LimeSurvey on Cloud Run — Lab Guide

Overview

Estimated time: 45–90 minutes

LimeSurvey is a free, open-source (GPL) online survey and questionnaire platform written in PHP, supporting unlimited surveys, conditional branching, quotas, and multi-language questionnaires. This lab takes you through the full operational lifecycle of the LimeSurvey 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 LimeSurvey survey-authoring 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, including the first-run super-admin login.
Perform day-2 operations — inspect, scale, update, and manage secrets and uploads.
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, Filestore/NFS, 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 LimeSurvey (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 (MySQL 8.0) database with its Secret Manager secrets (ADMIN_PASSWORD and the database password), a Cloud Filestore (NFS) instance for the upload directory, a dedicated limesurvey-uploads Cloud Storage bucket, builds the container image, and runs a one-shot db-init job that creates the empty database and user. LimeSurvey's own console installer then builds the schema on first container start. First deploys take roughly 20–35 minutes (Cloud SQL and Filestore creation dominate), plus a few extra minutes on the very first boot for the schema install.

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="$REGION" \
  --filter="metadata.name~limesurvey" --format="value(metadata.name)" --limit=1)
SERVICE_URL=$(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 healthy. LimeSurvey's liveness probe is an unauthenticated GET / on the landing page — allow generous time on the very first request while the console installer finishes building the schema:
```
curl -s -o /dev/null -w "%{http_code}\n" "$SERVICE_URL/"   # expect 200
```

Retrieve the auto-generated super-admin password from Secret Manager:

gcloud secrets versions access latest \
  --secret="$(gcloud secrets list --project="$PROJECT" \
    --filter='name~admin-password' --format='value(name)' | head -1)" \
  --project="$PROJECT"

Open $SERVICE_URL in a browser and sign in to the admin panel (/admin) as admin / admin@techequity.cloud using the password retrieved above. Create a test survey to confirm the database and upload paths both work end to end.

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

Inspect the service and its revisions (each deploy creates an immutable revision; traffic shifts to the newest healthy one):

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

Scale by changing the min/max instance inputs and clicking Update on the deployment details page — the module owns the service spec, so scaling is a configuration change, not a manual gcloud edit (a manual edit would be reverted on the next apply). Keep max_instance_count = 1 unless shared NFS + session handling for multiple instances has been confirmed — LimeSurvey keeps PHP session state.
Update the application version by changing the version input in the RAD platform and applying it via Update; a new image builds and a new revision rolls out. latest resolves to the pinned 6-apache tag — pin it explicitly in production to avoid an unplanned schema upgrade.

Manage secrets, uploads, and jobs:

gcloud secrets list --project="$PROJECT" --filter="name~limesurvey"
gcloud run jobs list --project="$PROJECT" --region="$REGION"        # db-init job
gcloud storage ls "gs://$(gcloud storage buckets list --project="$PROJECT" \
  --filter='name~limesurvey-uploads' --format='value(name)' | head -1)"

Open a database session for inspection or maintenance:

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

Task 4 — Observe: Logging & Monitoring [Manual]

Logs — from the CLI or the Logs Explorer:
```
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 (P50/P95/P99), instance count (scaling behaviour), and CPU / memory utilisation. Also check the Filestore instance's capacity and throughput metrics, since survey uploads accumulate there. The module also provisions an uptime check; confirm it is green under Monitoring → Uptime checks, and review Alerting → Policies.

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 LimeSurvey releases.

Every page 500s with "table settings_global not found": the console installer's schema creation silently failed — almost always a storage-engine problem (the image defaults to MyISAM, which Cloud SQL disables; this module forces InnoDB) or the installer could not reach the database. Check the container logs from the very first boot.
```
gcloud run revisions list --service="$SERVICE" --project="$PROJECT" --region="$REGION"
gcloud run services logs read "$SERVICE" --project="$PROJECT" --region="$REGION" --limit=200
```
Service exits immediately on boot: ADMIN_PASSWORD is required — the container exits 1 without it. Confirm the secret exists and resolved into the revision.

db-init job failed: list executions and read the failed one's logs:

gcloud run jobs executions list --job="${SERVICE}-db-init" \
  --project="$PROJECT" --region="$REGION"

Uploaded assets vanish after a restart: confirm enable_nfs = true and that the Filestore instance is reachable — without NFS, /var/www/html/upload is ephemeral.
Database connection errors: confirm the Cloud SQL instance is RUNNABLE and, since this module connects over private-IP TCP by default (enable_cloudsql_volume = false), that the service has VPC egress to reach it.
Image build failed: review Cloud Build history for the failed build's log.

See the Configuration Guide's Configuration Pitfalls section for setting-specific gotchas (including the critical rule to never revert the forced InnoDB engine, and to never rename db_name/db_user after first deploy).

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, Cloud Filestore instance, Secret Manager secrets, GCS buckets, and Artifact Registry images. 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 (MySQL 8.0), Filestore (NFS), storage bucket, secrets, and runs db-init
2 — Access & verify	Manual	Health check passes; retrieve admin password; log in and create a test survey
3 — Operate	Manual	Inspect revisions, scale, update version, manage secrets/uploads, DB access
4 — Observe	Manual	Query Cloud Logging; review Cloud Monitoring metrics and uptime check
5 — Troubleshoot	Manual	Diagnose schema-install, boot, init-job, NFS, and database 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​