Dify on Google Cloud Run

Dify is an open-source LLM application development platform for building production-grade AI applications with a visual workflow builder, RAG pipeline, agent framework, multi-model management, and built-in observability. This module deploys Dify on Cloud Run v2 on top of the App_CloudRun foundation, which provisions and manages the shared Google Cloud infrastructure.

This guide focuses on the cloud services Dify uses and how to explore and operate them from the Google Cloud Console and the command line. For the mechanics common to every Cloud Run application — service identity, ingress and load balancing, scaling and concurrency, CI/CD, Cloud Armor, IAP, Binary Authorization, VPC Service Controls, backups, and the deployment lifecycle — refer to the App_CloudRun foundation guide rather than repeating them here.

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What Dify costs on RAD, and how that compares

Dify on RAD's Cloud Run module costs about US$102 a month in a Google Cloud project you own, plus a one-time 175-credit module fee (US$17.50). Dify is a visual builder for production LLM applications, with a RAG pipeline, agent framework and built-in observability. GKE Autopilot suits Dify that must stay up, scale across pods, or run beside other Kubernetes workloads; for the lowest cost, this Cloud Run module is usually the right pick — see the GKE guide if you need the other.

If Dify is only needed occasionally — a demo, a trial, a seasonal or study workload — a RAD-managed project can be deleted and restored within 30 days for a handful of credits, so that US$102 becomes a few dollars a month instead. See Pause it for free, below.

What you pay on RAD

	In a Google Cloud project you own	In a project RAD manages for you
Module fee, once per deployment	175 credits (US$17.50 at the top-up price)	157.5 credits (10% lower)
Build time	A few credits per build (roughly 3–6)	The same
Google Cloud running cost	Billed by Google to your own billing account, about US$102 a month for the default configuration (table below)	Metered hourly in credits; RAD publishes 32 credits a day, about 960 a month (about US$96 at the top-up price)
Who owns what	You own the project and its billing; RAD deploys and updates it	RAD owns the project, with guardrails, quotas and budget alerts; you get console access, and a minimum purchased balance is held in reserve

10 credits cost US$1 on a one-off top-up, less on a plan. In a project RAD manages, the database, file server and network are shared by every application in the project, so a second application does not add a second database.

Default running cost in your own project (us-central1, Google list prices):

Resource (module default)	Per month
Cloud Run, 2x vCPU / 4 GiB (scaleToZero)	US$31.53
Cloud SQL for PostgreSQL, 1 vCPU / 3.75 GB, zonal, 10 GB SSD	US$51
NFS/cache file server (small VM)	US$13.43
Cloud NAT and networking	US$5
Cloud Storage (add-ons, backups)	US$1
Total	about US$102

How it compares

• The project's own managed offering, Dify Cloud, has a free Sandbox plan, then $590 per workspace a year (about $49 a month) on Professional and $1,590 per workspace a year (about $133 a month) on Team.
• Run it yourself and a VPS running Dify's API, worker and web containers plus PostgreSQL yourself costs less in cash: sized to roughly 2 vCPU/4 GiB, a comparable VPS (Hetzner or DigitalOcean) runs about $24–48 a month, or a GCP e2-standard-2-class VM about $49 — plus your own time for backups, security patches and upgrades, which RAD's managed Cloud SQL, Secret Manager and monitoring cover for you.
• RAD never claims to be cheaper than bare infrastructure in cash terms — it usually is not. The difference is what RAD manages for you: patching, backups, secrets and monitoring, plus the ability to pause Dify for free rather than paying for idle capacity (see below).
• Most of the running cost above is the managed PostgreSQL database (and, where used, the shared file server) — the part a bare VPS comparison has to run and back up by hand.

Pause it for free: delete a RAD-managed project, restore it when you need it

If Dify runs in a project RAD manages for you, you have a second option that goes well beyond scaling to zero: delete the whole project, and restore it within 30 days for close to nothing. This suits Dify that you only need occasionally far better than running it continuously.

• How it works. Deleting a RAD-managed project unlinks its billing first, then asks Google to delete the project. Google does not remove the project immediately: it keeps it, recoverable, for 30 days. Because billing is already unlinked, nothing is charged while it waits. Unlike deleting one module, this does not tear down Cloud SQL, the VM or Cloud Run resources one by one — the whole project, and everything in it, simply stops.
• Restoring costs a handful of credits, not a rebuild. Within 30 days, the project's owner can restore it. RAD asks Google to undelete the project and reattaches its billing account, then asks you to run Update on each deployment to confirm everything came back. Because nothing was individually destroyed, that Update finds the same resources already there — it is a check, not a rebuild, and an Update never charges the module fee again. That is a handful of credits (under US$1) in total for a typical Dify chain, against the 180 credits a full redeploy costs.
• So a month of occasional use can cost a few dollars, not US$102. Deploy Dify, use it, delete the project. Restore it next time you want it, confirm with Update, and delete it again when you're done. You pay only for the module fee once, the builds, and whatever hours it was actually live.
• What this needs. You must own the project (not a bring-your-own one RAD only manages billing for), and you restore it yourself within the 30 days — after that, Google deletes it for good. Restoring is admitted like creating a new project: your purchased credit balance must still clear the tier's floor (100 credits for the sandbox tier most study and demo use fits). Google says most services are fully working again within 36 hours of a restore.
• One real gap: the backup bucket does not survive. Nightly backups are written to a bucket inside the project, and that bucket is not protected by Cloud Storage's soft-delete, so it is very likely gone as soon as you delete the project — even though the project itself is recoverable for 30 days. If you have customised Dify and want to keep that work, copy a backup out (to Google Drive, or a bucket outside the project) before you delete. For a default installation with nothing irreplaceable in it, this does not matter.

Pay only while you use it, the other way: delete and redeploy

Cloud Run already scales to zero between requests. The option above only applies to a RAD-managed project; in your own project, or once the 30-day window has passed, the way to stop paying is to delete the deployment and deploy it again when you need it.

• What a redeploy costs. The module fee again plus the builds: about 180 credits (US$18) in your own project. Deleting saves money only once Dify would otherwise sit unused for about 6 days or more, whether in your own project or a RAD-managed one.
• Most of the running cost is usually the database and the shared file or cache server. They stop only when nothing else in the project uses them, so deleting Dify while something else shares the project saves only this app's own compute part.
• Keep your data first. Nightly backups are written to a bucket inside the deployment and are deleted with it, so copy the latest backup out before deleting if you want to keep it.
• Note your settings. RAD does not recreate a deleted deployment for you; you enter the settings again when you deploy.

Lab sessions and Managed Environments

• Lab sessions, for training. A trainer runs a session for a class. Each participant gets the app in their own Google Cloud project for 15 minutes to 24 hours, within an allowance the trainer sets. Either the trainer funds every place, or each participant pays for their own. Everything is deleted when the session ends and unused credits go back to the trainer.
• Managed Environments, for consultancies. A partner runs the app for a client from a ring-fenced wallet it funds, and settles with the client directly. If the wallet runs low, billing pauses and the data is kept, so nobody receives an unexpected charge. At the end the partner hands the project over and the deployments become the client's own.

Credits can be bought in more than 20 currencies, including XAF, XOF, NGN, GHS, KES and ZAR, by card, bank transfer or mobile money.

Sources (8 October 2026): Google Cloud list prices from the Cloud Billing Catalog API; RAD's own fees and daily-credit estimates from radmodules.dev/pricing; Delete and restore projects for the 30-day recovery window and what it says about Cloud Storage objects without soft delete; Dify Cloud. Prices change; check each source before relying on a figure.

1. Overview

Dify runs as a Python/Flask API container (with an embedded Celery worker under supervisord) plus a separate Next.js web frontend service. The deployment wires together a focused set of Google Cloud services:

Capability	Google Cloud service	Notes
Compute	Cloud Run v2 (gen2)	API+worker service (2 vCPU / 4 GiB by default) + web frontend service, request-based autoscaling
Database	Cloud SQL for PostgreSQL 15	Required — pgvector extension enabled for vector storage
Vector store	pgvector (in-database)	Reuses the Cloud SQL instance; no separate vector database needed
Shared files	Filestore (NFS)	Provides the default Redis host (NFS server VM co-hosts Redis)
Object storage	Cloud Storage	A dedicated storage bucket (gcs-dify<tenant-prefix>-storage) for uploaded files and assets
Cache & task queue	Redis	Required for Celery broker/backend and SSE/WebSocket LLM streaming
Secrets	Secret Manager	Auto-generated SECRET_KEY and database password
Ingress	Cloud Run URL / Cloud Load Balancing	Default run.app URL, optional external HTTPS load balancer + custom domain

Sensible defaults worth knowing up front:

• PostgreSQL 15 is mandatory. MySQL and NONE are not supported; Dify requires PostgreSQL for all metadata, workflow state, and user accounts.
• pgvector is always enabled. The vector extension is installed on the Cloud SQL instance automatically, making the same database instance the vector store — no extra service required.
• Redis is required. Celery (workflow execution, document indexing, async LLM calls) and the SSE/WebSocket event bus both depend on Redis. Disabling it breaks all background processing.
• NFS is enabled by default. The NFS server VM hosts the Redis process when no external Redis host is set. Requires gen2 execution environment.
• A web frontend service is deployed automatically. A langgenius/dify-web Cloud Run service is wired to the API service URL — you do not need to configure it separately. Access Dify through the web_url output.
• SECRET_KEY is auto-generated and stored in Secret Manager; it signs Dify sessions and must never be changed after first deployment.
• Database migrations run on every instance start (via MIGRATION_ENABLED=true), so version upgrades apply schema changes automatically.
• gen2 execution environment is required for NFS mounts and GCS Fuse volumes.

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2. Google Cloud Services & How to Explore Them

All commands assume PROJECT and REGION are set. Service and resource names are reported in the deployment Outputs.

A. Cloud Run — the Dify services

Dify runs as two Cloud Run v2 services: the API+worker service (Flask/gunicorn + Celery via supervisord) and the web frontend (Next.js). Each deployment creates an immutable revision; traffic can be split across revisions for safe rollouts.

• Console: Cloud Run → select the API service or the web service for revisions, traffic, logs, and metrics.
• CLI:

  gcloud run services list --project "$PROJECT" --region "$REGION"
  gcloud run services describe <service-name> --project "$PROJECT" --region "$REGION"
  gcloud run revisions list --service <service-name> --project "$PROJECT" --region "$REGION"

See App_CloudRun for scaling, concurrency, execution environment, and traffic splitting.

B. Cloud SQL for PostgreSQL 15

Dify stores all application data (workflows, knowledge bases, user accounts, API keys) in a managed Cloud SQL for PostgreSQL 15 instance. The service connects privately through the Cloud SQL Auth Proxy over a Unix socket — no public IP is exposed. On first deploy an initialization Job creates the application database and user. The pgvector extension is installed automatically so the same instance serves as the vector store.

• Console: SQL → select the instance for connections, backups, flags, metrics.
• CLI:

  gcloud sql instances list --project "$PROJECT"
  gcloud sql instances describe <instance-name> --project "$PROJECT"
  gcloud sql connect <instance-name> --user=<db-user> --project "$PROJECT"

The instance name, database, user, and password secret are in the Outputs. See App_CloudRun for the connection model, backups, and password rotation.

C. Filestore (NFS) and Cloud Storage

A Filestore (NFS) share is mounted into the service. The NFS server VM also runs the Redis process used as the Celery broker when no external Redis host is configured. A dedicated Cloud Storage bucket (gcs-dify<tenant-prefix>-storage) is provisioned for uploaded files and assets; Dify's google-storage driver accesses it via the Cloud Run service identity — no service account key file is needed.

• Console: Filestore → Instances; Cloud Storage → Buckets.
• CLI:

  gcloud filestore instances list --project "$PROJECT"
  gcloud storage buckets list --project "$PROJECT"
  gcloud storage ls gs://<storage-bucket>/

See App_CloudRun for the NFS mount, GCS Fuse, and CMEK.

D. Redis — Celery and event bus

Redis is required for three functions in Dify:

Role	Redis DB	Purpose
Celery broker & backend	db 1	Queues and tracks all background tasks (LLM inference, document indexing)
Event bus	db 0	SSE/WebSocket streaming for real-time LLM output
General cache	db 0	Application caching

When no external Redis host is configured, the NFS server VM IP is used as the Redis endpoint. For production, point redis_host at a dedicated Memorystore for Redis instance.

• Console: Memorystore → Redis (if using a managed instance).
• CLI:

  redis-cli -h <redis-host> ping
  redis-cli -h <redis-host> info keyspace

E. Secret Manager

The Dify SECRET_KEY (used for JWT signing and session encryption) and the database password are stored in Secret Manager and injected into the service at runtime. The SECRET_KEY is generated once and must not be rotated while the deployment is running.

• Console: Security → Secret Manager.
• CLI:

  gcloud secrets list --project "$PROJECT"
  gcloud secrets versions access latest --secret=<secret-name> --project "$PROJECT"

See App_CloudRun for injection and rotation details.

F. Networking & ingress

The API service is reachable at its run.app URL by default; open the web_url output in a browser for the Dify console. An external HTTPS load balancer with a custom domain, Cloud CDN, and Cloud Armor can be layered on.

• Console: Cloud Run (service URL); Network services → Load balancing.
• CLI:

  gcloud run services describe <service-name> --region "$REGION" --format='value(status.url)'
  gcloud compute addresses list --project "$PROJECT"

See App_CloudRun.

G. Cloud Logging & Monitoring

Container logs flow to Cloud Logging; Cloud Run and Cloud SQL metrics flow to Cloud Monitoring, with optional uptime checks and alert policies.

• Console: Logging → Logs Explorer; Monitoring → Dashboards / Alerting.
• CLI:

  gcloud run services logs read <service-name> --project "$PROJECT" --region "$REGION" --limit 50

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3. Dify Application Behaviour

• First-deploy database setup. An initialization Job (db-init) connects to Cloud SQL via the Auth Proxy and idempotently creates the Dify database user and database. It runs automatically on first deploy and is safe to re-run.
• Migrations on start. Each instance runs Dify's Flask-Migrate database migrations on startup (MIGRATION_ENABLED=true), so upgrading the application version applies schema changes automatically. No separate migration job is needed.
• API + worker in one container. The custom container wraps langgenius/dify-api with supervisord. Both the gunicorn API server (port 5001) and the Celery worker run inside the same container — they share the CPU and memory allocation. Size accordingly: 2 vCPU and 4 GiB is the recommended minimum.
• Web frontend. A langgenius/dify-web Cloud Run service is deployed automatically and wired to the API service's computed (predicted) Cloud Run URL via CONSOLE_API_URL/APP_API_URL. Access Dify through the web_url output.
• LLM provider API keys. Provider keys (OpenAI, Anthropic, etc.) are configured per-workspace via the Dify web console and stored in the application database. Use secret_environment_variables only for environment-level configuration that cannot be set in the UI.
• CORS. WEB_API_CORS_ALLOW_ORIGINS and CONSOLE_CORS_ALLOW_ORIGINS default to "*". Restrict to your domain via environment_variables in production.
• Health path. Startup and liveness probes target /health with a 30-second initial delay. Both HTTP probes work correctly on Cloud Run because the Dify API serves port 5001 without TLS/redirect complications (unlike PHP-based apps). The startup probe allows up to 30 × 10 = 300 seconds for first-boot setup.

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4. Configuration Variables

Variables are grouped exactly as they appear on the deployment platform. Only settings specific to or notable for Dify are listed; every other input is inherited from App_CloudRun with its standard behaviour.

Group 1 — Project & Identity

Variable	Default	Description
project_id	(required)	Target Google Cloud project.
region	us-central1	Region for the service and regional resources.

Group 2 — Deployment Environment

Variable	Default	Description
tenant_id	demo	Short suffix that makes resource names unique per environment.
support_users	[]	Emails granted project access and monitoring alerts.
resource_labels	{}	Labels applied to all resources.

Group 3 — Application Identity

Variable	Default	Description
application_name	dify	Base name for resources. Do not change after first deploy.
display_name	Dify - LLM Application Platform	Friendly name shown in the Console.
description	(set)	Service description.
application_version	0.15.0	Dify image version tag; applies to both API and web containers. Pin to a specific version in production.

Group 4 — Runtime & Scaling

Variable	Default	Description
deploy_application	true	Set false to provision infrastructure only.
cpu_limit	2000m	CPU per instance; 2 vCPU minimum — gunicorn and Celery share this allocation.
memory_limit	4Gi	Memory per instance; 4 GiB recommended for LLM workflow caching and document processing.
min_instance_count	0	Minimum instances (scale-to-zero). Set ≥ 1 so the Celery worker maintains its Redis broker connection.
max_instance_count	3	Maximum instances. Acts as a cost ceiling.
cpu_always_allocated	false	Cost-first cold-start default (request-based billing, paired with min_instance_count=0): CPU is billed only while serving a request. Trade-off — Celery async pipelines (dataset embedding, scheduled/batch jobs) stop while scaled to zero; interactive chat and apps still work on-request. Set true together with min_instance_count >= 1 to restore continuous operation.
container_port	5001	Dify API server listens on port 5001.
execution_environment	gen2	Required — gen2 is needed for NFS mounts and GCS Fuse.
timeout_seconds	300	Max request duration. Increase to 3600 for long-running LLM workflows.
enable_cloudsql_volume	true	Cloud SQL Auth Proxy sidecar for Unix socket connections. Required for database connectivity.
traffic_split	[]	Canary/blue-green traffic allocation across revisions. All entries must sum to 100.

Group 5 — Access & Ingress Control

Variable	Default	Description
ingress_settings	all	all (public), internal, or internal-and-cloud-load-balancing.
vpc_egress_setting	PRIVATE_RANGES_ONLY	Routes only RFC 1918 traffic via the VPC connector.
enable_iap	false	Require Google sign-in via Identity-Aware Proxy.
iap_authorized_users / iap_authorized_groups	[]	Who may access through IAP.

Group 6 — Environment Variables & Secrets

Variable	Default	Description
environment_variables	{}	Extra non-secret settings. Use to override WEB_API_CORS_ALLOW_ORIGINS, LOG_LEVEL, etc.
secret_environment_variables	{}	Map of env var → Secret Manager secret name. Use for LLM provider API keys.
secret_propagation_delay / secret_rotation_period	(set)	Replication wait / rotation cadence.

Group 7 — Backup & Restore

Variable	Default	Description
backup_schedule	0 2 * * *	Automated backup cron (UTC).
backup_retention_days	7	Retention; raise for production/compliance.
enable_backup_import / backup_source / backup_uri / backup_format	restore options	Restore from a backup on deploy.

Group 8 — CI/CD & Binary Authorization

Standard App_CloudRun Cloud Build / Cloud Deploy integration — see App_CloudRun. Key inputs: enable_cicd_trigger, github_repository_url, github_token, enable_cloud_deploy, enable_binary_authorization.

Group 9 — NFS Instance & Custom SQL

Variable	Default	Description
nfs_instance_name / nfs_instance_base_name	(set)	Existing NFS instance / base name for an inline one.
enable_custom_sql_scripts / custom_sql_scripts_bucket / custom_sql_scripts_path / custom_sql_scripts_use_root	off	Run SQL from a GCS bucket after provisioning. See App_CloudRun.

Group 10 — Domain, CDN, Cloud Armor & Image Retention

Variable	Default	Description
application_domains	[]	Custom hostnames for the external load balancer.
enable_cdn	false	Enable Cloud CDN on the LB backend. Requires enable_cloud_armor = true.
enable_cloud_armor / admin_ip_ranges	off	Attach a WAF policy / restrict privileged access.
max_images_to_retain / delete_untagged_images / image_retention_days	(set)	Artifact Registry cleanup policy.

Group 11 — Storage & Filesystem

Variable	Default	Description
enable_nfs	true	Shared Filestore volume; also provides the default Redis host. Requires gen2.
nfs_mount_path	/mnt/nfs	Mount path inside the container.
create_cloud_storage / storage_buckets / gcs_volumes	(set)	Additional buckets / GCS Fuse mounts. The storage bucket (gcs-dify<tenant-prefix>-storage) is always provisioned.
manage_storage_kms_iam / enable_artifact_registry_cmek	false	CMEK options.

Group 12 — Database Backend

Variable	Default	Description
database_type	POSTGRES_15	Required — do not change. Dify supports PostgreSQL only.
db_name	dify_db	Database name. Immutable after first deploy.
db_user	dify_user	Application user. Immutable after first deploy.
database_password_length	32	Generated password length (16–64).
enable_auto_password_rotation / rotation_propagation_delay_sec	off	DB password rotation.
db_host_env_var_name / db_name_env_var_name / db_user_env_var_name / db_port_env_var_name / service_url_env_var_name	(set)	Names under which connection details are injected (optional overrides).

Group 13 — Jobs & Scheduled Tasks

Variable	Default	Description
initialization_jobs	[]	Leave empty to use the built-in db-init job. Provide a non-empty list to replace it entirely.
cron_jobs	[]	Recurring jobs triggered by Cloud Scheduler.

Group 14 — Observability & Health

Variable	Default	Description
startup_probe / startup_probe_config	HTTP /health, 30 s delay	Startup probe — container receives no traffic until /health returns 200.
liveness_probe / health_check_config	HTTP /health	Liveness probe.
uptime_check_config	disabled, path /health	Cloud Monitoring uptime check; set enabled = true to provision it.
alert_policies	[]	Metric alert policies.

Group 21 — Redis Cache

Variable	Default	Description
enable_redis	true	Required. Enables Redis for Celery task queue and SSE/WebSocket streaming.
redis_host	""	Leave empty to use the NFS server IP; set for an external Memorystore instance.
redis_port	6379	Redis port.
redis_auth	""	Optional Redis auth password (sensitive).

Group 22 — VPC Service Controls & Audit Logging

Variable	Default	Description
enable_vpc_sc	false	Enforce a VPC-SC perimeter (requires organization_id).
vpc_cidr_ranges / vpc_sc_dry_run	(set)	Access level CIDRs / dry-run mode.
enable_audit_logging	false	Detailed Cloud Audit Logs.

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5. Outputs

Returned on a successful deployment — the quickest way to locate and explore the running resources.

Output	Description
service_name	Cloud Run service name (Dify API).
web_url	URL of the Dify web frontend — open this in a browser to access the Dify console.
api_url	URL of the Dify API service (consumed by the web UI and external integrations).
service_location	Region the service runs in.
stage_services	Stage-specific service URLs (Cloud Deploy).
load_balancer_ip / load_balancer_url	External HTTPS load balancer IP / URL (when enabled).
database_instance_name	Cloud SQL instance name.
database_name / database_user	Application database name / user.
database_password_secret	Secret Manager secret holding the DB password.
database_host / database_port	DB endpoint / port.
storage_buckets	Created Cloud Storage buckets.
network_name / network_exists / regions	VPC network, presence, regions.
container_image / container_registry	Deployed image and Artifact Registry repo.
monitoring_enabled / monitoring_notification_channels / uptime_check_names	Monitoring status, channels, uptime checks.
initialization_jobs	Names of the setup jobs.
deployment_id / tenant_id / resource_prefix	Naming identifiers.
project_id / project_number	Project identifiers.
cicd_enabled / github_repository_url / github_repository_owner / github_repository_name / cicd_configuration	CI/CD status and details.
artifact_registry_repository / cloudbuild_trigger_name / cloudbuild_trigger_id	Registry and build trigger.
vpc_sc_enabled / vpc_sc_perimeter_name / vpc_sc_dry_run_mode	VPC-SC status.
audit_logging_enabled / artifact_registry_cmek_enabled	Audit logging and CMEK status.

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6. Configuration Pitfalls & Sensible Defaults

Risk: Critical (data loss / outage / security) — High (service degraded) — Medium (cost or partial degradation) — Low (minor).

Setting	Sensible value	Risk	Consequence if wrong
enable_redis	true (required)	Critical	All Celery tasks (workflow execution, document indexing, async LLM calls) fail silently without Redis.
enable_cloudsql_volume	true (required)	Critical	The Auth Proxy sidecar is the only path to PostgreSQL; disabling it breaks all database connectivity.
SECRET_KEY (auto-generated)	immutable once set	Critical	All instances must share the same key; rotating it logs out all users and invalidates active sessions.
db_name / db_user	set once	Critical	Immutable after first deploy; renaming recreates the database and destroys data.
enable_backup_import	false unless restoring	Critical	Enabling without a valid backup_uri fails the import job.
secret_environment_variables for LLM keys	always use secret refs	Critical	Plain env vars expose API keys in Cloud Run revision metadata visible in the Console.
enable_redis + enable_nfs	both true if no external Redis	Critical	Without NFS, there is no Redis host when redis_host is empty — Celery fails to start.
redis_host	correct host	High	Incorrect host produces a malformed Celery broker URL; all async tasks queue indefinitely.
database_type	POSTGRES_15	High	Dify requires PostgreSQL; any other engine fails startup.
memory_limit	4Gi	High	Too little memory causes OOM kills during document ingestion or LLM workflow caching.
min_instance_count + cpu_always_allocated	ship 0 / false (cost-first); set 1+ / true for continuous Celery	High	The shipped defaults are a deliberate cost-first choice, not an oversight: scale-to-zero abandons in-flight Celery tasks (dataset embedding, scheduled/batch jobs) while the service is idle. Interactive chat and apps still work on-request. Override both settings together to restore continuous background processing.
timeout_seconds	300 (raise for workflows)	High	Multi-step workflows and RAG indexing can exceed 300 s; increase to 3600 for complex deployments.
execution_environment	gen2	High	gen1 does not support NFS mounts or GCS Fuse.
WEB_API_CORS_ALLOW_ORIGINS	restrict in production	High	Default "*" allows cross-origin requests from any domain.
application_version	pin to a specific version	Medium	Unpinned versions risk unexpected schema migrations that break the application on redeploy.
enable_iap / enable_cloud_armor	enable for production	Medium	The Dify console is publicly reachable without these controls.

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For the foundation behaviour referenced throughout — service identity, scaling and concurrency, ingress and load balancing, CI/CD, Cloud Armor, IAP, Binary Authorization, VPC-SC, backups, and image mirroring — see App_CloudRun. Dify-specific application configuration shared with the GKE variant is described in Dify_Common.

Related guides

• Hands-on lab: Dify on Cloud Run — deploy it step by step, with the console screens and commands at each stage.
• Dify on GKE Autopilot — the same application on Kubernetes, for when you need the other deployment target.
• Dify Common — Shared Application Configuration — the configuration shared by both deployment targets.
• Deployed alongside LiteLLM on Google Cloud Run, Qdrant on Google Cloud Run, Crawl4AI on Google Cloud Run, Langfuse on Google Cloud Run in the AI Application Builder solution.