Activepieces on Google Cloud Run

Activepieces is an open-source, Apache 2.0-licensed no-code workflow automation platform for connecting apps, APIs, and data sources. This module deploys Activepieces 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 Activepieces 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 Activepieces costs on RAD, and how that compares

Activepieces on RAD's Cloud Run module costs about US$83 a month in a project you own, with no licence fee for the software itself. RAD charges a one-off module fee of 75 credits (US$7.50 at the top-up price) in a project you own, and 67.5 credits (10% lower) in a project RAD manages. If Activepieces needs to run continuously across pods or beside other Kubernetes workloads, see the GKE guide instead. Figures are as at 8 October 2026; sources are listed at the end of this section.

If you only need it occasionally — studying for a certification, a demo, a seasonal need — a RAD-managed project can be deleted and restored within 30 days for a handful of credits, so that about US$83 a month becomes close to nothing instead. See Pause it for free, below.

What you pay on RAD

You pay for three things:

	In a Google Cloud project you own	In a project RAD manages for you
Module fee, once per deployment	75 credits (US$7.50 at the top-up price)	67.5 credits (10% lower)
Build time	A few credits, metered per minute of build time	The same
Google Cloud running cost	Billed by Google to your own billing account, about US$83 a month for the default configuration (table below)	Metered hourly in credits; RAD publishes 37 credits a day, about 1,110 a month (about US$111 at the top-up price, US$89 at the Scale plan's rate)
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, and less on a monthly plan. In a project RAD manages, the database is shared by every application in the project, so a second application does not add a second one.

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

Resource (module default)	Per month
Cloud Run, 2x vCPU / 2 GiB (warm)	US$26.28
Cloud SQL for PostgreSQL, 1 vCPU / 3.75 GB, zonal, 10 GB SSD	US$51.02
Cloud NAT and networking	US$5
Cloud Storage (add-ons, backups)	US$1
Total	about US$83

How it compares

• Zapier's own Professional plan starts at $29.99/month (monthly billing) for 750 tasks and rises with volume — $58.50/month for 1,500 tasks, $73.50/month for 2,000, up to several thousand dollars a month at high volume; its Team plan (which Activepieces' shared, multi-user workspace is closer to) starts at $103.50/month for 2,000 tasks/month.
• RAD runs the open-source project itself, not a vendor's hosted tenancy. You get the same software, under your own (or RAD's) infrastructure, instead of a per-seat or per-usage subscription that grows independently of what you actually use.
• Against a bare self-managed server: Running the same open-source software yourself, a Hetzner CPX22 (2 vCPU/4 GB, about $24/month) or a DigitalOcean 2 vCPU/4 GB Droplet (also $24/month) is roughly the same shape; a GCP Compute Engine e2-standard-2 (2 vCPU/8 GB) runs about $49/month. RAD is not cheaper than that in cash terms — the difference is the managed database, Secret Manager and monitoring that come with the module instead of being your own job.

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

If Activepieces runs in a project RAD manages for you, you have an option that goes well beyond scaling to zero: delete the whole project, and restore it within 30 days for close to nothing. This suits occasional use — studying for a certification, a demo, a seasonal need — far better than running Activepieces continuously.

• How it works. Deleting a RAD-managed project unlinks its billing first, then asks Google to delete the project outright. Google does not remove it immediately: it keeps the project, recoverable, for 30 days, and because billing is already unlinked nothing is charged while it waits. Unlike deleting one module, this does not tear down the database, any VM or the compute resource one by one — the whole project simply stops, and nothing is billed in the meantime.
• Restoring costs a handful of credits, not a rebuild. Within 30 days, only 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. This costs only a handful of credits in total (under US$1), against paying the module fee and a full build again.
• What this needs. You must own the project (not one RAD only manages billing for), you must restore it yourself within the 30 days — after that Google deletes it for good — and restoring is admitted like creating a new project, so 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: backups do not survive. Anything Activepieces writes to a backup bucket inside the project is very likely gone as soon as you delete the project, even though the project itself is recoverable for 30 days — that bucket has Cloud Storage's soft-delete explicitly turned off. Anyone who has customised the deployment and wants to keep that work should copy a backup out (to Google Drive, or a bucket outside the project) before deleting. For a default install with nothing irreplaceable in it, this does not matter.

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

This is the fallback for a project you own, or once the 30-day restore window above has passed: delete the deployment, and deploy it again when you next need it.

• What a redeploy costs. The module fee again, plus the builds: roughly 80 credits (about US$8) in your own project, or 72.5 credits in a RAD-managed one, because RAD rebuilds the resources from scratch. Deleting saves money once Activepieces would otherwise sit unused long enough to clear that redeploy cost against its own running cost — roughly 3 days or more in your own project (US$2.78/day) or 2 days or more in a RAD-managed one (37 credits/day).
• Most of the running cost is usually shared infrastructure. The database stops only when nothing else in the project uses them, so deleting Activepieces while another application shares the project saves only Activepieces's own compute part.
• Keep your data first. Anything Activepieces writes to a backup bucket inside the deployment is deleted with it — copy the latest backup out (to Google Drive, or a bucket you keep) before deleting if you want to keep it.
• RAD does not recreate a deleted deployment for you. You enter the settings again when you redeploy.

Lab sessions and Managed Environments

• Lab sessions, for training. A trainer runs a session for a class. Each participant gets Activepieces 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 Activepieces 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 fees and daily-credit estimate from radmodules.dev/pricing; Delete and restore projects for the pause/restore mechanics; Zapier pricing. Prices change; check each source before relying on a figure.

1. Overview

Activepieces runs as a Node.js container on Cloud Run v2. The deployment wires together a focused set of Google Cloud services:

Capability	Google Cloud service	Notes
Compute	Cloud Run v2	Node.js service, 2 vCPU / 2 GiB by default, serverless autoscaling; scale-to-zero supported
Database	Cloud SQL for PostgreSQL 15	Required — Activepieces does not support MySQL or other engines
Object storage	Cloud Storage	A dedicated data bucket provisioned automatically
Cache & queue	Redis (optional)	Required for horizontal scaling; memory queue mode is the default
Secrets	Secret Manager	Auto-generated AP_ENCRYPTION_KEY and AP_JWT_SECRET; 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. The database engine is fixed by the shared application layer; selecting any other engine breaks startup.
• Memory queue mode is the default. AP_QUEUE_MODE = MEMORY means all workflow jobs run in-process in a single instance. Scaling beyond one instance requires Redis (enable_redis = true).
• AP_ENCRYPTION_KEY and AP_JWT_SECRET are generated automatically and stored in Secret Manager. These keys must never be rotated after first boot without a maintenance window — rotating AP_ENCRYPTION_KEY corrupts all stored connection credentials, and rotating AP_JWT_SECRET invalidates all active user sessions.
• One instance is kept warm by default (min_instance_count = 1), because Activepieces' scheduler runs in-process. Setting it to 0 enables scale-to-zero, which adds 5–15 seconds of cold-start latency after idle.
• Public ingress is required for webhooks. ingress_settings = "all" is the default so external services can POST to Activepieces webhook endpoints. Enabling IAP will block these external calls.
• NFS is disabled by default. Activepieces stores all workflow state in PostgreSQL. Enable NFS only if co-locating Redis on the NFS server VM.
• The pgvector extension is installed automatically during the first-deploy database setup job, enabling AI-powered workflow pieces.
• AP_FRONTEND_URL and AP_WEBHOOK_URL_PREFIX are set from the predicted service URL at plan time and corrected at runtime by the container entrypoint, ensuring webhook and OAuth redirect URLs always reflect the actual Cloud Run service URL.
• Scheduled/triggered flows need a warm instance — keep min_instance_count = 1. Activepieces ships its own scheduler/worker/cron/queue-style trigger components, which only run while an instance exists, so on a scaled-to-zero service (0) scheduled flows silently never fire. The module therefore defaults to min_instance_count = 1. Note this module does not expose cpu_always_allocated — it is not declared in variables.tf or forwarded to the foundation. Lower the minimum to 0 only for webhook-only or interactive use.

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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 Activepieces service

Activepieces runs as a Cloud Run v2 service that autoscales by request load between the minimum and maximum instance counts. Each deployment creates an immutable revision; traffic can be split across revisions for safe rollouts.

• Console: Cloud Run → select the 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

Activepieces stores all application data (flows, connections, execution history, users) 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 and installs the pgvector extension.

• 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> --database=<db-name> --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. Cloud Storage

A dedicated Cloud Storage data bucket is provisioned automatically for Activepieces file storage. Additional buckets can be declared via storage_buckets.

• Console: Cloud Storage → Buckets.
• CLI:

  gcloud storage buckets list --project "$PROJECT"
  gcloud storage ls gs://<data-bucket>/        # bucket name is in the Outputs

See App_CloudRun for GCS Fuse and CMEK options.

D. Redis (queue mode)

Redis is disabled by default (AP_QUEUE_MODE = MEMORY). When enable_redis = true is set, the queue backend switches to AP_QUEUE_MODE = REDIS, which is required before scaling beyond one instance. When redis_host is left empty and enable_nfs is true, the NFS server VM's IP is used as the Redis endpoint.

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

  redis-cli -h <redis-host> ping
  redis-cli -h <redis-host> info keyspace
  # Confirm queue mode in the running revision:
  gcloud run services describe <service-name> --region "$REGION" \
    --format='value(spec.template.spec.containers[0].env)'

E. Secret Manager

Two cryptographic secrets are generated automatically and stored in Secret Manager: AP_ENCRYPTION_KEY (used to encrypt all stored connection credentials) and AP_JWT_SECRET (used to sign user session tokens). The database password is managed separately by the foundation.

• 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 service is reachable at its run.app URL by default, which allows public access required for webhook endpoints. An external HTTPS load balancer with a custom domain, Cloud CDN, and Cloud Armor can be layered on; ingress settings and VPC egress control connectivity.

• 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. Activepieces Application Behaviour

• First-deploy database setup. An initialization Job runs db-init.sh using postgres:15-alpine. It connects through the Cloud SQL Auth Proxy and idempotently creates the application database and user, grants privileges, and installs the pgvector extension for AI-powered flow pieces. The job is safe to re-run.
• Database migrations on start. Activepieces applies its own schema migrations automatically on every startup, so upgrading the application version applies schema changes without a separate migration step.
• AP_ENCRYPTION_KEY and AP_JWT_SECRET are immutable after first boot. These keys are generated once and written to Secret Manager. Changing AP_ENCRYPTION_KEY permanently corrupts all stored connection credentials. Changing AP_JWT_SECRET invalidates all active user sessions. Only rotate during a planned maintenance window.
• Webhook endpoints. The default ingress_settings = "all" allows external systems to POST to Activepieces webhook URLs. Enabling IAP will block these calls. After deployment, verify AP_FRONTEND_URL and AP_WEBHOOK_URL_PREFIX match the actual service URL. Inspect the running revision:

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

• Sign-up is open by default. AP_SIGN_UP_ENABLED = "true" is injected automatically. After creating the initial administrator account, disable sign-up by adding AP_SIGN_UP_ENABLED = "false" to environment_variables.
• Health path. Startup and liveness probes target /api/v1/flags — the Activepieces flags API endpoint that responds only when the server is fully initialised and connected to PostgreSQL. Allow at least 7 minutes on first boot (the default startup probe provides a 120-second initial delay plus a 300-second retry window).
• Inspect job execution:

  gcloud run jobs list --project "$PROJECT" --region "$REGION"
  gcloud run jobs executions list --job <job-name> --project "$PROJECT" --region "$REGION"

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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 Activepieces 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	activepieces	Base name for resources. Do not change after first deploy.
display_name	Activepieces Workflow Automation	Human-readable name shown in the Console.
description	(set)	Service description.
application_version	latest	Deployment-tracking tag for the built image. Does not pin the upstream release: Activepieces_Common's Dockerfile always builds FROM activepieces/activepieces:latest with no version ARG, so changing this value only relabels the pushed Artifact Registry tag.

Group 4 — Runtime & Scaling

Variable	Default	Description
deploy_application	true	Set false to provision infrastructure only.
cpu_limit	2000m	CPU per instance; 2 vCPU recommended.
memory_limit	2Gi	Memory per instance; minimum 1 GiB.
min_instance_count	1	0 enables scale-to-zero; set 1 to avoid cold starts on webhooks.
max_instance_count	1	Only increase when enable_redis = true.
container_port	8080	Activepieces listens on port 8080.
execution_environment	gen2	Gen2 required for NFS and GCS Fuse mounts.
timeout_seconds	300	Maximum request duration (0–3600 seconds).
enable_cloudsql_volume	true	Cloud SQL Auth Proxy for socket connections.
enable_image_mirroring	true	Mirror the Activepieces image into Artifact Registry.
traffic_split	[]	Split traffic across revisions for staged rollouts.
max_revisions_to_retain	7	Declared for convention parity; not referenced by this module's deployment.

Group 5 — Access & Ingress Control

Variable	Default	Description
ingress_settings	all	all is required for public webhook endpoints.
vpc_egress_setting	PRIVATE_RANGES_ONLY	Route only RFC 1918 traffic via VPC.
enable_iap	false	Require Google sign-in. Blocks public webhook endpoints.
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. Core AP_* values are set automatically — do not set AP_ENCRYPTION_KEY, AP_JWT_SECRET, or AP_POSTGRES_* here.
secret_environment_variables	{}	Map of env var → Secret Manager secret name.
secret_propagation_delay	30	Seconds to wait after secret creation before proceeding.
secret_rotation_period	2592000s	Secret Manager rotation notification frequency.

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 — Load Balancer, CDN & Image Retention

Variable	Default	Description
enable_cloud_armor	false	Provision Global HTTPS LB + Cloud Armor WAF.
admin_ip_ranges	[]	CIDR ranges exempted from WAF rules.
application_domains	[]	Custom domain names for the HTTPS LB.
enable_cdn	false	Enable Cloud CDN on the HTTPS LB backend.
max_images_to_retain / delete_untagged_images / image_retention_days	(set)	Artifact Registry cleanup policy.

Group 10 — Storage & Filesystem

Variable	Default	Description
create_cloud_storage	true	Create GCS buckets defined in storage_buckets.
storage_buckets	[]	Additional GCS buckets beyond the auto-provisioned data bucket.
enable_nfs	false	NFS is off by default; enable only if co-locating Redis on the NFS server.
nfs_mount_path	/mnt/nfs	Mount path inside the container.
gcs_volumes	[]	GCS Fuse volume mounts (requires gen2).
manage_storage_kms_iam / enable_artifact_registry_cmek	false	CMEK options.

Group 11 — Custom SQL Scripts

enable_custom_sql_scripts, custom_sql_scripts_bucket, custom_sql_scripts_path, custom_sql_scripts_use_root — run SQL from a GCS bucket after provisioning. See App_CloudRun.

Group 12 — Database Backend

Variable	Default	Description
db_name	activepieces_db	PostgreSQL database name. Immutable after first deploy.
db_user	ap_user	Application database user. Password auto-generated in Secret Manager.
database_password_length	32	Generated password length (16–64).
enable_auto_password_rotation / rotation_propagation_delay_sec	off	DB password rotation.

Group 13 — Jobs & Scheduled Tasks

Variable	Default	Description
initialization_jobs	[]	Leave empty to use the built-in db-init job.
cron_jobs	[]	Not forwarded — Activepieces has no platform-scheduled recurring tasks.

Group 14 — Observability & Health

Variable	Default	Description
startup_probe	HTTP /api/v1/flags 120s delay	Startup probe. Allow 7+ minutes on first boot.
liveness_probe	HTTP /api/v1/flags 30s delay	Liveness probe.
startup_probe_config	disabled	Alternative structured probe (disabled by default; startup_probe takes effect).
health_check_config	HTTP /	Alternative structured liveness probe.
uptime_check_config	{ enabled=false, path="/" }	Cloud Monitoring uptime check; disabled by default, enable explicitly to activate.
alert_policies	[]	Metric alert policies.

Group 21 — Redis Cache & Queue

Variable	Default	Description
enable_redis	false	Switch AP_QUEUE_MODE from MEMORY to REDIS. Required when max_instance_count > 1.
redis_host	""	Redis endpoint. Leave empty to use the NFS server IP (requires enable_nfs = true).
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.
service_url	Default run.app URL of the service.
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).

Inherited plan-time validation. This module passes its configuration through the App_CloudRun foundation engine, which validates values and combinations at plan time — a read replica without its primary, IAP with no authorized identities, a gen1 runtime with NFS/GCS mounts, a database_type that does not match an enabled extension, an out-of-range redis_port/backup_retention_days. Invalid configuration fails the plan with a clear, named error before any resource is created, so most mistakes below are caught up front rather than at apply or runtime.

Setting	Sensible value	Risk	Consequence if wrong
AP_ENCRYPTION_KEY (auto-generated)	Never rotate after first boot	Critical	Rotating it permanently corrupts all stored connection credentials — they cannot be decrypted.
AP_JWT_SECRET (auto-generated)	Only rotate in a maintenance window	Critical	Rotating it invalidates all active user sessions, forcing immediate re-login for everyone.
db_name / db_user	Set once	Critical	Immutable after first deploy; renaming recreates the DB/user and destroys all data.
enable_backup_import	false unless restoring	Critical	Enabling without a valid backup_uri fails the import job.
AP_FRONTEND_URL / AP_WEBHOOK_URL_PREFIX	Actual service URL	Critical	Incorrect URL breaks all webhook integrations and OAuth callbacks.
max_instance_count	1 unless Redis enabled	High	Scaling beyond 1 in memory queue mode splits the job queue across instances, causing duplicate executions and lost runs.
enable_redis	true before scaling	High	Without Redis, each instance maintains its own in-memory queue — inconsistent execution with more than 1 instance.
redis_host	"" (NFS) or explicit	High	When Redis is on but NFS is off and no host is set, the Redis connection string is blank and the app fails to start.
memory_limit	2Gi	High	Values below 1 GiB cause OOM kills during concurrent flow executions.
ingress_settings	all	High	Setting to internal blocks all external webhook callbacks.
enable_iap	only when webhooks not needed	High	IAP blocks all unauthenticated requests, including external webhook callbacks.
AP_SIGN_UP_ENABLED (auto-injected "true")	Disable after first admin	High	Leaving sign-up open allows anyone with the URL to create an account.
min_instance_count	1 (the default)	Medium	Scale-to-zero (0) adds 5–15 second cold-start delays on incoming webhooks after idle.
min_instance_count (with Activepieces scheduled/triggered flows enabled)	1 (no cpu_always_allocated override exists)	High	Activepieces' own scheduler/worker/cron components only run while an instance is warm; at min_instance_count = 0 scheduled flows silently never fire, and this module does not expose cpu_always_allocated to force always-on CPU instead.
backup_retention_days	7 (raise for prod)	Medium	Too short for compliance retention.
enable_cloud_armor	enable for production	Medium	Webhook endpoints and the admin UI are publicly reachable without WAF protection.

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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. Activepieces-specific application configuration shared with the GKE variant is described in Activepieces_Common.

Related guides

• Hands-on lab: Activepieces on Cloud Run — deploy it step by step, with the console screens and commands at each stage.
• Activepieces on GKE Autopilot — the same application on Kubernetes, for when you need the other deployment target.
• Activepieces Common — Shared Application Configuration — the configuration shared by both deployment targets.
• Deployed alongside n8n on Google Cloud Run, Node-RED on Google Cloud Run, Ntfy on Google Cloud Run, EvolutionAPI on Google Cloud Run in the Workflow Automation Hub solution.