Healthchecks on Cloud Run — Lab Guide

Overview

Estimated time: 45–60 minutes

Healthchecks is an open-source, self-hosted cron job and heartbeat monitoring service: scheduled tasks "ping" it on success, and it alerts you when a ping is late or missing. This lab takes you through the full operational lifecycle of the Healthchecks on Cloud Run module on Google Cloud: deploy it, access and verify it, run it day-to-day, observe it, diagnose common problems, and tear it down.

The lab focuses on operating the Cloud Run module and the Google Cloud platform, not on Healthchecks product features. For the complete list of provisioned services and every configuration input (organised by group), see the Configuration Guide — this lab deliberately does not duplicate that detail so it stays accurate over time.

Objectives

By the end of this lab you will be able to:

Deploy the module from the RAD platform and locate the resources it provisions.
Access and verify the running service, and log in with the seeded admin account.
Perform day-2 operations — inspect, scale, update, and manage secrets.
Observe the service with Cloud Logging and Cloud Monitoring.
Diagnose and resolve the most common deployment and runtime issues.
Tear the deployment down cleanly.

Prerequisites

Services_GCP deployed in the target project (provides the VPC, Cloud SQL networking, Artifact Registry, and shared service accounts this module depends on).
A Google Cloud project with billing enabled.
gcloud CLI authenticated: gcloud auth login and gcloud auth application-default login.
Project Owner (or equivalent) IAM on the project.
RAD platform access with permission to deploy modules into the project.

Set these shell variables once; every task below reuses them:

export PROJECT="<your-gcp-project-id>"
export REGION="us-central1"          # the region you deploy into

Task 1 — Deploy the module [Automated]

In the RAD platform, open Healthchecks (Cloud Run), set project_id, and review the inputs. Configure only what you need — the Configuration Guide documents every input by group, with defaults. Review the estimated cost (if credits are enabled) and click Deploy, which opens the deployment status page with real-time logs.
The platform provisions the Cloud Run service, a Cloud SQL (PostgreSQL 15) database with its Secret Manager secrets (SECRET_KEY, ADMIN_PASSWORD, and the database password), and runs two one-shot jobs: db-init (creates the database and role) and admin-bootstrap (runs migrations and seeds the initial superuser account). First deploys take roughly 15–25 minutes (Cloud SQL creation dominates).

When it completes, discover the resources with name-agnostic filters (so the commands keep working regardless of the deployment suffix):

SERVICE=$(gcloud run services list --project="$PROJECT" --region="$REGION" \
  --filter="metadata.name~healthchecks" --format="value(metadata.name)" --limit=1)
SERVICE_URL=$(gcloud run services describe "$SERVICE" \
  --project="$PROJECT" --region="$REGION" --format="value(status.url)")
echo "Service: $SERVICE"
echo "URL:     $SERVICE_URL"

Task 2 — Access & verify [Manual]

Confirm the service is up and serving the login page (Healthchecks has no dedicated health endpoint — the root page is the public, unauthenticated signal):
```
curl -s -o /dev/null -w '%{http_code} %{size_download}\n' "$SERVICE_URL/"
# expect 200 (or a redirect in the 300 range) and a non-zero body size
```
Retrieve the seeded admin credential and log in:
```
ADMIN_SECRET=$(gcloud secrets list --project="$PROJECT" \
  --filter="name~healthchecks-admin-password" --format="value(name)" --limit=1)
gcloud secrets versions access latest --secret="$ADMIN_SECRET" --project="$PROJECT"
```
Open $SERVICE_URL in a browser, sign in with admin_email (default admin@techequity.cloud, or whatever value you configured) and the password above. You should land on the empty checks dashboard.
Create a test check from the UI (or via the API) and confirm it appears in the dashboard — this proves the database write path is working end-to-end, not just that the login page rendered.

Task 3 — Operate & keep it running (Day-2) [Manual]

Inspect the service and its revisions:

gcloud run services describe "$SERVICE" --project="$PROJECT" --region="$REGION"
gcloud run revisions list --service="$SERVICE" --project="$PROJECT" --region="$REGION"

Do not scale to zero carelessly. This module defaults to min_instance_count = 1 and cpu_always_allocated = true specifically so the co-located sendalerts/sendreports background loop keeps noticing missed check-ins. If you scale to min_instance_count = 0 or flip cpu_always_allocated = false to save cost, understand that alerting may become unreliable while the service is idle.
Update the application version tag by changing the version input in the RAD platform and applying it via Update; a new revision rolls out using the same official healthchecks/healthchecks image at the new tag.

Manage secrets:

gcloud secrets list --project="$PROJECT" --filter="name~healthchecks"
gcloud run jobs list --project="$PROJECT" --region="$REGION"   # db-init + admin-bootstrap

Configure real outbound email (required for alerts to actually be delivered — the default DEFAULT_FROM_EMAIL is a placeholder): set EMAIL_HOST, EMAIL_PORT, EMAIL_HOST_USER via environment_variables and EMAIL_HOST_PASSWORD via secret_environment_variables, then apply.

Open a database session for inspection or maintenance:

INSTANCE=$(gcloud sql instances list --project="$PROJECT" --format="value(name)" --limit=1)
gcloud sql connect "$INSTANCE" --user=healthchecks_user --project="$PROJECT"

Task 4 — Observe: Logging & Monitoring [Manual]

Logs — from the CLI or the Logs Explorer. The same log stream carries both the web server AND the sendalerts/sendreports background workers (they run in the same container):
```
gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" --limit=50
```
Logs Explorer filter: resource.type="cloud_run_revision" AND resource.labels.service_name="<service>".
Monitoring — open the Cloud Run dashboard for the service and review request count, request latency, instance count, and CPU/memory utilisation. Since this service defaults to always-on (min_instance_count = 1), expect steady low-level CPU usage from the background alert loop even with zero HTTP traffic. The module can provision an uptime check (when uptime_check_config.enabled = true — it defaults to false); if enabled, confirm it is green under Monitoring → Uptime checks.

Task 5 — Troubleshoot & debug [Manual]

Durable techniques for the failure modes you are most likely to hit. These are platform-level diagnostics and do not change with Healthchecks releases.

Revision unhealthy / service won't serve: inspect the latest revision and its logs for startup errors, and confirm env vars and secrets resolved. The startup probe targets / with a 60-second initial delay.
```
gcloud run revisions list --service="$SERVICE" --project="$PROJECT" --region="$REGION"
gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" --limit=100
```
Database connection errors: confirm the Cloud SQL instance is RUNNABLE, the DB password secret exists, and the db-init job completed successfully.
Login page loads but the app seems to be using SQLite / data resets on restart: confirm the DB env var actually resolved to "postgres" on the running revision — this is the single most important setting to verify.
```
gcloud run revisions describe <revision-name> --project="$PROJECT" --region="$REGION" \
  --format=json | grep -A2 '"name": "DB"'
```
Can't log in with the seeded credential: confirm the admin-bootstrap job actually completed (it depends on db-init finishing first):
```
gcloud run jobs executions list --job="${SERVICE}-admin-bootstrap" \
  --project="$PROJECT" --region="$REGION"
```
Alerts never arrive: this is very likely a missing/placeholder SMTP configuration (DEFAULT_FROM_EMAIL/EMAIL_HOST), not a platform bug — check the service logs for SMTP connection errors from sendalerts.
Image build failed: this module deploys the official prebuilt image with container_image_source = "prebuilt" — there should be no build step at all. If you see a Cloud Build failure, check whether container_image_source was accidentally overridden to "custom".
403 / permission errors: verify the runtime service account's IAM roles.

See the Configuration Guide's Configuration Pitfalls section for setting-specific gotchas.

Task 6 — Tear down [Automated]

On the Deployments page, open the deployment and click the Trash icon (Delete). Delete runs terraform destroy and is irreversible (the deployment record is retained for history). If a deployment is stuck and the RAD platform can no longer manage it (for example after manual changes that conflict with the Terraform state), use Purge instead — it removes the deployment from RAD's records without destroying the cloud resources (it makes RAD forget the project). This removes everything the module created — the Cloud Run service, Cloud SQL database, and Secret Manager secrets. Resources owned by Services_GCP (the VPC, shared Cloud SQL, registry) are managed separately and are not removed here.

Summary

Task	Type	Outcome
1 — Deploy	Automated	Module provisions Cloud Run, Cloud SQL (PostgreSQL 15), secrets, and runs `db-init` + `admin-bootstrap`
2 — Access & verify	Manual	Login page loads; sign in with the seeded admin credential; create a test check
3 — Operate	Manual	Inspect revisions, update version, manage secrets, configure SMTP, DB access
4 — Observe	Manual	Query Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — Troubleshoot	Manual	Diagnose revision, database engine, admin-bootstrap, and SMTP issues
6 — Tear down	Automated	Delete (Trash) removes all module resources

By Dr Shiyghan Emmanuel Navti · Google Cloud certified: ACE · PCA · PCD · PDE · PSE · CDL

Overview​

Objectives​

Prerequisites​

Task 1 — Deploy the module [Automated]​

Task 2 — Access & verify [Manual]​

Task 3 — Operate & keep it running (Day-2) [Manual]​

Task 4 — Observe: Logging & Monitoring [Manual]​

Task 5 — Troubleshoot & debug [Manual]​

Task 6 — Tear down [Automated]​

Summary​