household-bot/docs/runbooks/first-deploy.md

First Deployment Runbook

Purpose

Execute the first real deployment with a repeatable sequence that covers infrastructure, secrets, webhook cutover, smoke checks, scheduler rollout, and rollback.

Preconditions

• main is green in CI.
• Terraform baseline has already been reviewed for the target environment.
• You have access to:
  • GCP project
  • GitHub repo settings
  • Telegram bot token
  • Supabase project and database URL

Required Configuration Inventory

Terraform variables

Required in your environment *.tfvars:

• project_id
• region
• environment
• bot_api_image
• mini_app_image
• bot_household_id
• bot_household_chat_id
• bot_purchase_topic_id

Recommended:

• database_url_secret_id = "database-url"
• telegram_bot_token_secret_id = "telegram-bot-token"
• openai_api_key_secret_id = "openai-api-key"
• optional supabase_url_secret_id = "supabase-url"
• optional supabase_publishable_key_secret_id = "supabase-publishable-key"
• bot_feedback_topic_id
• bot_mini_app_allowed_origins
• scheduler_timezone
• scheduler_paused = true
• scheduler_dry_run = true

Secret Manager values

Create the secret resources via Terraform, then add secret versions for:

• telegram-bot-token
• telegram-webhook-secret
• scheduler-shared-secret
• database-url
• optional openai-api-key
• optional supabase-url
• optional supabase-publishable-key

GitHub Actions secrets

Required for CD:

• GCP_PROJECT_ID
• GCP_WORKLOAD_IDENTITY_PROVIDER
• GCP_SERVICE_ACCOUNT

Recommended:

• DATABASE_URL

GitHub Actions variables

Set if you do not want the defaults:

• GCP_REGION
• ARTIFACT_REPOSITORY
• CLOUD_RUN_SERVICE_BOT
• CLOUD_RUN_SERVICE_MINI

Phase 1: Local Readiness

Run the quality gates locally from the deployment ref:

bun run format:check
bun run lint
bun run typecheck
bun run test
bun run build

If the release includes schema changes, also run:

bun run db:check
E2E_SMOKE_ALLOW_WRITE=true bun run test:e2e

Phase 2: Provision or Reconcile Infrastructure

1. Prepare environment-specific variables:

cp infra/terraform/terraform.tfvars.example infra/terraform/dev.tfvars

2. Initialize Terraform with the correct state bucket:

terraform -chdir=infra/terraform init -backend-config="bucket=<terraform-state-bucket>"

3. Review and apply:

terraform -chdir=infra/terraform plan -var-file=dev.tfvars
terraform -chdir=infra/terraform apply -var-file=dev.tfvars

4. Capture outputs:

BOT_API_URL="$(terraform -chdir=infra/terraform output -raw bot_api_service_url)"
MINI_APP_URL="$(terraform -chdir=infra/terraform output -raw mini_app_service_url)"

5. If you did not know the mini app URL before the first apply, set bot_mini_app_allowed_origins = [\"${MINI_APP_URL}\"] in dev.tfvars and apply again.

Phase 3: Add Runtime Secret Versions

Use the real project ID from Terraform variables:

echo -n "<telegram-bot-token>" | gcloud secrets versions add telegram-bot-token --data-file=- --project <project_id>
echo -n "<telegram-webhook-secret>" | gcloud secrets versions add telegram-webhook-secret --data-file=- --project <project_id>
echo -n "<scheduler-shared-secret>" | gcloud secrets versions add scheduler-shared-secret --data-file=- --project <project_id>
echo -n "<database-url>" | gcloud secrets versions add database-url --data-file=- --project <project_id>

Add optional secret versions only if those integrations are enabled.

For a functional household dev deployment, set database_url_secret_id = "database-url" in dev.tfvars before the apply that creates the Cloud Run services. Otherwise the bot deploys without DATABASE_URL, and finance commands, reminders, mini app auth/dashboard, and anonymous feedback remain disabled.

Keep telegram_bot_token_secret_id = "telegram-bot-token" aligned with the actual bot token secret name. CD uses that secret to sync the Telegram command menu after deploy.

Phase 4: Configure GitHub CD

Populate GitHub repository secrets with the Terraform outputs:

• GCP_PROJECT_ID
• GCP_WORKLOAD_IDENTITY_PROVIDER
• GCP_SERVICE_ACCOUNT
• optional DATABASE_URL

If you prefer the GitHub CLI:

gh secret set GCP_PROJECT_ID
gh secret set GCP_WORKLOAD_IDENTITY_PROVIDER
gh secret set GCP_SERVICE_ACCOUNT
gh secret set DATABASE_URL

Set GitHub repository variables if you want to override the defaults used by .github/workflows/cd.yml.

• optional TELEGRAM_BOT_TOKEN_SECRET_ID
  • only needed if your bot token secret name is not telegram-bot-token

Phase 5: Trigger the First Deployment

You have two safe options:

• Merge the deployment ref into main and let CD run after successful CI.
• Trigger CD manually from the GitHub Actions UI with workflow_dispatch.

The workflow will:

• optionally run bun run db:migrate if DATABASE_URL secret is configured
• build and push bot and mini app images
• deploy both Cloud Run services

Phase 6: Telegram Webhook Cutover

After the bot service is live, set the webhook explicitly:

export TELEGRAM_BOT_TOKEN="$(gcloud secrets versions access latest --secret telegram-bot-token --project <project_id>)"
export TELEGRAM_WEBHOOK_SECRET="$(gcloud secrets versions access latest --secret telegram-webhook-secret --project <project_id>)"
export TELEGRAM_WEBHOOK_URL="${BOT_API_URL}/webhook/telegram"

bun run ops:telegram:webhook set
bun run ops:telegram:webhook info

If you want to discard queued updates during cutover:

export TELEGRAM_DROP_PENDING_UPDATES=true
bun run ops:telegram:webhook set

Phase 7: Post-Deploy Smoke Checks

Run the smoke script:

export BOT_API_URL
export MINI_APP_URL
export TELEGRAM_EXPECTED_WEBHOOK_URL="${BOT_API_URL}/webhook/telegram"

bun run ops:deploy:smoke

The smoke script verifies:

• bot health endpoint
• mini app root delivery
• mini app auth endpoint is mounted
• scheduler endpoint rejects unauthenticated requests
• Telegram webhook matches the expected URL when bot token is provided

Phase 8: Scheduler Enablement

First release:

1. Keep scheduler_paused = true and scheduler_dry_run = true on initial deploy.
2. After smoke checks pass, set scheduler_paused = false and apply Terraform.
3. Trigger one job manually:

gcloud scheduler jobs run household-dev-utilities --location <region> --project <project_id>

4. Verify the reminder request succeeded and produced dryRun: true logs.
5. Set scheduler_dry_run = false and apply Terraform.
6. Trigger one job again and verify the delivery side behaves as expected.

Rollback

If the release is unhealthy:

1. Pause scheduler jobs again in Terraform:

terraform -chdir=infra/terraform apply -var-file=dev.tfvars -var='scheduler_paused=true'

2. Move Cloud Run traffic back to the last healthy revision:

gcloud run revisions list --service <bot-service-name> --region <region> --project <project_id>
gcloud run services update-traffic <bot-service-name> --region <region> --project <project_id> --to-revisions <previous-revision>=100
gcloud run revisions list --service <mini-service-name> --region <region> --project <project_id>
gcloud run services update-traffic <mini-service-name> --region <region> --project <project_id> --to-revisions <previous-revision>=100

3. If webhook traffic must stop immediately:

bun run ops:telegram:webhook delete

4. If migrations were additive, leave schema in place and roll application code back.
5. If a destructive migration failed, stop and use the rollback SQL prepared in that PR.

Dev-to-Prod Promotion Notes

• Repeat the same sequence in a separate prod.tfvars and Terraform state.
• Keep separate GCP projects for dev and prod when possible.
• Do not unpause production scheduler jobs until prod smoke checks are complete.