Automated Kubernetes testing with Robot Framework, ArgoCD & with KinD lifecycle
Overview
This n8n workflow provides automated CI/CD testing for Kubernetes applications using KinD (Kubernetes in Docker). It creates temporary infrastructure, runs tests, and cleans up everything automatically.
Three-Phase Lifecycle
INIT Phase - Infrastructure Setup
- Installs dependencies (sshpass, Docker, KinD)
- Creates KinD cluster
- Installs Helm and Nginx Ingress
- Installs HAProxy for port forwarding
- Deploys ArgoCD
- Applies ApplicationSet
TEST Phase - Automated Testing
- Downloads Robot Framework test script from GitLab
- Installs Robot Framework and Browser library
- Executes automated browser tests
- Packages test results
- Sends results via Telegram
DESTROY Phase - Complete Cleanup
- Removes HAProxy
- Deletes KinD cluster
- Uninstalls KinD
- Uninstalls Docker
- Sends completion notification
Execution Modes
Full Pipeline Mode (progress_only = false)
> Automatically progresses through all phases: INIT → TEST → DESTROY
Single Phase Mode (progress_only = true)
> Executes only the specified phase and stops
Prerequisites
Local Environment (n8n Host)
- n8n instance version 1.0 or higher
- Community node
n8n-nodes-robotframeworkinstalled - Network access to target host and GitLab
- Minimum 4 GB RAM, 20 GB disk space
Remote Target Host
- Linux server (Ubuntu, Debian, CentOS, Fedora, or Alpine)
- SSH access with sudo privileges
- Minimum 8 GB RAM (16 GB recommended)
- 20 GB free disk space
- Open ports:
22,80,60080,60443,56443
External Services
- GitLab account with OAuth2 application
- Repository with test files (
test.robot,config.yaml,demo-applicationSet.yaml) - Telegram Bot for notifications
- Telegram Chat ID
Setup Instructions
Step 1: Install Community Node
- In n8n web interface, navigate to Settings → Community Nodes
- Install
n8n-nodes-robotframework - Restart n8n if prompted
Step 2: Configure GitLab OAuth2
Create GitLab OAuth2 Application
- Log in to GitLab
- Navigate to User Settings → Applications
- Create new application with redirect URI:
https://your-n8n-instance.com/rest/oauth2-credential/callback - Grant scopes:
read_api,read_repository,read_user - Copy Application ID and Secret
Configure in n8n
- Create new GitLab OAuth2 API credential
- Enter GitLab server URL, Client ID, and Secret
- Connect and authorize
Step 3: Prepare GitLab Repository
Create repository structure:
your-repo/
├── test.robot
├── config.yaml
├── demo-applicationSet.yaml
└── .gitlab-ci.yml
Upload your:
- Robot Framework test script
- KinD cluster configuration
- ArgoCD ApplicationSet manifest
Step 4: Configure Telegram Bot
Create Bot
- Open Telegram, search for @BotFather
- Send
/newbotcommand - Save the API token
Get Chat ID
For personal chat:
- Send message to your bot
- Visit:
https://api.telegram.org/bot<YOUR_TOKEN>/getUpdates - Copy the chat ID (positive number)
For group chat:
- Add bot to group
- Send message mentioning the bot
- Visit getUpdates endpoint
- Copy group chat ID (negative number)
Configure in n8n
- Create Telegram API credential
- Enter bot token
- Save credential
Step 5: Prepare Target Host
Verify SSH access:
- Test connection:
ssh -p <port> <username>@<host_ip> - Verify sudo:
sudo -v
The workflow will automatically install dependencies.
Step 6: Import and Configure Workflow
Import Workflow
- Copy workflow JSON
- In n8n, click Workflows → Import from File/URL
- Import the JSON
Configure Parameters
Open Set Parameters node and update:
| Parameter | Description | Example |
|-----------|-------------|---------|
| target_host | IP address of remote host | 192.168.1.100 |
| target_port | SSH port | 22 |
| target_user | SSH username | ubuntu |
| target_password | SSH password | your_password |
| progress | Starting phase | INIT, TEST, or DESTROY |
| progress_only | Execution mode | true or false |
| KIND_CONFIG | Path to config.yaml | config.yaml |
| ROBOT_SCRIPT | Path to test.robot | test.robot |
| ARGOCD_APPSET | Path to ApplicationSet | demo-applicationSet.yaml |
> Security: Use n8n credentials or environment variables instead of storing passwords in the workflow.
Configure GitLab Nodes
For each of the three GitLab nodes:
- Set Owner (username or organization)
- Set Repository name
- Set File Path (uses parameter from Set Parameters)
- Set Reference (branch:
mainormaster) - Select Credentials (GitLab OAuth2)
Configure Telegram Nodes
-
Send ROBOT Script Export Pack node:
- Set Chat ID
- Select Credentials
-
Process Finish Report node:
- Update chat ID in command
Step 7: Test and Execute
- Test individual components first
- Run full workflow
- Monitor execution (30-60 minutes total)
How to Use
Execution Examples
Complete Testing Pipeline
progress = "INIT"progress_only = "false"- Flow: INIT → TEST → DESTROY
Setup Infrastructure Only
progress = "INIT"progress_only = "true"- Flow: INIT → Stop
Test Existing Infrastructure
progress = "TEST"progress_only = "false"- Flow: TEST → DESTROY
Cleanup Only
progress = "DESTROY"- Flow: DESTROY → Complete
Trigger Methods
1. Manual Execution
- Open workflow in n8n
- Set parameters
- Click Execute Workflow
2. Scheduled Execution
- Open Schedule Trigger node
- Configure time (default: 1 AM daily)
- Ensure workflow is Active
3. Webhook Trigger
- Configure webhook in GitLab repository
- Add webhook URL to GitLab CI
Monitoring Execution
In n8n Interface:
- View progress in Executions tab
- Watch node-by-node execution
- Check output details
Via Telegram:
- Receive test results after TEST phase
- Receive completion notification after DESTROY phase
Execution Timeline: | Phase | Duration | |-------|----------| | INIT | 15-25 minutes | | TEST | 5-10 minutes | | DESTROY | 5-10 minutes |
Understanding Test Results
After TEST phase, receive testing-export-pack.tar.gz via Telegram containing:
log.html- Detailed test execution logreport.html- Test summary reportoutput.xml- Machine-readable resultsscreenshots/- Browser screenshots
To view:
- Download
.tar.gzfrom Telegram - Extract:
tar -xzf testing-export-pack.tar.gz - Open
report.htmlfor summary - Open
log.htmlfor detailed steps
Success indicators:
- All tests marked PASS
- Screenshots show expected UI states
- No error messages in logs
Failure indicators:
- Tests marked FAIL
- Error messages in logs
- Unexpected UI states in screenshots
Configuration Files
test.robot
Robot Framework test script structure:
- Uses Browser library
- Connects to
http://autotest.innersite - Logs in with
autotest/autotest - Takes screenshots
- Runs in headless Chromium
config.yaml
KinD cluster configuration:
- 1 control-plane node
- 1 worker node
- Port mappings:
60080(HTTP),60443(HTTPS),56443(API) - Kubernetes version:
v1.30.2
demo-applicationSet.yaml
ArgoCD Application manifest:
- Points to Git repository
- Automatic sync enabled
- Deploys to default namespace
gitlab-ci.yml
Triggers n8n workflow on commits:
- Installs curl
- Sends POST request to webhook
Troubleshooting
SSH Permission Denied
Symptoms:
Error: Permission denied (publickey,password)
Solutions:
- Verify password is correct
- Check SSH authentication method
- Ensure user has sudo privileges
- Use SSH keys instead of passwords
Docker Installation Fails
Symptoms:
Error: Package docker-ce is not available
Solutions:
- Check OS version compatibility
- Verify network connectivity
- Manually add Docker repository
KinD Cluster Creation Timeout
Symptoms:
Error: Failed to create cluster: timed out
Solutions:
- Check available resources (RAM/CPU/disk)
- Verify Docker daemon status
- Pre-pull images
- Increase timeout
ArgoCD Not Accessible
Symptoms:
Error: Failed to connect to autotest.innersite
Solutions:
- Check HAProxy status:
systemctl status haproxy - Verify
/etc/hostsentry - Check Ingress:
kubectl get ingress -n argocd - Test port forwarding:
curl http://127.0.0.1:60080
Robot Framework Tests Fail
Symptoms:
Error: Chrome failed to start
Solutions:
- Verify Chromium installation
- Check Browser library:
rfbrowser show-trace - Ensure correct
executablePathin test.robot - Install missing dependencies
Telegram Notification Not Received
Symptoms:
- Workflow completes but no message
Solutions:
- Verify Chat ID
- Test Telegram API manually
- Check bot status
- Re-add bot to group
Workflow Hangs
Symptoms:
- Node shows "Executing..." indefinitely
Solutions:
- Check n8n logs
- Test SSH connection manually
- Verify target host status
- Add timeouts to commands
Best Practices
Development Workflow
-
Test locally first
- Run Robot Framework tests on local machine
- Verify test script syntax
-
Version control
- Keep all files in Git
- Use branches for experiments
- Tag stable versions
-
Incremental changes
- Make small testable changes
- Test each change separately
-
Backup data
- Export workflow regularly
- Save test results
- Store credentials securely
Production Deployment
-
Separate environments
- Dev: Frequent testing
- Staging: Pre-production validation
- Production: Stable scheduled runs
-
Monitoring
- Set up execution alerts
- Monitor host resources
- Track success/failure rates
-
Disaster recovery
- Document cleanup procedures
- Keep backup host ready
- Test restoration process
-
Security
- Use SSH keys
- Rotate credentials quarterly
- Implement network segmentation
Maintenance Schedule
| Frequency | Tasks | |-----------|-------| | Daily | Review logs, check notifications | | Weekly | Review failures, check disk space | | Monthly | Update dependencies, test recovery | | Quarterly | Rotate credentials, security audit |
Advanced Topics
Custom Configurations
Multi-node clusters:
- Add more worker nodes for production-like environments
- Configure resource limits
- Add custom port mappings
Advanced testing:
- Load testing with multiple iterations
- Integration testing for full deployment pipeline
- Chaos engineering with failure injection
Integration with Other Tools
Monitoring:
- Prometheus for metrics collection
- Grafana for visualization
Logging:
- ELK stack for log aggregation
- Custom dashboards
CI/CD Integration:
- Jenkins pipelines
- GitHub Actions
- Custom webhooks
Resource Requirements
Minimum
| Component | CPU | RAM | Disk | |-----------|-----|-----|------| | n8n Host | 2 | 4 GB | 20 GB | | Target Host | 4 | 8 GB | 20 GB |
Recommended
| Component | CPU | RAM | Disk | |-----------|-----|-----|------| | n8n Host | 4 | 8 GB | 50 GB | | Target Host | 8 | 16 GB | 50 GB |
Useful Commands
KinD
- List clusters:
kind get clusters - Get kubeconfig:
kind get kubeconfig --name automate-tst - Export logs:
kind export logs --name automate-tst
Docker
- List containers:
docker ps -a --filter "name=automate-tst" - Enter control plane:
docker exec -it automate-tst-control-plane bash - View logs:
docker logs automate-tst-control-plane
Kubernetes
- Get all resources:
kubectl get all -A - Describe pod:
kubectl describe pod -n argocd <pod-name> - View logs:
kubectl logs -n argocd <pod-name> --follow - Port forward:
kubectl port-forward -n argocd svc/argocd-server 8080:80
Robot Framework
- Run tests:
robot test.robot - Run specific test:
robot -t "Test Name" test.robot - Generate report:
robot --outputdir results test.robot
Additional Resources
Official Documentation
- n8n: https://docs.n8n.io
- KinD: https://kind.sigs.k8s.io
- ArgoCD: https://argo-cd.readthedocs.io
- Robot Framework: https://robotframework.org
- Browser Library: https://marketsquare.github.io/robotframework-browser
Community
- n8n Community: https://community.n8n.io
- Kubernetes Slack: https://kubernetes.slack.com
- ArgoCD Slack: https://argoproj.github.io/community/join-slack
- Robot Framework Forum: https://forum.robotframework.org
Related Projects
- k3s: Lightweight Kubernetes distribution
- minikube: Local Kubernetes alternative
- Flux CD: Alternative GitOps tool
- Playwright: Alternative browser automation
Automated Kubernetes Testing with Robot Framework and ArgoCD (Kind Lifecycle)
This n8n workflow automates the process of setting up a local Kubernetes cluster using Kind, deploying applications with ArgoCD, running Robot Framework tests, and then tearing down the cluster. It provides a robust CI/CD-like pipeline for testing Kubernetes deployments locally.
Description
This workflow streamlines the entire lifecycle of testing Kubernetes applications. It starts by creating a temporary Kind cluster, installs ArgoCD, deploys a specified application, executes Robot Framework tests against the deployed application, and finally cleans up the Kind cluster. This allows for rapid, isolated, and repeatable testing of Kubernetes deployments without impacting production or shared development environments.
What it does
- Triggers: The workflow can be initiated manually or on a scheduled basis.
- Initial Setup:
- Sets a variable
KIND_CLUSTER_NAMEto "n8n-kind-robot-test". - Executes a shell command to delete any existing Kind cluster with that name, ensuring a clean slate.
- Executes a shell command to create a new Kind cluster.
- Sets a variable
- ArgoCD Installation:
- Executes a shell command to install ArgoCD CLI.
- Executes a shell command to apply ArgoCD manifests to the Kind cluster.
- Waits for ArgoCD pods to be ready.
- Retrieves the initial admin password for ArgoCD.
- Forwards the ArgoCD server port for local access.
- Logs into ArgoCD using the retrieved password.
- Application Deployment with ArgoCD:
- Executes a shell command to add a Git repository to ArgoCD (e.g.,
https://github.com/argoproj/argocd-example-apps.git). - Executes a shell command to create an ArgoCD application (e.g.,
guestbook) within the Kind cluster. - Waits for the ArgoCD application to be healthy.
- Executes a shell command to add a Git repository to ArgoCD (e.g.,
- Robot Framework Test Execution:
- Executes a shell command to run Robot Framework tests. This step assumes your Robot Framework test suite is available on the n8n host and configured to target the deployed application.
- Conditional Cleanup:
- If tests pass:
- Sends a success message to a specified Telegram chat.
- Executes a shell command to delete the Kind cluster.
- If tests fail:
- Sends a failure message to a specified Telegram chat.
- Executes a shell command to delete the Kind cluster.
- If tests pass:
- GitLab Integration (Optional/Unconnected): The workflow includes an unconnected GitLab node, suggesting potential for future integration with GitLab events (e.g., triggering tests on push to a repository).
Prerequisites/Requirements
- n8n Instance: A running n8n instance with access to the underlying operating system's shell commands.
- Kind (Kubernetes in Docker): Docker must be installed and running on the n8n host. Kind CLI should be installed or the workflow should be modified to install it.
- kubectl: Kubernetes command-line tool installed on the n8n host.
- ArgoCD CLI: ArgoCD CLI installed on the n8n host or installed by the workflow itself (as seen in the JSON).
- Robot Framework: Robot Framework and its dependencies must be installed on the n8n host, along with your test suite.
- Telegram Account: A Telegram bot token and a chat ID for sending notifications.
- GitLab Account (Optional): If you plan to integrate with GitLab, a GitLab API token will be required.
Setup/Usage
- Import the Workflow: Import the provided JSON into your n8n instance.
- Configure Credentials:
- Telegram: Set up a Telegram credential with your bot token.
- Customize Shell Commands: Review and modify the "Execute Command" nodes to match your specific environment and testing needs:
- Kind Cluster Name: Adjust
KIND_CLUSTER_NAMEif desired. - ArgoCD Application: Update the
argocd app createcommand with your application's repository URL, path, and destination. - Robot Framework Tests: Ensure the
robotcommand points to your actual Robot Framework test suite and any necessary arguments.
- Kind Cluster Name: Adjust
- Telegram Notifications: Update the "Telegram" nodes with your target
Chat IDfor success and failure notifications. - Activate the Workflow: Enable the workflow.
- Trigger the Workflow:
- Manually execute the workflow using the "When clicking ‘Execute workflow’" trigger.
- Set up a schedule using the "Schedule Trigger" node for automated periodic testing.
Related Templates
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Track personal finances in Google Sheets with AI agent via Slack
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How it works Scheduled Daily Check-in (11 PM) Fetches current balances from Google Sheets Retrieves all active debts Formats and sends a Slack message with balance summary Prompts you to share the day's transactions AI Agent Transaction Processing When you mention the bot in Slack: Phase 1: Parse & Analyze Extracts amount, payment type (cash/online), category (food, travel, etc.) Identifies transaction type (expense, income, borrowed, lent, repaid) Stores conversation context in PostgreSQL memory Phase 2: Calculate & Preview Reads current balances from Google Sheets Calculates new balances based on transactions Shows formatted preview with projected changes Waits for your approval ("yes"/"no") Phase 3: Update Database (only after approval) Logs transactions with unique IDs and timestamps Updates debt records with person names and status Recalculates and stores new balances Handles debt lifecycle (Active → Settled) Phase 4: Confirmation Sends success message with updated balances Shows active debts summary Includes logging timestamp Requirements Essential Services: n8n instance (self-hosted or cloud) Slack workspace with admin access Google account Google Gemini API key PostgreSQL database Recommended: Claude AI model (mentioned in workflow notes as better alternative to Gemini) How to set up Google Sheets Setup Create a new Google Sheet with three tabs named exactly: Balances Tab: | Date | CashBalance | OnlineBalance | Total_Balance | |------|--------------|----------------|---------------| Transactions Tab: | TransactionID | Date | Time | Amount | PaymentType | Category | TransactionType | PersonName | Description | Added_At | |----------------|------|------|--------|--------------|----------|------------------|-------------|-------------|----------| Debts Tab: | PersonName | Amount | Type | Datecreated | Status | Notes | |-------------|--------|------|--------------|--------|-------| Add header rows and one initial balance row in the Balances tab with today's date and starting amounts. Slack App Setup Go to api.slack.com/apps and create a new app Under OAuth & Permissions, add these Bot Token Scopes: app_mentions:read chat:write channels:read Install the app to your workspace Copy the Bot User OAuth Token Create a dedicated channel (e.g., personal-finance-tracker) Invite your bot to the channel Google Gemini API Visit ai.google.dev Create an API key Save it for n8n credentials setup PostgreSQL Database Set up a PostgreSQL database (you can use Supabase free tier): Create a new project Note down connection details (host, port, database name, user, password) The workflow will auto-create the required table n8n Workflow Configuration Import the workflow and configure: A. Credentials Google Sheets OAuth2: Connect your Google account Slack API: Add your Bot User OAuth Token Google Gemini API: Add your API key PostgreSQL: Add database connection details B. Update Node Parameters All Google Sheets nodes: Select your finance spreadsheet Slack nodes: Select your finance channel Schedule Trigger: Adjust time if you prefer a different check-in hour (default: 11 PM) Postgres Chat Memory: Change sessionKey to something unique (e.g., financetrackeryour_name) Keep tableName as n8nchathistory_finance or rename consistently C. Slack Trigger Setup Activate the "Bot Mention trigger" node Copy the webhook URL from n8n In Slack App settings, go to Event Subscriptions Enable events and paste the webhook URL Subscribe to bot event: app_mention Save changes Test the Workflow Activate both workflow branches (scheduled and agent) In your Slack channel, mention the bot: @YourBot ₹100 cash snacks Bot should respond with a preview Reply "yes" to approve Verify Google Sheets are updated How to customize Change Transaction Categories Edit the AI Agent's system message to add/remove categories. Current categories: travel, food, entertainment, utilities, shopping, health, education, other Modify Daily Check-in Time Change the Schedule Trigger's triggerAtHour value (0-23 in 24-hour format). Add Currency Support Replace ₹ with your currency symbol in: Format Daily Message code node AI Agent system prompt examples Switch AI Models The workflow uses Google Gemini, but notes recommend Claude. To switch: Replace "Google Gemini Chat Model" node Add Claude credentials Connect to AI Agent node Customize Debt Types Modify AI Agent's system prompt to change debt handling logic: Currently: IOwe and TheyOwe_Me You can add more types or change naming Add More Payment Methods Current: cash, online To add more (e.g., credit card): Update AI Agent prompt Modify Balances sheet structure Update balance calculation logic Change Approval Keywords Edit AI Agent's Phase 2 approval logic to recognize different approval phrases. Add Spending Analytics Extend the daily check-in to calculate: Weekly/monthly spending summaries Category-wise breakdowns Use additional Code nodes to process transaction history Important Notes ⚠️ Never trigger with normal messages - Only use app mentions (@botname) to avoid infinite loops where the bot replies to its own messages. 💡 Context Awareness - The bot remembers conversation history, so you can reference "yesterday", "last week", or previous transactions naturally. 🔒 Data Privacy - All your financial data stays in your Google Sheets and PostgreSQL database. The AI only processes transaction text temporarily. 📊 Backup Regularly - Export your Google Sheets periodically as backup. --- Pro Tips: Start with small test transactions to ensure everything works Use consistent person names for debt tracking The bot understands various formats: "₹500 cash food" = "paid 500 rupees in cash for food" You can batch transactions in one message: "₹100 travel, ₹200 food, ₹50 snacks"