Google Cloud Run Reference
Commands, customization, environment variables, and troubleshooting for the Google Cloud Run template.
The Cloud Run service is agent-os, the Cloud SQL instance is agentos-db, and the Artifact Registry repo is agentos. The scripts target the current gcloud project and us-central1; override them with GCP_PROJECT_ID and GCP_REGION.
Manage
For a nondefault region, export GCP_REGION in your shell before running redeploy, env-sync, or log commands. Those scripts use the shell value or us-central1; the value saved by up.sh in the env file is not sufficient for redeploy or env-sync.
export GCP_REGION=europe-west1 # use the region of your service| Task | Command |
|---|---|
| Deploy code changes | ./scripts/gcp/redeploy.sh |
| Sync env variables | ./scripts/gcp/env-sync.sh (defaults to .env.production; pass .env to sync that instead) |
| Tail logs | gcloud run services logs read agent-os --region us-central1 --limit 100 |
| Resize the service | Edit the --cpu/--memory flags in scripts/gcp/up.sh and rerun it |
| Tear down | ./scripts/gcp/down.sh (add --yes to skip the confirmation) |
Production auth
See the first-deploy limitation before creating a new production service. The commands on this page also support existing services with working verification configuration.
Token-Based Authorization is on by default. Production startup requires JWT_VERIFICATION_KEY or a readable JWKS file at the container path in JWT_JWKS_FILE; otherwise the process exits.
Token-Based Auth gives you three things:
- Protected runtime access. Protected API routes require a valid credential. Health, discovery, and API documentation remain public; Slack and MCP OAuth have their own authentication flows.
- Per-request identity. Middleware validates the token and exposes its
user_id, optionalsession_id, scopes, and claims to the request. - Scope-based permissions. Token scopes control access to AgentOS routes and resources.
The template already sets AuthorizationConfig(user_isolation=True). Authenticated non-admin REST access is scoped to the principal; local dev mode disables scope enforcement and is open when no credentials are configured. This does not scope Platform Manager’s direct database tools to that REST identity. See User Isolation for the boundaries and admin exceptions.
To disable JWT authentication in a private deployment with another auth layer, set authorization=False, remove JWT_VERIFICATION_KEY and JWT_JWKS_FILE from the running service, and rebuild or redeploy the app as needed. Disabling scope enforcement alone does not remove JWT validation while those credentials remain configured. MCP OAuth remains enabled while MCP_CONNECT_SECRET is set.
Customize
Ask your coding agent to run /create-agent, or do it by hand. Create agents/my_agent.py:
from agno.agent import Agent
from app.learning import shared_learning
from app.settings import default_model
from db import get_postgres_db
INSTRUCTIONS = """\
What the agent does, which tools it uses, the rules to follow when answering.
"""
my_agent = Agent(
id="my-agent",
name="My Agent",
user_id="anonymous-user", # Local fallback; authenticated runs supply identity.
model=default_model(),
db=get_postgres_db(),
instructions=INSTRUCTIONS,
learning=shared_learning,
add_datetime_to_context=True,
add_history_to_context=True,
num_history_runs=5,
)The fallback user ID lets local anonymous calls use the shared learning machine; those calls share one profile. Authenticated run identity overrides this default.
Import it in app/main.py and update the agents argument in the existing AgentOS call. Keep its other arguments, including teams, workflows, knowledge, and registry:
from agents.my_agent import my_agent
agent_os = AgentOS(
# Keep the other arguments from the existing call.
agents=[platform_builder, platform_manager, platform_engineer, my_agent],
)Add its UI metadata beneath the existing manifest: key in app/config.yaml:
my-agent:
description: "What the agent does."
quick_prompts:
- "First example prompt"
- "Second example prompt"
- "Third example prompt"Local containers reload Python source changes. After editing app/config.yaml, run docker compose restart agentos-api to reload the manifest. For production, run ./scripts/gcp/redeploy.sh.
app/settings.py defines default_model(), used by every agent. Change it in one place:
from agno.models.anthropic import Claude
def default_model():
return Claude(id="claude-sonnet-5")Add anthropic to pyproject.toml, set the provider key in your env, and regenerate pins:
./scripts/generate_requirements.shRebuild locally with docker compose up -d --build. For production:
./scripts/gcp/env-sync.sh
./scripts/gcp/redeploy.shAgno ships 100+ toolkits. See Toolkits.
from agno.tools.slack import SlackTools
my_agent = Agent(
# Keep the agent’s existing configuration.
tools=[SlackTools()],
)- Edit
pyproject.toml. - Regenerate pins:
./scripts/generate_requirements.sh(addupgradeto refresh every pin). - Rebuild locally with
docker compose up -d --build, or redeploy with./scripts/gcp/redeploy.sh.
Set both variables in your env file:
SLACK_BOT_TOKEN=xoxb-...
SLACK_SIGNING_SECRET=...Sync with ./scripts/gcp/env-sync.sh. The interface activates automatically and routes messages to the Agno team. Change team= in app/main.py to select another team, or replace it with agent=my_agent to route to an agent. See Slack setup.
The deployment check runs daily by default (ENABLE_DEPLOY_CHECK=True); it uses fixed checks without model calls. The run-evals schedule is always registered but starts disabled because it uses model calls. Enable it from the AgentOS UI. Both workflows remain runnable on demand. Startup reapplies ENABLE_DEPLOY_CHECK to the deployment-check schedule; the enabled state of an existing run-evals schedule is preserved.
Format, validate, and run evals
Run evals against a dedicated local test platform with no concurrent writers. The starter’s cleanup hooks remove components and learning state created during a case; concurrent application writes can be removed too. The same prerequisite applies to scheduled evals. See eval setup and isolation.
The host scripts require uv. The setup script creates a Python 3.14 venv:
./scripts/venv_setup.sh
source .venv/bin/activate| Task | Command |
|---|---|
| Format | ./scripts/format.sh |
| Lint and type-check | ./scripts/validate.sh |
| Run smoke evals | python -m evals --tag smoke |
./scripts/mcp_check.sh runs inside the container, so it needs no venv.
Environment variables
| Variable | Required | Default | Description |
|---|---|---|---|
OPENAI_API_KEY | Yes | - | Models and embeddings. |
RUNTIME_ENV | No | prd | dev disables scope enforcement; configured JWT credentials still enable token validation. Compose sets it for local. Keep production on prd so scope enforcement remains enabled. |
JWT_VERIFICATION_KEY | Production | - | Public key from os.agno.com. Quote the value so the multi-line PEM parses as one variable. |
JWT_JWKS_FILE | Production | - | Path to a JWKS file inside the container. The scripts set only this environment variable. Add the file to the image build context, rebuild, and redeploy the image, or configure a mount and roll the service. |
MCP_CONNECT_SECRET | No | generated by up.sh | OAuth consent secret (16+ chars) for connecting claude.ai and ChatGPT to /mcp. up.sh generates one on deploy and writes it to .env.production. |
AGENTOS_MCP_SIGNING_KEY | No | generated | Optional high-entropy signing-key material (32+ chars) for OAuth tokens. Unset, a strong key is generated and persisted in the database. Rotating it invalidates outstanding tokens. |
AGENTOS_URL | No | http://127.0.0.1:8000 | Scheduler base URL. up.sh sets it to your Cloud Run URL. Loopback reaches the app inside this container; set the public URL for hosted MCP OAuth and the template’s deployment check. When MCP_CONNECT_SECRET is set, OAuth metadata also derives its public origin from this URL. |
ENABLE_DEPLOY_CHECK | No | True | Daily deployment-check cron. |
EVALS_TAG | No | smoke | Eval tag the run-evals workflow runs. |
EVALS_CASE_TIMEOUT_SECONDS | No | 90 | Fallback timeout for cases without an explicit timeout. |
EVALS_SUITE_TIMEOUT_SECONDS | No | derived from selected cases | Sum of selected case timeouts plus 30 seconds per case, with a 60-second floor. A positive integer overrides this ceiling. |
PARALLEL_API_KEY | No | - | WebSearch uses the Parallel SDK when set, keyless MCP otherwise. |
SLACK_BOT_TOKEN | No | - | Set with the signing secret to enable Slack. |
SLACK_SIGNING_SECRET | No | - | Set with the bot token to enable Slack. |
GCP_PROJECT_ID / GCP_REGION | No | current project, us-central1 | Project and region the scripts/gcp/ scripts target. up.sh records GCP_REGION in your env file so down.sh finds the right region. |
DB_HOST / DB_PORT / DB_USER / DB_PASS / DB_DATABASE | No | matches compose | Postgres connection. |
DB_DRIVER | No | postgresql+psycopg | SQLAlchemy driver. |
AGNO_DEBUG | No | False | Verbose Agno logs. Compose sets it for dev. |
WAIT_FOR_DB | No | False | If True, the entrypoint blocks on the database before starting. Compose sets it. |
Troubleshooting
Install the Google Cloud SDK, then run gcloud auth login and gcloud config set project <id>.
This is the intended post-deploy prompt. In the reviewed revision, a fresh production deployment fails before reaching it because the first revision is missing verification configuration; see the deployment limitation. For a service that already has working verification configuration: At os.agno.com, choose Connect OS → Live, enter your Cloud Run URL, name it Live AgentOS, turn on Token-Based Authorization (JWT) on the connection panel, and connect. The UI generates the public key. If the OS is already connected, enable the setting under Settings → OS & Security. Paste the full PEM into the script prompt. To add a PEM later, set JWT_VERIFICATION_KEY in .env.production and run ./scripts/gcp/env-sync.sh. To use JWT_JWKS_FILE, add the file to the image build context and run ./scripts/gcp/redeploy.sh, or configure a mount. Then add the container path to .env.production and run ./scripts/gcp/env-sync.sh. The scripts do not upload or mount the file.
Non-dev mode requires JWT verification configuration. Configured JWT credentials also enable validation in dev mode. Set JWT_VERIFICATION_KEY and sync. For JWKS, add the file to the image build context and run ./scripts/gcp/redeploy.sh, or configure a mount. Then set JWT_JWKS_FILE to its container path in .env.production and run ./scripts/gcp/env-sync.sh. For a private deployment using another auth layer, follow the credential-removal steps under Production auth.
Your organization likely enforces Domain Restricted Sharing (constraints/iam.allowedPolicyMemberDomains), which silently rejects the allUsers binding that --allow-unauthenticated needs. The deploy still succeeds; the service just ships private. up.sh prints a warning when it detects this. Grant roles/run.invoker to specific principals, or ask an org admin for an allUsers exception.
Check that billing is enabled on the project. up.sh warns when it can't confirm billing; Cloud SQL and Cloud Run creation both fail without it.
Check that the schedule is enabled, the scheduler is running, and its request URL is reachable from the container. Inspect application logs for request or authentication failures. The default loopback URL reaches the app on port 8000; it does not by itself prevent scheduled runs. For hosted MCP OAuth, set a public AGENTOS_URL and run ./scripts/gcp/env-sync.sh.
down.sh is targeting a different region than the one you deployed to. up.sh records GCP_REGION in your env file and down.sh reads it from there; if the file is gone, rerun with GCP_REGION=<region> ./scripts/gcp/down.sh. A wrong-region teardown looks clean while the real resources keep billing.