Deploy on Google Cloud Run

When you finish this page, the Kindgi runtime and your pack's service run as two Cloud Run services in one Google Cloud project, with everything around them, from Kindgi's Terraform module. You then deploy your pack, run a flow, and turn on sign-in. The Cloud Run module reference has what the module grants, the settings that change its shape, and its limits.

In the verification run, the first apply took about ten minutes, most of it Cloud SQL. A tool call from the runtime to your pack took 42 ms at the median, and 100 ms at p95.

Access to the runtime image

Sign in at access.kindgi.com with GitHub for the runtime image's pull credentials, and log in once with kindgi auth registry (see Install). Questions or trouble: contact@kindgi.com.

What you'll have

• The runtime (kindgi-server): Kindgi's server, on Cloud Run with its own service account and one instance. It has public ingress on port 4000, which Cloud Run passes as PORT. Its CPU is always allocated, so a run started in the background keeps running after its answer.
• Your pack's service (kindgi-pack): your tools' code. Internal ingress, and IAM-protected: only the runtime's service account may call it, with a Google ID token on every call.
• Cloud SQL (Postgres 16) for the runtime's data, reached through the Cloud SQL socket.
• Artifact Registry for both images. The runtime also reads your pack's image from it when you deploy.
• Secret Manager for the runtime's secrets, and a Cloud KMS key that wraps the secrets the runtime stores, such as model API keys and webhook secrets.
• A VPC with Direct VPC egress and Cloud NAT, which carries the runtime's calls to your pack's service and out to model APIs and webhooks. Or, when your tools need a VPC you already have, that VPC through its connector (A new VPC, or yours).

Your organization may forbid public access to Cloud Run: its iam.allowedPolicyMemberDomains policy then refuses allUsers. Set server_invoker_iam_disabled = true and server_public = false. The runtime's API token still guards every call.

Who calls whom:

• your app calls the runtime, with its API token;
• the runtime calls your pack's service, with an ID token, and Cloud SQL and model APIs;
• kindgi deploy calls the runtime with a signed envelope, and the runtime reads the pack's image from Artifact Registry.

Before you start

• A Google Cloud project, and a Cloud Storage bucket for Terraform's state. Whoever applies the module is an Owner, or an Editor with Security Admin and Secret Manager Admin.
• Terraform 1.6 or later, gcloud, Docker with buildx, jq, curl, openssl, and your pack's kindgi CLI, 0.1.2 or later, which has kindgi key trust.
• For kindgi commands: Kindgi 0.1's CLI, which runs from any folder as npx --yes @kindgi/cli@0.1 (Install). Inside a pack project, pnpm exec kindgi runs the project's pinned CLI instead. The build, env plan and deploy steps need the pack's folder, so they use pnpm exec kindgi.
• Runtime 0.1.1 or later. Cloud SQL has no superuser; 0.1.0 can't start on it.
• Access to the runtime image (kindgi auth registry; see Install).
• A license key: a non-production key covers staging. Write to contact@kindgi.com for one.
• A pack that kindgi build --local --push builds, with an environment block for this deployment in its config.

1. The foundation

The services need images and secret values that the next steps make. So the first apply creates everything else: the APIs, the network, the service accounts, the repository, the KMS key, Cloud SQL and the secrets' containers.

The module is deploy/gcp-cloud-run/ in the kindgi-sdk repository: copy the folder from the release you run. Its README.md lists every variable. example.tfvars is the shape on this page, with a new VPC. example-connector.tfvars runs in a VPC you already have, through a Serverless VPC Access connector. A new VPC, or yours says which to pick.

cp example.tfvars prod.tfvars   # project_id, region, kindgi_env, the seed ids, …
terraform init -backend-config=bucket=<state bucket> -backend-config=prefix=<this deployment>
terraform apply -var-file=prod.tfvars \
  -target=google_project_service.apis \
  -target=google_compute_router_nat.nat \
  -target=google_artifact_registry_repository_iam_member.server_reads_images \
  -target=google_kms_crypto_key_iam_member.server_wraps \
  -target=google_sql_database.kindgi \
  -target=google_secret_manager_secret_iam_member.server_reads \
  -target=google_secret_manager_secret_iam_member.pack_reads_token \
  -target=google_project_iam_member.server_sql_client

Excerpt

• prod.tfvars holds this deployment's variables. example.tfvars lists them.
• -backend-config tells init where the state goes: <state bucket>, and <this deployment> as its own prefix in it.
• -target limits this apply to the APIs, the network, the database, the secrets' containers and the grants, with what they need.

Give each deployment its own state prefix, never shared with your app's own infrastructure.

The plan creates 34 resources. Cloud SQL is the long one, about six minutes.

The module sets Cloud SQL's edition to ENTERPRISE. A Postgres 16 instance otherwise defaults to ENTERPRISE_PLUS, which takes only the db-perf-optimized-N-* tiers, and the apply fails with Invalid Tier (db-f1-micro) for (ENTERPRISE_PLUS) Edition.

2. The images into Artifact Registry

Cloud Run pulls from Artifact Registry, not from the runtime's private registry. Copy the runtime image there by digest, with every platform it was built for:

REPO=$(terraform output -raw image_repository)
gcloud auth configure-docker "${REPO%%/*}"
docker buildx imagetools create --tag "$REPO/runtime:0.1.9" \
  quay.io/kindgi/runtime:0.1.9@sha256:604e283abed492f5bd50c88dcf582d13e38e19534ee7ddad817ba08012f99523

• REPO is the repository's address, from the foundation's output. configure-docker lets Docker push to its host.
• imagetools create --tag copies the image by digest, every platform included, under the tag you give.

The copy keeps the release's digest. A plain docker pull, tag and push from an Apple silicon machine pushes only the arm64 image, which Cloud Run can't run.

A repository you already have instead of the module's own: image_repository = { project, location, repository }. The module then creates none, gives the runtime's service account roles/artifactregistry.reader on it, and, for a repository in another project, gives this project's Cloud Run service agent the same role so it can pull. terraform output image_repository names where images go, either way.

Check the repository's cleanup policies

A cleanup policy that deletes tags or images by age can delete the digest a running revision pins, and the next instance start then fails. Keep Kindgi's images out of such a policy, or use the module's own repository.

Then build and push your pack's image, signed. --local builds it on your machine, --push pushes it to the registry of your pack's prod environment block, and --env prod names that block:

pnpm exec kindgi build --local --push --env prod

It prints the build as JSON, then each step. The last steps:

…
    ✓ Pushed …/acme@sha256:bd7bfe4f…

  Verifying build output
    ✓ /app/index.json in the image matches the local index byte for byte

  Signing locally
    ✓ Ed25519 signature over (imageDigest, artifactVersion, indexHash, tenantId, publishedAt)
      key: …
…

Excerpt

Set server_image and pack_image in prod.tfvars to the two digests (…@sha256:…).

With tenancy = "multi" (Serve many tenants) there's no pack_image and no pack service: each deployment is a Cloud Run service of its own.

3. The secrets

The services read their secrets from Secret Manager. Make each value here and pipe it straight into Secret Manager: it's never on disk, in Terraform's state or in a command's arguments, which other processes can read and gcloud writes to its log file. Kindgi generates none of them. The commands are for bash or zsh. To run with no KMS key, set secrets_backend = "none" first (Without a KMS key).

N=kindgi   # name_prefix
CONN=$(terraform output -raw sql_connection_name)
P=$(gcloud config get-value project)

# Kindgi's database user: a built-in user, not an IAM one. The instance is
# named after name_prefix ($N); the database is database_name (kindgi).
# Made through the Cloud SQL Admin API rather than `gcloud sql users create --password`:
# the body goes in on stdin and the token in a header from a pipe.
# Each step runs only if the one before it worked, so the secret never holds
# a password the user wasn't given.
DBPW=$(openssl rand -hex 24)
OP=$(printf '{"name":"kindgi","password":"%s"}' "$DBPW" \
  | curl -sS -H @<(printf 'Authorization: Bearer %s\n' "$(gcloud auth print-access-token)") \
      -H 'Content-Type: application/json' --data-binary @- \
      "https://sqladmin.googleapis.com/v1/projects/$P/instances/$N/users" \
  | jq -r '.name // error(.error.message)') && [ -n "$OP" ] \
  && gcloud sql operations wait "$OP" --project=$P \
  && printf 'postgres://kindgi:%s@/kindgi?host=/cloudsql/%s' "$DBPW" "$CONN" \
  | gcloud secrets versions add $N-database-url --data-file=-
unset DBPW

# The token the runtime and the pack's service share.
openssl rand -hex 32 | tr -d '\n' | gcloud secrets versions add $N-pack-service-token --data-file=-

# The first API token, and the two keys, base64.
printf 'kgi_bt_%s' "$(openssl rand -hex 32)" | gcloud secrets versions add $N-api-token --data-file=-
openssl rand 32 | base64 | gcloud secrets versions add $N-secrets-aad-key --data-file=-   # version 1 (not with secrets_backend = "none")
openssl genpkey -algorithm ed25519 | base64 | gcloud secrets versions add $N-public-token-key --data-file=-
# Only with export_signing = "secret": the key that signs exports.
openssl genpkey -algorithm ed25519 | base64 | gcloud secrets versions add $N-export-signing-key --data-file=-

# The license key, pasted, never echoed.
read -rs LICENSE_KEY && printf '%s' "$LICENSE_KEY" | gcloud secrets versions add $N-license-key --data-file=- && unset LICENSE_KEY

• N is your name_prefix, CONN the Cloud SQL instance's connection name, and P your Google Cloud project's id.
• curl sends the database user's name and password to the Cloud SQL Admin API (users.insert) on its input, with your gcloud access token in a header read from a pipe. jq takes the operation's name, or prints the API's error, and gcloud sql operations wait waits until the user exists. The &&s stop at the first step that fails, and [ -n "$OP" ] stops them when curl got no answer: then no password goes into the secret.
• gcloud secrets versions add <name> --data-file=- adds what it reads on its input as the secret's next version.
• openssl rand makes random values, and openssl genpkey -algorithm ed25519 an Ed25519 private key.
• read -rs reads the license key you paste, without showing it.

The server reads the AAD key's version that secrets_aad_key_version names in prod.tfvars: "1", the one you added. The example files have it. Every secret stored in Postgres is bound to that key, so the module pins it and refuses latest:

secrets_aad_key_version is a version number ("1" for a new deployment), never "latest": every secret stored in Postgres is bound to the key it names.

The database user is a built-in Cloud SQL user. It isn't a superuser. But it has CREATEROLE, and owns the database through cloudsqlsuperuser, which is what the runtime needs. An IAM database user has neither.

Your pack's own secrets: kindgi env plan --env prod lists what your pack needs. Create each secret and add its value. The module passes them to the pack's service. jq turns the plan into the module's pack_env and pack_secret_env variables:

pnpm exec kindgi env plan --env prod > /tmp/pack-env.json
jq '{pack_env: .env, pack_secret_env: .secret_env}' /tmp/pack-env.json > prod.pack-env.auto.tfvars.json

4. The services

With the images and the secrets in place, apply the whole module. It creates the two services:

terraform apply -var-file=prod.tfvars

The pack's service comes up first, in about 22 seconds. It's ready only when every module loaded and every required variable is set. Then the runtime. On Cloud Run it logs JSON, so its startup lines are the lines of one log record, Kindgi runtime ready:

gcloud logging read 'resource.labels.service_name="'$N'-server" AND jsonPayload.message="Kindgi runtime ready"' \
  --limit=1 --format=json | jq -r '.[0].jsonPayload.lines[]'

--limit=1 reads the newest such record, and jq prints its lines. They name the pack's service it reached, and how it calls it (How the runtime calls your pack's service):

Pack service: https://kindgi-pack-…a.run.app — acme (artifact …), protocol 2, 3 tools, 1 check
Pack service auth: a Google ID token per call (KINDGI_PACK_SERVICE_AUTH)

Excerpt

The KMS check comes right before them, as a log line of its own:

gcloud logging read 'resource.labels.service_name="'$N'-server" AND textPayload:"KMS probe"' \
  --limit=1 --format='value(textPayload)'

KMS probe OK (gcp-cloud-kms): gcp-cloud-kms v1 (encrypt/decrypt round trip, key version 1) (170ms)

On the first apply, the pack service line can read instead:

⚠ Pack service at https://… isn't answering (pack-service-unauthorized: The platform in front of the pack service refused the call: check the identity token (KINDGI_PACK_SERVICE_AUTH) and that the server may invoke the service). The server is up; pack tools and checks fail until it answers.

Excerpt

The runtime's permission to call the pack's service is seconds old then, and Google Cloud is still applying it. It clears without a restart: in our run, the first tool call, 3½ minutes after the warning, worked. If tool calls still fail after that, check that the runtime's service account has roles/run.invoker on the pack's service.

Call your app's Cloud Run services from a tool

When a tool calls one of your app's IAM-protected Cloud Run services, list it in pack_run_invokers, by its name, not its URL:

pack_run_invokers = [
  { project = "acme-app", location = "europe-west1", service = "orders-api" },
]

Excerpt

The pack's service account gets roles/run.invoker on each one, beside its other members; nothing else of the service changes. The tool asks the metadata server for a Google ID token for the service's URL and sends it as Authorization: Bearer:

tools/call-service/index.ts

// acme.call-service: calls one of the app's IAM-protected Cloud Run services
// with a Google ID token for its URL from the metadata server, and reports
// what came back, as is.

import { defineTool } from '@kindgi/sdk/define';
import type { ToolId } from '@kindgi/sdk/types';
import { z } from 'zod';

const Input = z.object({ url: z.string().url() });

const Output = z.object({
  token: z.string(),
  status: z.number().optional(),
  body: z.string().optional(),
  headers: z.record(z.string(), z.string()).optional(),
  error: z.string().optional(),
});

const METADATA =
  'http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/identity';

const defined = defineTool({
  id: 'acme.call-service' as ToolId,
  description: "Call an app Cloud Run service with the pack's Google ID token; report the answer.",
  version: '0.1.0',
  input: Input,
  output: Output,
  effects: [{ kind: 'reads', resource: 'external:cloud-run' }],
  mutating: false,
  handler: async ({ url }) => {
    const audience = new URL(url).origin;
    const minted = await fetch(`${METADATA}?audience=${encodeURIComponent(audience)}`, {
      headers: { 'Metadata-Flavor': 'Google' },
    });
    if (!minted.ok) return { token: `refused ${minted.status}`, body: await minted.text() };
    const idToken = (await minted.text()).trim();
    try {
      const res = await fetch(url, { headers: { authorization: `Bearer ${idToken}` } });
      const headers: Record<string, string> = {};
      for (const name of ['content-type', 'www-authenticate', 'server', 'x-cloud-trace-context']) {
        const value = res.headers.get(name);
        if (value !== null) headers[name] = value;
      }
      return { token: 'minted', status: res.status, body: (await res.text()).slice(0, 2000), headers };
    } catch (cause) {
      return { token: 'minted', error: cause instanceof Error ? `${cause.name}: ${cause.message}` : String(cause) };
    }
  },
});

if (defined.kind === 'err') {
  throw new Error(`acme.call-service failed to compile: ${defined.error.message}`);
}

export default defined.value;

The call leaves through the pack's own egress, so the service's ingress has to take it. A service with ingress all does, with IAM as the guard. A service with internal ingress refuses it with a 404, Google's "Page not found" page, not a 403, so the tool's error can look like a wrong URL. A call from Cloud Run to an internal service has to go through a VPC network, and the pack's calls to your services don't (Cloud Run: Restrict network endpoint ingress).

OpenFGA behind Cloud Run IAM

When OpenFGA runs as a Cloud Run service of its own, with IAM on, the runtime proves who it is to Cloud Run as well as to OpenFGA (runtime 0.1.8 or later). Give the runtime's service account roles/run.invoker on OpenFGA's service, run OpenFGA with a key and its playground off (Require a key for OpenFGA), and set:

openfga_api_url = "https://openfga-…a.run.app" # OpenFGA's own service URL
server_env = {
  KINDGI_OPENFGA_AUTH = "google-id-token"
}
server_secret_env = {
  KINDGI_OPENFGA_PRESHARED_KEY = { secret = "kindgi-openfga-key", version = "1" }
}

Excerpt

Each call then carries a Google ID token for that URL, from the runtime's own identity, in X-Serverless-Authorization, beside the key in Authorization. With both headers, Cloud Run checks only X-Serverless-Authorization, and passes the token on without its signature, so the key reaches OpenFGA (Cloud Run: Authenticating service-to-service). The URL is the token's audience, so use OpenFGA's service URL itself, over https. The startup line about OpenFGA's calls names the token too (KINDGI_OPENFGA_AUTH).

Keep the key's secret pinned to a version, as here: then change the key one deploy at a time.

Serve many tenants

By default (tenancy = "single") the server serves one tenant, seed_tenant_id's, and calls one pack service (pack_image). With "multi", on runtime 0.1.8 or later, it serves every tenant created through POST /v1/system/tenants, and takes each request's tenant from its key or session. Each deployment is then a Cloud Run service of its own: your orchestrator creates it and records its endpoint through the runtime's /v1/system/… deployment routes. This module doesn't.

tenancy         = "multi"
openfga_api_url = "https://openfga-…a.run.app"
# no seed_tenant_id, seed_user_id or pack_image; secrets_backend stays "postgres"
server_env = {
  KINDGI_TENANT_HOST_ACCESS  = "isolated"
  KINDGI_PACK_ROUTING        = "per-deployment"
  KINDGI_PACK_ENDPOINT_HOSTS = "*-<project number>.<region>.run.app" # the deployments' services
}
server_secret_env = {
  KINDGI_OPENFGA_PRESHARED_KEY = { secret = "<a key OpenFGA accepts>", version = "1" }
}

Excerpt

• What the plan needs, and names when it's missing: openfga_api_url (without an authorization store no tenant would have an admin), KINDGI_OPENFGA_PRESHARED_KEY in server_secret_env (Require a key for OpenFGA), KINDGI_TENANT_HOST_ACCESS = "isolated", KINDGI_PACK_ROUTING = "per-deployment" and KINDGI_PACK_ENDPOINT_HOSTS in server_env, and secrets_backend = "postgres" (each endpoint's token is sealed under the secrets' key). The server won't start without them.
• What the plan refuses: seed_tenant_id, seed_user_id, pack_image, and what the pack service would run with: pack_env, pack_secret_env, pack_cloud_sql_instances, pack_bucket_readers and pack_run_invokers. The pack service's other settings do nothing without it.
• Each deployment's service (your orchestrator's):
  • Its host matches KINDGI_PACK_ENDPOINT_HOSTS. On Cloud Run, *-<project number>.<region>.run.app admits only one project's services; *.run.app and *.<region>.run.app are refused at start. Record its endpoint by that URL: Cloud Run's other URL for the service, the one ending in .a.run.app, doesn't match.
  • The server calls it with its own identity when the endpoint's auth is a Google ID token, so the service grants roles/run.invoker to the server's account (terraform output service_accounts).
  • In connector mode its ingress is all traffic, with IAM as the guard: the server's connector carries private ranges only. In direct mode it can be internal when it runs in the server's project (or inside a VPC Service Controls perimeter with it), as the module's own pack service does (Cloud Run: Restrict network endpoint ingress).
• What the module sets: KINDGI_TENANCY=multi (the variable), and none of KINDGI_TENANT_ID, KINDGI_SEED_USER_ID, KINDGI_PACK_SERVICE_URL, KINDGI_PACK_SERVICE_TOKEN or KINDGI_PACK_SERVICE_AUTH. It creates no pack service, pack account or pack grants, and no shared pack token. pack_call_timeout_ms still caps each call.
• The API token is the operator's: it reaches only /v1/system/*, in no tenant. So step 5 and everything after it use a tenant's key instead:
  • A tenant: POST /v1/system/tenants with the API token. With firstAdmin, that person is its admin and holds every capability but secrets:reveal, to put on the keys they make (Who can do what). Without it, the answer carries the first admin's key, sent once. That key is a service account's, so the runs it starts count as unattended (Service accounts): for the work you start, add yourself as a person (Add a person) and use a key of your own.
  • Its image repository: the create's imagePrefix, or PUT /v1/system/tenants/{tenantId}/image-prefix, before its first deploy. Without it, a deploy is refused with 409 image-prefix-unset.
  • Its tools answer once your orchestrator has run the deployment's service and recorded its endpoint. Until then, a run that calls one fails with pack-endpoint-pending: "The pack service of the deployment shipping … isn't ready yet."
• An existing deployment keeps its tenant, with its data, keys and people, as the first of many at the first "multi" boot. Before the switch:
  • OpenFGA first: if it has no openfga_api_url yet, add it (and the key) in a single-tenant apply. That boot makes the tenant's authorization store, with the seed user as its admin. Switching in the same apply leaves the tenant without one, and none can be made afterwards without naming its first admin.
  • A key of the tenant for anything that deploys or calls with the API token: after the switch, that token no longer reaches the tenant.
  • Its deployments' services: the switch removes the one pack service, so each deployment needs a service and a recorded endpoint of its own, as any tenant's does.
  • Then, in one apply: tenancy = "multi", without seed_tenant_id, seed_user_id and pack_image, with the settings above.
• After an upgrade that adds a step per tenant, kindgi-runtime tenants repair --all has to run once: a server serving many tenants sets nothing up per tenant at boot. This module runs no such job.
• An earlier runtime ignores KINDGI_TENANCY. With no tenant id it would seed a new tenant at every start, so upgrade the runtime first.

5. Trust your key, and deploy

The runtime accepts only deploys signed by a key it trusts. Read its address and the first API token, trust your pack's key, then deploy. With tenancy = "multi", use a key of the tenant here and after, not the API token, and the tools answer once your orchestrator has recorded the deployment's endpoint (Serve many tenants).

URL=$(terraform output -raw server_url)
export KINDGI_API_TOKEN=$(gcloud secrets versions access latest --secret=$N-api-token)
npx --yes @kindgi/cli@0.1 key trust acme-prod --url "$URL"

It prints the key the runtime now trusts, then says so:

{
  "keyId": "acme-prod",
  "tenantId": "722e23b8-bbb4-43dc-9a37-9640e369fa7d",
  "algorithm": "ed25519",
  "publicKey": "UCeKMLv5KIFRJo5exp/5BKzsPOKzdlmJYYuLKVYmEVo=",
  "createdAt": "2026-10-12T14:28:47.190Z"
}

  ✓ Trusted acme-prod (sha256:60e5a3c06154b3ee3e425037)
    The runtime now accepts deploys this key signs.

• gcloud secrets versions access reads the API token from step 3.
• acme-prod is your signing key's id, from ~/.kindgi/keys/.
• --url is the runtime's address. The commands send the API token, exported as KINDGI_API_TOKEN, which keeps it off the command line. kindgi deploy takes the address as --endpoint, and --env prod names the environment block to deploy.

pnpm exec kindgi deploy --env prod --endpoint "$URL"

It prints the deployment as JSON, then each step. The last steps:

…
  Registering deployment
    ✓ POST /v1/deployments  →  201 Created
      deploymentId:    b27ee9ec-…
      artifactVersion: …
      primitives:      3 tools, 1 guardrail, 1 agent, 2 flows
      activatedAt:     2026-10-04T22:23:24.370Z

  Deploy complete.
  Runs started from now use image sha256:bd7bfe4f7d9c8… (artifactVersion …).
  Runs already in flight continue on their pinned image.

Excerpt

To deploy a client's pack into its own project, add --project <id or slug> (Deploy a client's pack into its project).

The runtime read your pack's image from Artifact Registry with its own token (KINDGI_IMAGE_REGISTRY_AUTH=google) to check it before registering it.

A deploy that's refused, for an untrusted key or a missing variable, says what to fix. Fix it and run the same command again.

6. Check it

Check the runtime answers, lists your pack's tools, and runs a flow:

curl "$URL/health"                                  # {"ok":true}
npx --yes @kindgi/cli@0.1 tools list --url "$URL"   # your pack's tools
npx --yes @kindgi/cli@0.1 runs start --flow=acme.greet-echo --input='{"name":"Ada"}' --url "$URL"

--flow names the flow to run, and --input is its input, as JSON.

In the verification run, every run completed. A new instance of the runtime was ready in about 7 seconds, 8 with its first migrations, and the pack's service in about 5.

7. Turn on sign-in

Nobody can sign in to the console until you turn sign-in on. The API, the CLI and the SDKs take API tokens either way. Until then, the startup lines say so:

  ⚠ Console sign-in: nobody can sign in to the console. KINDGI_CONSOLE_TOKEN_SIGN_IN=on allows an API token; KINDGI_AUTH_SECRET_PATH turns on sign-in with identity providers.

The runtime's own settings go in two variables, as the pack's do: server_env for plain values, and server_secret_env for Secret Manager secrets, read with the runtime's identity. You create each secret, and the runtime gets read access to exactly those (a secret in another project is granted there). The plan refuses a name the module sets itself (its own variables cover those, such as public_url below), KINDGI_DEV, and a secret given as a plain value: a name with SECRET in it, a preshared key, or the SMTP URL.

With an API token, which the console's sign-in page then takes:

server_env = {
  KINDGI_CONSOLE_TOKEN_SIGN_IN = "on"
}

Excerpt

With an emailed link, you need the runtime's sign-in secret, an SMTP server and public_url:

# The sign-in secret: 32 bytes, base64.
openssl rand 32 | base64 | gcloud secrets create $N-auth-secret --data-file=-
# The SMTP URL, password included: paste it; it never goes in a file.
read -rs SMTP_URL && printf '%s' "$SMTP_URL" | gcloud secrets create $N-smtp-url --data-file=- && unset SMTP_URL

public_url = "https://kindgi-dev-server-abc123-pd.a.run.app" # terraform output -raw server_url
server_env = {
  KINDGI_CONSOLE_TOKEN_SIGN_IN = "on"
  KINDGI_AUTH_EMAIL_FROM       = "kindgi@acme.example"
}
server_secret_env = {
  KINDGI_AUTH_SECRET         = { secret = "kindgi-dev-auth-secret", version = "1" }
  KINDGI_AUTH_EMAIL_SMTP_URL = { secret = "kindgi-dev-smtp-url", version = "1" }
}

Excerpt

Pin each secret to a version, as here, rather than latest: a new version then reaches the runtime only when you change version.

• public_url (KINDGI_PUBLIC_URL) is the address people open the console at: terraform output -raw server_url after the first apply, so the emailed link comes with a second apply, or your own domain in front. Console sessions are then accepted from that address only. The plan refuses KINDGI_AUTH_SECRET without it, because the runtime wouldn't start.
• Continue with Google, Microsoft or GitHub, verified domains and Turnstile go the same way: each provider's client id, KINDGI_AUTH_VERIFIED_DOMAINS and the Turnstile site key in server_env; each …_CLIENT_SECRET and KINDGI_AUTH_TURNSTILE_SECRET in server_secret_env. The module mounts no files, so use the value forms of the settings, not their …_PATH forms.

Check it worked: after the apply, the new revision's startup lines say where it's reached, and which ways in the console has, instead of the warning. From a deployment with identity providers and the emailed link:

Kindgi API server listening on http://localhost:4000 (reached at https://kindgi-server-…a.run.app)
  Console sign-in: identity providers, or an API token (KINDGI_CONSOLE_TOKEN_SIGN_IN)
  …
  Pack service: https://kindgi-pack-…a.run.app — acme (artifact 20261009.132057), protocol 2, 4 tools, 1 check
  Pack service auth: a Google ID token per call (KINDGI_PACK_SERVICE_AUTH)

Excerpt

What each setting does, and the ways in: Turn on sign-in.

Use Gemini

The runtime can call Gemini on Vertex AI with its own service account, so there's no key to store. Set vertex_ai = true and apply: the module turns on the Vertex AI API and grants the runtime's service account roles/aiplatform.user. Then register the preset:

npx --yes @kindgi/cli@0.1 providers register --preset=gemini --project=<project> --models=gemini-3.8-flash --url "$URL"

{
  "providerId": "gemini"
}
✓ Registered gemini: gemini-3.8-flash (default)

• --preset=gemini registers Gemini on Vertex AI.
• <project> is your Google Cloud project's id.
• --models lists the models to offer. The first is the default.

Without the role, every model call fails. This one was captured with gemini-2.5-flash, and another model's call names that model:

Model call to gemini (gemini-2.5-flash) failed: {"error":{"code":403,"message":"Permission 'aiplatform.endpoints.predict' denied on resource '//aiplatform.googleapis.com/projects/<project>/locations/global/publishers/google/models/gemini-2.5-flash' (or it may not exist). …

Excerpt

A new grant can take a minute or two to apply.

Operate it

• Upgrade at least every 90 days while Kindgi is in preview. Until Kindgi 1.0, a release stops starting 90 days after it was released. Cloud Run starts new instances on its own, and after that day none comes up. The runtime warns from 30 days before, at startup and once a day, in a log record with jsonPayload.event = "kindgi.preview_expiry": set a log-based alert on it (Licensing).

• Upgrade: back up Cloud SQL, copy the new runtime image by digest, set server_image, and apply. The new revision takes all the traffic. Migrations only go forward: never run two runtime versions on one database, and go back by restoring the backup. From a module copy older than secrets_aad_key_version, add it to prod.tfvars first, set to the version your server reads, normally 1 (gcloud secrets versions list $N-secrets-aad-key lists them). Without it, terraform plan stops and asks for it.

• Restore Cloud SQL: a point-in-time recovery always makes a new instance, and a backup can go into one too (restored into the serving instance, it overwrites everything on it). database_instance moves the server onto the new instance: the instance's name, and a secret of yours holding the server's URL to it. The module's own instance stays as it is. The module's README has the steps, under Serving from a restored instance:

  • the new instance's URL, and the server's read access to it;
  • the erasure replay before it serves (Erasures and backups);
  • the switch, and the way back.

• Rotate a secret: add a version, then roll a new revision of each service that reads it (gcloud run services update … --update-labels=rotated=$(date +%s)).

• The AAD key is never rotated. Every stored secret is bound to the version the server reads, so a new version is a key change that needs every stored secret re-encrypted first. The pin keeps a version added by mistake away from the server.

• Client addresses: the module trusts one proxy, Cloud Run's front end, which adds the caller to X-Forwarded-For. That's trusted_proxies = "1", the runtime's KINDGI_TRUSTED_PROXIES, so rate limits and sign-in records see the caller. Behind an external Application Load Balancer, set "2": it adds the client and then its own address (Google: X-Forwarded-For header).

• Erasures, after a restore: a memory erasure keeps a keyed hash of whom it erased, so it can be replayed after you restore a backup. The key goes in Secret Manager, named in server_secret_env:

  openssl rand 32 | base64 | gcloud secrets create $N-erasure-ledger-key --data-file=-

  server_secret_env = {
    KINDGI_ERASURE_LEDGER_KEY = { secret = "kindgi-dev-erasure-ledger-key", version = "1" }
  }

  Excerpt

  The startup lines then say:

    Erasures: on; the ledger is replayable after a backup restore (key from KINDGI_ERASURE_LEDGER_KEY)

  Without it, they say erasures aren't replayable. Keep the key: losing it means losing replay (Erasures and backups).

• Logs: Cloud Logging, per service. The runtime logs JSON there, one record per line, and Cloud Logging reads each record's severity. Filter by jsonPayload.traceId to follow one request or run. The startup lines are the lines of its boot record, as in The startup log. See Logs.

Tear it down

Terraform won't delete Cloud SQL while database_deletion_protection is on (the default). Set it to false and apply first. The KMS key ring and key outlive terraform destroy: Google Cloud never deletes them. Take them out of Terraform's state, destroy the rest, then schedule the key's versions for destruction:

terraform apply -var-file=prod.tfvars -var=database_deletion_protection=false
terraform state rm 'google_kms_crypto_key.secrets[0]' 'google_kms_key_ring.kindgi[0]'   # none with secrets_backend = "none"
terraform destroy -var-file=prod.tfvars
gcloud kms keys versions destroy 1 --key=… --keyring=… --location=…

Excerpt

If the destroy stops at the subnet (is already being used by …/addresses/serverless-ipv4-cloudrun-…), Cloud Run hasn't released its addresses: run it again later.

Next

• Cloud Run module reference: the network, the secrets backend, the IAM it sets up, and its limits.
• Operate a self-hosted runtime: health, backups, upgrades and rotating keys.
• Turn on sign-in: every way in, and what each setting does.