# Nomad Job Management Guide This guide explains the complete process of creating, deploying, monitoring, and troubleshooting Nomad jobs using the Nomad MCP service. It's designed to be used by both humans and AI assistants to effectively manage containerized applications in a Nomad cluster. ## Prerequisites - Access to a Nomad cluster - Nomad MCP service installed and running - Proper environment configuration (NOMAD_ADDR, NOMAD_NAMESPACE, etc.) - Python with required packages installed ## 1. Creating a Nomad Job Specification A Nomad job specification defines how your application should run. This can be created in two formats: ### Option A: Using a .nomad HCL File ```hcl job "your-job-name" { datacenters = ["dc1"] type = "service" namespace = "development" group "app" { count = 1 network { port "http" { to = 8000 } } task "app-task" { driver = "docker" config { image = "your-registry/your-image:tag" ports = ["http"] command = "python" args = ["-m", "uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"] # Mount volumes if needed mount { type = "bind" source = "local/app-code" target = "/app" readonly = false } } # Pull code from Git repository if needed artifact { source = "git::ssh://git@your-git-server:port/org/repo.git" destination = "local/app-code" options { ref = "main" sshkey = "your-base64-encoded-ssh-key" } } env { # Environment variables PORT = "8000" HOST = "0.0.0.0" LOG_LEVEL = "INFO" PYTHONPATH = "/app" # Add any application-specific environment variables STATIC_DIR = "/local/app-code/static" } resources { cpu = 200 memory = 256 } service { name = "your-service-name" port = "http" tags = [ "traefik.enable=true", "traefik.http.routers.your-service.entryPoints=https", "traefik.http.routers.your-service.rule=Host(`your-service.domain.com`)" ] check { type = "http" path = "/api/health" interval = "10s" timeout = "2s" } } } } } ``` ### Option B: Using a Python Deployment Script ```python #!/usr/bin/env python import os import json from app.services.nomad_client import NomadService def main(): # Initialize the Nomad service nomad_service = NomadService() # Create job specification job_spec = { "Job": { "ID": "your-job-name", "Name": "your-job-name", "Type": "service", "Datacenters": ["dc1"], "Namespace": "development", "TaskGroups": [ { "Name": "app", "Count": 1, "Networks": [ { "DynamicPorts": [ { "Label": "http", "To": 8000 } ] } ], "Tasks": [ { "Name": "app-task", "Driver": "docker", "Config": { "image": "your-registry/your-image:tag", "ports": ["http"], "command": "python", "args": ["-m", "uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"], "mount": [ { "type": "bind", "source": "local/app-code", "target": "/app", "readonly": False } ] }, "Artifacts": [ { "GetterSource": "git::ssh://git@your-git-server:port/org/repo.git", "RelativeDest": "local/app-code", "GetterOptions": { "ref": "main", "sshkey": "your-base64-encoded-ssh-key" } } ], "Env": { "PORT": "8000", "HOST": "0.0.0.0", "LOG_LEVEL": "INFO", "PYTHONPATH": "/app", "STATIC_DIR": "/local/app-code/static" }, "Resources": { "CPU": 200, "MemoryMB": 256 }, "Services": [ { "Name": "your-service-name", "PortLabel": "http", "Tags": [ "traefik.enable=true", "traefik.http.routers.your-service.entryPoints=https", "traefik.http.routers.your-service.rule=Host(`your-service.domain.com`)" ], "Checks": [ { "Type": "http", "Path": "/api/health", "Interval": 10000000000, # 10 seconds in nanoseconds "Timeout": 2000000000 # 2 seconds in nanoseconds } ] } ] } ] } ] } } # Start the job response = nomad_service.start_job(job_spec) print(f"Job deployment response: {response}") if response.get("status") == "started": print(f"✅ Job deployed successfully!") print(f"Job ID: {response.get('job_id')}") print(f"Evaluation ID: {response.get('eval_id')}") else: print(f"❌ Failed to deploy job.") print(f"Status: {response.get('status')}") print(f"Message: {response.get('message', 'Unknown error')}") if __name__ == "__main__": main() ``` ## 2. Deploying the Nomad Job ### Option A: Using the Nomad CLI ```bash # Deploy using a .nomad file nomad job run your-job-file.nomad # Verify the job was submitted nomad job status your-job-name ``` ### Option B: Using the Python Deployment Script ```bash # Run the deployment script python deploy_your_job.py ``` ### Option C: Using the Nomad MCP API ```bash # Using curl curl -X POST http://localhost:8000/api/claude/create-job \ -H "Content-Type: application/json" \ -d '{ "job_id": "your-job-name", "name": "Your Job Name", "type": "service", "datacenters": ["dc1"], "namespace": "development", "docker_image": "your-registry/your-image:tag", "count": 1, "cpu": 200, "memory": 256, "ports": [ { "Label": "http", "Value": 0, "To": 8000 } ], "env_vars": { "PORT": "8000", "HOST": "0.0.0.0", "LOG_LEVEL": "INFO", "PYTHONPATH": "/app", "STATIC_DIR": "/local/app-code/static" } }' # Using PowerShell Invoke-RestMethod -Uri "http://localhost:8000/api/claude/create-job" -Method POST -Headers @{"Content-Type"="application/json"} -Body '{ "job_id": "your-job-name", "name": "Your Job Name", "type": "service", "datacenters": ["dc1"], "namespace": "development", "docker_image": "your-registry/your-image:tag", "count": 1, "cpu": 200, "memory": 256, "ports": [ { "Label": "http", "Value": 0, "To": 8000 } ], "env_vars": { "PORT": "8000", "HOST": "0.0.0.0", "LOG_LEVEL": "INFO", "PYTHONPATH": "/app", "STATIC_DIR": "/local/app-code/static" } }' ``` ## 3. Checking Job Status After deploying a job, you should check its status to ensure it's running correctly. ### Option A: Using the Nomad CLI ```bash # Check job status nomad job status your-job-name # Check allocations for the job nomad job allocs your-job-name # Check the most recent allocation nomad alloc status -job your-job-name ``` ### Option B: Using the Nomad MCP API ```bash # Using curl curl -X POST http://localhost:8000/api/claude/jobs \ -H "Content-Type: application/json" \ -d '{ "job_id": "your-job-name", "action": "status", "namespace": "development" }' # Using PowerShell Invoke-RestMethod -Uri "http://localhost:8000/api/claude/jobs" -Method POST -Headers @{"Content-Type"="application/json"} -Body '{ "job_id": "your-job-name", "action": "status", "namespace": "development" }' ``` ### Option C: Using a Python Script ```python #!/usr/bin/env python from app.services.nomad_client import NomadService def main(): # Initialize the Nomad service service = NomadService() # Get job information job = service.get_job('your-job-name') print(f"Job Status: {job.get('Status', 'Unknown')}") print(f"Job Type: {job.get('Type', 'Unknown')}") print(f"Job Datacenters: {job.get('Datacenters', [])}") # Get allocations allocations = service.get_allocations('your-job-name') print(f"\nFound {len(allocations)} allocations") if allocations: latest_alloc = allocations[0] print(f"Latest allocation ID: {latest_alloc.get('ID', 'Unknown')}") print(f"Allocation Status: {latest_alloc.get('ClientStatus', 'Unknown')}") if __name__ == "__main__": main() ``` ## 4. Checking Job Logs Logs are crucial for diagnosing issues with your job. Here's how to access them: ### Option A: Using the Nomad CLI ```bash # First, get the allocation ID nomad job allocs your-job-name # Then view the logs for a specific allocation nomad alloc logs # View stderr logs nomad alloc logs -stderr # Follow logs in real-time nomad alloc logs -f ``` ### Option B: Using the Nomad MCP API ```bash # Using curl curl -X GET http://localhost:8000/api/claude/job-logs/your-job-name # Using PowerShell Invoke-RestMethod -Uri "http://localhost:8000/api/claude/job-logs/your-job-name" -Method GET ``` ### Option C: Using a Python Script ```python #!/usr/bin/env python from app.services.nomad_client import NomadService def main(): # Initialize the Nomad service service = NomadService() # Get allocations for the job allocations = service.get_allocations('your-job-name') if allocations: latest_alloc = allocations[0] alloc_id = latest_alloc["ID"] print(f"Latest allocation ID: {alloc_id}") # Get logs for the allocation try: # Get stdout logs stdout_logs = service.get_allocation_logs(alloc_id, task="your-task-name", log_type="stdout") print("\nStandard Output Logs:") print(stdout_logs) # Get stderr logs stderr_logs = service.get_allocation_logs(alloc_id, task="your-task-name", log_type="stderr") print("\nStandard Error Logs:") print(stderr_logs) except Exception as e: print(f"Error getting logs: {str(e)}") else: print("No allocations found for your-job-name job") if __name__ == "__main__": main() ``` ## 5. Troubleshooting Common Issues ### Issue: Job Fails to Start 1. **Check the job status**: ```bash nomad job status your-job-name ``` 2. **Examine the allocation status**: ```bash nomad alloc status -job your-job-name ``` 3. **Check the logs for errors**: ```bash # Get the allocation ID first nomad job allocs your-job-name # Then check the logs nomad alloc logs -stderr ``` 4. **Common errors and solutions**: a. **Missing static directory**: ``` RuntimeError: Directory 'static' does not exist ``` Solution: Add an environment variable to specify the static directory path: ```hcl env { STATIC_DIR = "/local/app-code/static" } ``` b. **Invalid mount configuration**: ``` invalid mount config for type 'bind': bind source path does not exist ``` Solution: Ensure the source path exists or is created by an artifact: ```hcl artifact { source = "git::ssh://git@your-git-server:port/org/repo.git" destination = "local/app-code" } ``` c. **Port already allocated**: ``` Allocation failed: Failed to place allocation: failed to place alloc: port is already allocated ``` Solution: Use dynamic ports or choose a different port: ```hcl network { port "http" { to = 8000 } } ``` ### Issue: Application Errors After Deployment 1. **Check application logs**: ```bash nomad alloc logs ``` 2. **Verify environment variables**: ```bash nomad alloc status ``` Look for the "Environment Variables" section. 3. **Check resource constraints**: Ensure the job has enough CPU and memory allocated: ```hcl resources { cpu = 200 # Increase if needed memory = 256 # Increase if needed } ``` ## 6. Updating a Job After fixing issues, you'll need to update the job: ### Option A: Using the Nomad CLI ```bash # Update the job with the modified specification nomad job run your-updated-job-file.nomad ``` ### Option B: Using the Nomad MCP API ```bash # Using PowerShell to restart a job Invoke-RestMethod -Uri "http://localhost:8000/api/claude/jobs" -Method POST -Headers @{"Content-Type"="application/json"} -Body '{ "job_id": "your-job-name", "action": "restart", "namespace": "development" }' ``` ### Option C: Using a Python Script ```python #!/usr/bin/env python from app.services.nomad_client import NomadService def main(): # Initialize the Nomad service service = NomadService() # Get the current job specification job = service.get_job('your-job-name') # Modify the job specification as needed # For example, update environment variables: job["TaskGroups"][0]["Tasks"][0]["Env"]["STATIC_DIR"] = "/local/app-code/static" # Update the job response = service.start_job({"Job": job}) print(f"Job update response: {response}") if __name__ == "__main__": main() ``` ## 7. Stopping a Job When you're done with a job, you can stop it: ### Option A: Using the Nomad CLI ```bash # Stop a job nomad job stop your-job-name # Stop and purge a job nomad job stop -purge your-job-name ``` ### Option B: Using the Nomad MCP API ```bash # Using PowerShell Invoke-RestMethod -Uri "http://localhost:8000/api/claude/jobs" -Method POST -Headers @{"Content-Type"="application/json"} -Body '{ "job_id": "your-job-name", "action": "stop", "namespace": "development", "purge": true }' ``` ### Option C: Using a Python Script ```python #!/usr/bin/env python from app.services.nomad_client import NomadService def main(): # Initialize the Nomad service service = NomadService() # Stop the job response = service.stop_job('your-job-name', purge=True) print(f"Job stop response: {response}") if __name__ == "__main__": main() ``` ## 8. Complete Workflow Example Here's a complete workflow for deploying, monitoring, troubleshooting, and updating a job: ```python #!/usr/bin/env python import time from app.services.nomad_client import NomadService def main(): # Initialize the Nomad service service = NomadService() # 1. Create and deploy the job job_spec = { "Job": { "ID": "example-app", "Name": "Example Application", "Type": "service", "Datacenters": ["dc1"], "Namespace": "development", # ... rest of job specification ... } } deploy_response = service.start_job(job_spec) print(f"Deployment response: {deploy_response}") # 2. Wait for the job to be scheduled print("Waiting for job to be scheduled...") time.sleep(5) # 3. Check job status job = service.get_job('example-app') print(f"Job Status: {job.get('Status', 'Unknown')}") # 4. Get allocations allocations = service.get_allocations('example-app') if allocations: latest_alloc = allocations[0] alloc_id = latest_alloc["ID"] print(f"Latest allocation ID: {alloc_id}") print(f"Allocation Status: {latest_alloc.get('ClientStatus', 'Unknown')}") # 5. Check logs for errors stderr_logs = service.get_allocation_logs(alloc_id, log_type="stderr") # 6. Look for common errors if "Directory 'static' does not exist" in stderr_logs: print("Error detected: Missing static directory") # 7. Update the job to fix the issue job["TaskGroups"][0]["Tasks"][0]["Env"]["STATIC_DIR"] = "/local/app-code/static" update_response = service.start_job({"Job": job}) print(f"Job update response: {update_response}") # 8. Wait for the updated job to be scheduled print("Waiting for updated job to be scheduled...") time.sleep(5) # 9. Check the updated job status updated_job = service.get_job('example-app') print(f"Updated Job Status: {updated_job.get('Status', 'Unknown')}") else: print("No allocations found for the job") if __name__ == "__main__": main() ``` ## 9. Best Practices 1. **Always check logs after deployment**: Logs are your primary tool for diagnosing issues. 2. **Use environment variables for configuration**: This makes your jobs more flexible and easier to update. 3. **Implement health checks**: Health checks help Nomad determine if your application is running correctly. 4. **Set appropriate resource limits**: Allocate enough CPU and memory for your application to run efficiently. 5. **Use artifacts for code deployment**: Pull code from a Git repository to ensure consistency. 6. **Implement proper error handling**: Your application should handle errors gracefully and provide meaningful error messages. 7. **Use namespaces**: Organize your jobs into namespaces based on environment or team. 8. **Document your job specifications**: Include comments in your job files to explain configuration choices. 9. **Implement a CI/CD pipeline**: Automate the deployment process to reduce errors and improve efficiency. 10. **Monitor job performance**: Use Nomad's monitoring capabilities to track resource usage and performance. ## 10. Conclusion Managing Nomad jobs effectively requires understanding the job lifecycle, from creation to deployment, monitoring, troubleshooting, and updating. By following this guide, you can create robust deployment processes that ensure your applications run reliably in a Nomad cluster. Remember that the key to successful job management is thorough testing, careful monitoring, and quick response to issues. With the right tools and processes in place, you can efficiently manage even complex applications in a Nomad environment.