations run googleapis com launch stage beta name service spec template metadata annotations run googleapis com scaling concurrency target disabled replace service with the name of your service to scale only by concurrency disable the cpu target by setting the run googleapis com scaling cpu target attribute to disabled apiversion serving knative dev v1 kind service metadata annotations run googleapis com launch stage beta name service spec template metadata annotations run googleapis com scaling cpu target disabled replace service with the name of your service create or update the service using the following command gcloud run services replace service yaml the gcloud run services replace command defaults to using service yaml file if present restore to default values when you restore the target cpu or the target concurrency utilization values to default you opt out of the scaling controls feature you can restore scaling controls to default using the gcloud cli or yaml when you deploy a new revision gcloud restore the target cpu utilization and the target concurrency utilization to their defaults by running the gcloud beta run services update command to restore the...
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