Flowise on GKE Autopilot

Flowise is an open-source visual AI workflow builder that lets non-developers assemble LangChain and LlamaIndex AI pipelines through a drag-and-drop interface. This module deploys Flowise on GKE Autopilot on top of the App_GKE foundation, which provisions and manages the shared Google Cloud and Kubernetes infrastructure.

This guide focuses on the cloud services Flowise uses and how to explore and operate them from the Google Cloud Console and the command line. For the mechanics that are common to every GKE application — Workload Identity, ingress, autoscaling, CI/CD, Cloud Armor, IAP, Binary Authorization, VPC Service Controls, backups, and the deployment lifecycle — refer to the App_GKE foundation guide rather than repeating them here.

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What Flowise costs on RAD, and how that compares

In a Google Cloud project you own, Flowise on RAD's GKE Autopilot module costs about US$93 a month, plus US$11 once per deployment and no per-user licence. For the lowest cost, the Cloud Run module runs the same Flowise for about US$69 a month. Flowise is an open-source visual AI workflow builder for assembling LangChain and LlamaIndex pipelines by drag and drop. Figures are as at 8 October 2026; sources are listed at the end of this section.

If this runs in a project RAD manages for you, it can be deleted and restored within 30 days for a few credits instead of sitting there running — so an occasional-use deployment costs a few dollars a month, not US$93. 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	110 credits (US$11 at the top-up price)	99 credits (10% lower)
Build time	A few credits per build	The same
Google Cloud running cost	Billed by Google to your own billing account, about US$93 a month for the default configuration (table below)	Metered hourly in credits; RAD publishes 85 credits a day, about 2,550 a month (about US$255 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, and less on a monthly 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
GKE Autopilot pod, 1 vCPU / 1 GiB, running all the time	US$36
Cloud SQL for PostgreSQL, 1 vCPU / 3.75 GB, zonal, 10 GB SSD	US$51
Cloud NAT gateway and IP address	US$5
Cloud Storage for backups	US$1
Total	about US$93

GKE's free tier covers the management fee of one Autopilot or zonal cluster per billing account, so the total above assumes this is that cluster; otherwise add about US$73 a month.

How it compares

Flowise has its own official hosted plan, Flowise Cloud: Flowise's own hosted Cloud plan starts at $35/month (Starter: unlimited flows, 10,000 predictions/month, 1 GB storage); a $65/month Pro plan raises those limits — read 8 October 2026.

Option	Per month	Who runs it
Flowise Cloud, Starter (official hosted plan)	US$35/mo	Flowise
RAD, GKE Autopilot, your own project	US$93, plus US$11 once	RAD's automation, in your project
RAD, GKE Autopilot, a RAD-managed project	about 2,550 credits (US$255)	RAD
RAD, Cloud Run	about US$69; see the Cloud Run guide	RAD

Flowise Cloud's price was read from its own pricing page on 8 October 2026 and may have changed since — check the source before relying on the figure.

• Flowise Cloud is the fixed comparison; a self-managed server is the flexible one. On your own Hetzner or DigitalOcean box (2 vCPU/4GB, about US$24/month) or a GCP Compute Engine e2-standard-2 (2 vCPU/8GB, about US$49/month) you would pay less in cash than either option, but you run the operating system, the database, backups, security patches and upgrades yourself — exactly what RAD's managed Cloud SQL, Secret Manager and monitoring do for you.
• A cheap server is cheap until something breaks. On RAD, backups, point-in-time recovery, password rotation through Secret Manager, and logging and monitoring come from Google Cloud by default. On your own server, or on a fixed-price hosted plan with no infrastructure control, each of those is a job someone still has to do or a limit you cannot change.

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

If Flowise runs in a project RAD manages for you, you have an option beyond scaling down: delete the whole project, and restore it within 30 days for close to nothing. This suits a deployment you only need occasionally — studying for a certification, a demo, a seasonal need — 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 it immediately: it keeps it, 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 Cloud SQL, the VM or GKE Autopilot 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 costs a handful of build-time credits in total (under US$1) for a typical 2–3-deployment chain.
• So a month of occasional use can cost a few dollars, not US$93. Deploy Flowise, use it for a session, 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/demo use fits). Google says most services are fully working again within 36 hours of a restore.
• One real gap: nightly backups do not survive. Backups are written to a bucket inside the project, and that bucket has Cloud Storage's soft-delete explicitly turned off, 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've customised this deployment and want to keep that work, 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

GKE keeps at least one pod running, so Flowise never scales to zero on its own. 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 115 credits (US$11.50). Deleting saves money if Flowise would otherwise sit unused for about 4 days or more in your own project (about US$3.10 a day), or about 2 days or more in a RAD-managed one (85 credits a day).
• Delete everything Flowise uses. Most of the running cost is usually the database and any shared file/cache VM. They stop only when nothing else in the project uses them, so deleting this app while something else shares the project saves only this app's own compute part.
• Keep data first. Nightly backups go 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 Flowise 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 estimate from radmodules.dev/pricing; Delete and restore projects for the pause/restore mechanism; Flowise Cloud pricing. Prices change; check each source before relying on a figure.

1. Overview

Flowise runs as a Node.js container workload. The deployment wires together a focused set of Google Cloud services:

Capability	Google Cloud service	Notes
Compute	GKE Autopilot	Node.js pods, 1 vCPU / 1 GiB by default, horizontally autoscaled
Database	Cloud SQL for PostgreSQL 15	Required — Flowise does not support MySQL in this deployment
Object storage	Cloud Storage	A dedicated uploads bucket always provisioned; stores Flowise file uploads
Secrets	Secret Manager	Auto-generated Flowise admin password
Ingress	Cloud Load Balancing	External LoadBalancer, optional custom domain + managed certificate

Sensible defaults worth knowing up front:

• PostgreSQL 15 is mandatory. The database engine is fixed; selecting MySQL or NONE breaks startup.
• GCS-backed file storage is always enabled. STORAGE_TYPE=gcs and APIKEY_STORAGE_TYPE=db are injected automatically; API keys are stored in the database, not in files.
• Session affinity is ClientIP. Requests from a browser are pinned to one pod to keep the Flowise UI session consistent.
• The admin password is generated automatically and stored in Secret Manager; you never set it in plain text.
• DATABASE_* variables are mapped by the entrypoint script (flowise-entrypoint.sh) from platform-standard DB_* variables at container startup — do not set them directly as environment variables.
• Redis is disabled by default. It is not required for Flowise core functionality, but multi-replica deployments that share flow-execution state do benefit from it.

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2. Google Cloud Services & How to Explore Them

All commands assume you have run gcloud container clusters get-credentials <cluster> --region <region> --project <project> and that PROJECT, REGION, and NAMESPACE are set. The namespace and other identifiers are reported in the deployment Outputs.

A. GKE Autopilot — the Flowise workload

Flowise pods are scheduled on Autopilot, which bills for the CPU/memory the pods actually request. Horizontal Pod Autoscaling sizes the deployment between the minimum and maximum replica counts.

• Console: Kubernetes Engine → Workloads → select the Flowise workload to see pods, revisions, and events. Kubernetes Engine → Services & Ingress shows the external IP.
• CLI:

  kubectl get pods,svc,hpa -n "$NAMESPACE"
  kubectl logs -n "$NAMESPACE" deploy/<service-name> --tail=100
  kubectl describe hpa -n "$NAMESPACE"          # current vs target utilisation

See App_GKE for how Autopilot, scaling, and the workload type (Deployment vs StatefulSet) are managed.

B. Cloud SQL for PostgreSQL 15

Flowise stores all application data (flow definitions, credentials, executions) in a managed Cloud SQL for PostgreSQL 15 instance. Pods reach it privately through the Cloud SQL Auth Proxy sidecar over a Unix socket, so no public IP is exposed. On first deploy an initialization Job creates the application database and user.

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

  gcloud sql instances list --project "$PROJECT"
  gcloud sql instances describe <instance-name> --project "$PROJECT"
  # Open an interactive shell to inspect schema/data:
  gcloud sql connect <instance-name> --user=<db-user> --project "$PROJECT"

The instance name, database name, user, and the Secret Manager secret holding the password are all surfaced in the Outputs. For the connection model, automated backups, and password rotation, see App_GKE.

C. Cloud Storage

A dedicated Cloud Storage uploads bucket is always provisioned by Flowise_Common. Its name is injected into the container automatically as GOOGLE_CLOUD_STORAGE_BUCKET_NAME. Flowise writes all user-uploaded files (documents, images) to this bucket. Additional buckets can be configured via storage_buckets.

• Console: Cloud Storage → Buckets.
• CLI:

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

See App_GKE for GCS Fuse mounts and CMEK options.

D. Secret Manager

The Flowise admin password is stored as a Secret Manager secret and injected into pods at runtime; plaintext never appears in configuration. 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"

The database password secret name is in the Outputs. See App_GKE for the Secret Store CSI integration and rotation.

E. Networking & ingress

By default the workload is exposed through an external Cloud Load Balancing IP. A custom domain with a Google-managed certificate can be enabled, and a static IP can be reserved so the address survives redeploys.

• Console: Network services → Load balancing; VPC network → IP addresses.
• CLI:

  kubectl get ingress,svc -n "$NAMESPACE"
  gcloud compute addresses list --project "$PROJECT"

See App_GKE for custom domains, Cloud CDN, and static IP details.

F. Cloud Logging & Monitoring

Pod stdout/stderr flow to Cloud Logging; GKE and Cloud SQL metrics flow to Cloud Monitoring. Optional uptime checks and alert policies are available.

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

  gcloud logging read 'resource.type="k8s_container" AND resource.labels.namespace_name="'"$NAMESPACE"'"' \
    --project "$PROJECT" --limit 50

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3. Flowise Application Behaviour

• First-deploy database setup. An initialization Job (db-init) using the postgres:15-alpine image creates the Flowise database and user and grants privileges before the application starts. It is idempotent and safe to re-run.
• Health probe. Both startup and liveness probes target Flowise's dedicated health endpoint /api/v1/ping, which returns HTTP 200 when the application is ready. The startup probe allows up to 5 minutes of startup budget (30 failures × 10-second interval) to accommodate first-boot database initialisation.
• Admin login. The initial admin username is configurable via flowise_username (default admin). The admin password is auto-generated and stored in Secret Manager; retrieve it with:

  gcloud secrets versions access latest \
    --secret=<resource_prefix>-flowise-password --project "$PROJECT"

• DB variable remapping. flowise-entrypoint.sh unconditionally maps DB_HOST, DB_USER, DB_NAME, and DB_PASSWORD (injected by the platform) to DATABASE_HOST, DATABASE_USER, DATABASE_NAME, and DATABASE_PASSWORD at container startup. Do not set DATABASE_* variables directly.
• GCS file storage. STORAGE_TYPE=gcs and GCLOUD_PROJECT are always injected. Flowise writes uploaded files to the auto-provisioned GCS bucket. Overriding STORAGE_TYPE causes uploads to be written to ephemeral pod storage and lost on every restart.
• Multi-replica considerations. Flowise stores in-memory flow-execution state. Running more than one replica without Redis causes flow executions to fail when requests are load-balanced to a different pod. Keep max_instance_count = 1 unless Redis is configured.

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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 Flowise are listed; every other input is inherited from App_GKE with its standard behaviour and defaults.

Group 1 — Project & Identity

Variable	Default	Description
project_id	(required)	Target Google Cloud project.
region	us-central1	Region for the workload 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 for cost/ownership tracking.

Group 3 — Application Identity

Variable	Default	Description
application_name	flowise	Base name for resources. Do not change after first deploy.
application_display_name	Flowise	Friendly name shown in the Console.
application_description	(set)	Workload description annotation.
application_version	latest	Flowise image version tag; update to roll out a new release.
flowise_username	admin	Flowise admin username injected as FLOWISE_USERNAME. Change before exposing publicly.

Group 4 — Runtime & Scaling

Variable	Default	Description
deploy_application	true	Set false to provision infrastructure only.
container_image_source	custom	custom builds via Cloud Build; prebuilt deploys an existing image URI.
container_image	""	Override image URI (only used when container_image_source = "prebuilt").
container_resources	{ cpu_limit="1000m", memory_limit="1Gi" }	CPU/memory limits per pod.
min_instance_count	1	Minimum replicas. Keep ≥ 1 to avoid cold starts for AI workflow execution.
max_instance_count	1	Maximum replicas. Increase only with Redis enabled.
container_port	3000	Flowise listens on port 3000.
timeout_seconds	300	Max backend pod response wait. Increase for long-running AI workflows (max 3600).
enable_cloudsql_volume	true	Cloud SQL Auth Proxy sidecar for socket connections.
enable_vertical_pod_autoscaling	false	Let Autopilot tune resource requests automatically.

Group 5 — Environment Variables & Secrets

Variable	Default	Description
environment_variables	{}	Extra non-secret settings. Do not override platform-managed vars (DATABASE_*, FLOWISE_*, STORAGE_TYPE).
secret_environment_variables	{}	Map of env var → Secret Manager secret name (e.g. { OPENAI_API_KEY = "flowise-openai-key" }).
secret_propagation_delay	30	Seconds to wait after secret creation before proceeding.
secret_rotation_period	2592000s	Secret Manager rotation notification frequency.

Group 6 — GKE Backend & Cluster

Variable	Default	Description
gke_cluster_name	""	GKE cluster name. Leave empty for auto-discovery.
service_type	LoadBalancer	How the Service is exposed.
session_affinity	ClientIP	Sticky routing recommended for the Flowise UI.
workload_type	null	Defaults to Deployment for Flowise (stateless).
network_tags	["nfsserver"]	Node/pod tags for firewall rules.

Group 7 — StatefulSet

Only relevant when workload_type = "StatefulSet".

Variable	Default	Description
stateful_pvc_enabled	null	Enable PVC templates in the StatefulSet spec.
stateful_pvc_size	10Gi	Storage size for each PVC.
stateful_pvc_mount_path	/data	Container path where the PVC is mounted.
stateful_pvc_storage_class	standard-rwo	Kubernetes StorageClass for PVCs.

Group 8 — Resource Quota

Variable	Default	Description
enable_resource_quota	false	Cap namespace CPU/memory/object counts.
quota_memory_requests / quota_memory_limits	""	Must use binary units (4Gi, 8192Mi) — bare integers are read as bytes and block all scheduling.

Group 9 — Reliability Policies

Variable	Default	Description
enable_pod_disruption_budget	false	Protect availability during node upgrades.
pdb_min_available	1	Minimum pods available during voluntary disruptions.
enable_topology_spread	false	Spread pods across zones.

Group 10 — Observability & Health

Variable	Default	Description
startup_probe_config	path /api/v1/ping, 30s delay, 30 failures	5-minute startup budget for DB initialisation on first boot.
health_check_config	path /api/v1/ping, 15s delay	Liveness probe.
uptime_check_config	disabled, path /	Cloud Monitoring uptime check from global locations.
alert_policies	[]	Optional metric alert policies.

Group 11 — Jobs & Scheduled Tasks

Variable	Default	Description
initialization_jobs	[]	Leave empty to use the built-in db-init job.
cron_jobs	[]	Scheduled Kubernetes CronJobs.
additional_services	[]	Sidecar or helper GKE services deployed alongside Flowise.

Group 12 — CI/CD & GitHub Integration

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

Group 13 — Filesystem (NFS)

Variable	Default	Description
enable_nfs	false	Provision Filestore NFS volume. Useful for Flowise workflow file uploads when NFS is preferred over GCS.
nfs_mount_path	/mnt/nfs	Mount path inside the container.

Group 14 — Cloud Storage & Artifact Registry

Variable	Default	Description
create_cloud_storage	true	Provision the additional buckets in storage_buckets. The Flowise uploads bucket is always created by Flowise_Common.
storage_buckets	[{ name_suffix="data" }]	Additional GCS buckets to provision.
gcs_volumes	[]	GCS Fuse volume mounts.
manage_storage_kms_iam / enable_artifact_registry_cmek	false	CMEK options.

Group 15 — Redis (optional)

Variable	Default	Description
enable_redis	false	Enable Redis. Not required for core functionality; needed for multi-replica deployments.
redis_host	""	Redis endpoint. Required when enable_redis = true (or enable_nfs = true uses the NFS host IP).
redis_port	6379	Redis port.
redis_auth	""	Optional Redis auth password (sensitive).

Group 16 — Database Backend

Variable	Default	Description
database_type	POSTGRES_15	Cloud SQL engine. Flowise requires PostgreSQL.
application_database_name	flowisedb	Database name. Immutable after first deploy.
application_database_user	flowiseuser	Application user. Immutable after first deploy.
database_password_length	32	Generated password length (16–64).
enable_postgres_extensions	false	Enable installation of PostgreSQL extensions.
postgres_extensions	[]	List of PostgreSQL extensions to install.
enable_auto_password_rotation	false	Zero-downtime DB password rotation.

Group 17 — Backup & Maintenance

Variable	Default	Description
backup_schedule	0 2 * * *	Automated backup cron (UTC).
backup_retention_days	7	Retention; raise to 30–90 for production/compliance.
enable_backup_import / backup_source / backup_file / backup_format	restore options	Restore from a backup on deploy.

Group 18 — 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_GKE.

Group 19 — Custom Domain, Static IP & Networking

Variable	Default	Description
enable_custom_domain	true	Provision Ingress for custom hostnames + managed certificate.
application_domains	[]	Hostnames to serve (e.g. ["flowise.example.com"]).
reserve_static_ip	true	Stable external IP across redeploys.

Group 20 — Identity-Aware Proxy (IAP)

Variable	Default	Description
enable_iap	false	Require Google sign-in in front of Flowise. Recommended for production.
iap_authorized_users / iap_authorized_groups	[]	Who may access.
iap_oauth_client_id / iap_oauth_client_secret	""	Required when IAP is enabled (sensitive).
iap_support_email	""	Shown on the OAuth consent screen.

Group 21 — Cloud Armor & CDN

Variable	Default	Description
enable_cloud_armor	false	Attach a Cloud Armor (WAF) policy to the Ingress backend.
admin_ip_ranges	[]	CIDRs allowed privileged access.
cloud_armor_policy_name	default-waf-policy	Policy name.
enable_cdn	false	Enable Cloud CDN on the GKE Ingress backend.

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

These values are returned on a successful deployment and are the quickest way to locate and explore the running resources.

Output	Description
service_name	Kubernetes Service name.
namespace	Namespace the workload runs in.
service_cluster_ip	In-cluster ClusterIP.
stage_service_cluster_ips	Map of ClusterIPs for stage-specific services.
service_external_ip	External LoadBalancer IP (when a static IP is reserved).
service_url	URL to reach Flowise.
database_instance_name	Cloud SQL instance name.
database_name	Application database name.
database_user	Application database user.
database_password_secret	Secret Manager secret holding the DB password.
database_host	DB endpoint (127.0.0.1 via the Auth Proxy).
database_port	Database port.
storage_buckets	Created Cloud Storage buckets.
network_name / network_exists / regions	VPC network, presence, available regions.
container_image / container_registry	Deployed image and Artifact Registry repo.
monitoring_enabled / monitoring_notification_channels	Monitoring status and channels.
initialization_jobs	Names of the setup jobs.
db_import_job	Name of the (optional) import job.
deployment_id / tenant_id / resource_prefix	Naming identifiers.
project_id / project_number	Project identifiers.
cicd_enabled / cicd_configuration	CI/CD status and details.
github_repository_url / github_repository_owner / github_repository_name	CI/CD repo details.
artifact_registry_repository / cloudbuild_trigger_name / cloudbuild_trigger_id	Registry and build trigger.
kubernetes_ready	Whether the cluster/workload is ready.
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
database_type	POSTGRES_15	Critical	Flowise requires PostgreSQL; MySQL/NONE breaks startup.
enable_cloudsql_volume	true	Critical	Without the Auth Proxy sidecar, the database connection is refused.
application_database_name / _user	set once	Critical	Immutable after first deploy; renaming recreates the DB/user and destroys data.
enable_backup_import	false unless restoring	Critical	Enabling without a valid backup file fails the import job.
quota_memory_requests / _limits	binary units	Critical	Bare integers are bytes and block all scheduling.
flowise_username	change from admin	High	The default username is publicly known; combined with a guessed password it grants full access to all AI flows.
FLOWISE_SECRETKEY_OVERWRITE	leave unset after first deploy	High	Changing or removing this after the first deploy permanently scrambles all stored LLM API keys and vector-store credentials.
container_resources.memory_limit	1Gi	High	Below 512Mi the Node.js process is OOM-killed on startup. Production with large flow graphs needs 2Gi.
max_instance_count	1 (without Redis)	High	Multiple replicas without a shared Redis store cause flow executions to fail when requests are routed to a different pod.
enable_iap	enable for admin-facing	High	The Flowise UI is otherwise publicly reachable without authentication.
STORAGE_TYPE	gcs (default)	High	Overriding to anything else writes uploads to ephemeral pod storage, lost on every pod restart.
min_instance_count	1	Medium	0 risks cold-start latency that exceeds downstream LLM client timeouts.
enable_redis	enable with >1 replica	Medium	Required for shared session/queue state across multiple replicas.
backup_retention_days	7 (raise for prod)	Medium	Too short for compliance retention.
pdb_min_available vs min_instance_count	leave headroom	Medium	1/1 can stall node upgrades (single pod cannot be evicted).

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For the foundation behaviour referenced throughout — IAM and Workload Identity, autoscaling, ingress and certificates, CI/CD, Cloud Armor, IAP, Binary Authorization, VPC-SC, backups, and image mirroring — see App_GKE. Flowise-specific application configuration shared with the Cloud Run variant is described in Flowise_Common.

Related guides

• Hands-on lab: Flowise on GKE Autopilot — deploy it step by step, with the console screens and commands at each stage.
• Flowise on Google Cloud Run — the same application on Cloud Run, for when you need the other deployment target.
• Flowise Common — Shared Application Configuration — the configuration shared by both deployment targets.