Head and management nodes

Roles of Head and Management Nodes

In an HPC cluster, head and management nodes form the “control plane” of the system. They generally do not run user computations; instead, they coordinate and supervise everything that happens on the compute nodes.

While exact designs differ between sites, the roles are usually split into:

• Head (login/front-end) nodes
• Entry point for users
• Interactive work and compilation
• Job submission and light data management
• Management nodes
• Cluster-wide control and monitoring
• Scheduling and resource management
• Provisioning and configuration
• Central services (e.g., authentication, databases)

On small systems, these roles might be combined into one or two machines; on large systems, they can be many separate nodes, each with a focused task.

Typical Services on Head Nodes

Head (often called login or front-end) nodes expose the cluster to users while shielding the internal network and compute nodes.

Common services and uses:

• User access
• SSH entry point: ssh username@cluster.example.org
• Sometimes multiple login nodes: login1, login2, etc., behind a load balancer or round-robin DNS.
• Interactive shell and editing
• Running shells, text editors, and simple tools
• Viewing and managing files: ls, cp, mv, rm, tar, etc.
• Compiling and building software
• Using compilers and build systems
• Linking against libraries installed on the cluster
• Preparing executables that will later run on compute nodes
• Job submission interface
• Running scheduler client commands (e.g., sbatch, squeue, etc.)
• Preparing job scripts and launching batch jobs
• Light pre- and post-processing
• Small-scale data checks, visualization for small output, creating plots
• Generating input decks or configurations
• User environment management
• Loading environment modules
• Setting environment variables
• Managing SSH keys, shell profiles (e.g., .bashrc)

Head nodes are shared resources. Sites typically enforce usage policies to avoid overloading them, because poor behavior here impacts all users.

Typical Services on Management Nodes

Management nodes support the infrastructure of the cluster itself. Users usually do not log onto them directly.

Common roles include:

• Scheduler / resource manager host
• Runs the central scheduler daemon (e.g., slurmctld for SLURM) and associated services
• Maintains the global view of node status, queues, and running jobs
• Database and accounting
• Job accounting databases (e.g., SLURM accounting DB)
• Tracking who used how many resources and when
• Supporting fair-share and quota enforcement
• Configuration and provisioning
• Central configuration management (e.g., Ansible, Puppet, Chef)
• Node provisioning systems (e.g., PXE boot infrastructure)
• Managing OS images and configuration templates
• Monitoring and logging
• Cluster health monitoring tools (e.g., Grafana, Prometheus, Nagios, Ganglia)
• Collecting logs from all nodes (syslog, audit logs, scheduler logs)
• Alerting admins when something fails or degrades
• Authentication and directory services
• Directory services (e.g., LDAP, Active Directory)
• Central authentication, user/group management
• Sometimes home directory or user profile services via networked filesystems
• License servers and other central services
• Floating license managers for commercial software
• Web interfaces to cluster portals or science gateways
• Internal API endpoints for automation or meta-scheduling

In production systems, these services are usually split across multiple management nodes for reliability and scalability.

Separation from Compute Nodes

Head/management nodes are architecturally distinct from compute nodes:

• Workload types
• Head/management nodes run mostly control and I/O oriented tasks.
• Compute nodes run user applications and heavy numerical computations.
• Resource usage expectations
• Head nodes: many concurrent interactive sessions, moderate CPU/IO use per user.
• Management nodes: steady background load, peaks when scheduling large batches or collecting many metrics.
• Compute nodes: high, sustained CPU/GPU utilization, minimal interactive use.
• Security and access control
• Compute nodes often not directly reachable from outside the cluster.
• Head nodes are hardened entry points; management nodes are often restricted further (admin-only).
• Stability requirements
• Management nodes must remain up for the cluster to function at all.
• Jobs can survive individual compute node failures (to some extent), but losing a critical management node can stop scheduling cluster-wide.

This separation allows the cluster to scale: adding more compute nodes does not significantly increase the load on head nodes if services are designed correctly.

Resource Policies and Usage Guidelines

From a user’s perspective, the most important aspect of head nodes is how to use them responsibly:

What *is* appropriate on head nodes

• Editing code and job scripts
• Running make or cmake to build your programs (within reasonable limits)
• Using simple analysis scripts that do not use a lot of CPU or memory
• Copying data to and from the cluster (e.g., scp, rsync)
• Checking job status, logs, and small output files
• Testing short commands or very small test cases (often under a few minutes)

What is usually *not* allowed

• Long-running CPU-heavy computations
• Large parallel runs or threading on head nodes
• High-memory or I/O-intensive tasks that could affect everyone
• Background “daemon-like” scripts that run indefinitely

Clusters typically enforce these policies via:

• System limits (e.g., maximum CPU time, memory per process)
• Process monitors that kill long-running jobs on login nodes
• Load monitoring and user notifications
• Explicit usage rules in site documentation

Always consult your site’s policies: some clusters provide separate interactive or “development” nodes specifically for heavier interactive work; others require that all serious computation go through the scheduler.

Architectural Patterns for Head and Management Nodes

Different sites adopt different architectures based on their scale and needs. Some common patterns:

Single combined head/management node

• Used in very small clusters or teaching systems.
• One machine hosts:
• Login access
• Scheduler daemon
• Monitoring and configuration tools
• NFS or other shared filesystem exports
• Simplifies management but creates a single point of failure and a potential bottleneck.

Multiple head (login) nodes, shared management backend

• Typical for medium to large systems.
• Several login nodes behind a common DNS name (e.g., login.cluster.org).
• One or more management nodes host:
• Scheduler controller and database
• Monitoring and configuration
• Advantages:
• User sessions spread across login nodes
• Maintenance windows can be staggered
• Higher aggregate throughput for compilations and data transfers

Dedicated role-based management nodes

• Common in large facilities and national centers.
• Different management nodes for:
• Scheduling and accounting
• Provisioning and configuration
• Monitoring and logging
• File-serving (separate from pure computation)
• Highly redundant design: active/passive or active/active failover, database replication, redundant power and networking.

Users usually do not need to know all these details, but understanding that there is a control plane behind the login nodes helps when interpreting outages or performance issues.

Security and Access Control Considerations

Head and management nodes sit at critical points in the cluster’s security model.

Typical measures:

• Network isolation
• Head nodes are on both external (or DMZ) and internal cluster networks.
• Management nodes are generally reachable only from within the cluster or by admins.
• Strict authentication
• SSH with public-key authentication, sometimes combined with multi-factor methods.
• Role-based access: regular users vs. admins.
• Limited privilege on head nodes
• Users don’t get root access.
• Certain operations may be restricted (e.g., running container engines, listening on specific ports).
• Audit and compliance
• Logging of SSH logins, job submissions, and configuration changes.
• Integration with central institutional security policies.

From a user perspective, the important part is to treat head nodes as shared and monitored resources, and to follow the site’s security recommendations (e.g., key management, not storing plaintext passwords in scripts).

Interaction with Schedulers and Other Services

Management nodes host the central scheduler components, but users interact with those services primarily from head nodes.

Typical flow:

1. User logs in to a head node via SSH.
2. User prepares job scripts and sets up the environment (modules, paths).
3. User submits jobs using scheduler commands (e.g., sbatch job.sh).
4. The head node’s scheduler client talks to the scheduler daemon on a management node.
5. The scheduler allocates resources on compute nodes and starts the job.
6. Logs and output are written to shared filesystems accessible from head nodes.
7. The user periodically uses the head node to monitor or manage jobs (e.g., squeue, scancel).

Other interactions include:

• File services
• Head nodes often mount the same shared filesystems as compute nodes, making it easy to stage input/output data.
• Monitoring interfaces
• Web dashboards may be hosted on management nodes, but are accessed from your browser, not from the command line.
• CLI tools for checking node status may be run from head nodes, querying management services.

Understanding that head nodes are mostly a client interface to central services clarifies why, for example, submitting thousands of tiny jobs or constantly polling the scheduler from scripts can overload management systems.

Practical Tips for Users

To use head and management node infrastructure effectively:

• Choose when and where to run tasks
• Do: light editing, compiling, and job submission on head nodes.
• Don’t: run your production simulation directly on a head node.
• Balance usage across login nodes
• If your site has multiple login nodes (e.g., login1, login2), spread heavy compilations or transfers across them when appropriate.
• Be gentle with automated scripts
• Avoid tight polling loops querying the scheduler every second.
• Add reasonable delays (sleep 30 or longer) when monitoring many jobs.
• Know where services live
• Use the documented login hostname(s) for interactive work.
• Use web portals or designated hosts for monitoring dashboards.
• Don’t assume you can or should access management nodes directly.
• Watch for maintenance windows
• Scheduler or management node maintenance can temporarily affect job submission, monitoring, or accounting.
• Already-running jobs on compute nodes may continue even if some management services are briefly offline, depending on the cluster design.

Having a clear mental model of head and management nodes—as the cluster’s “front door” and “brain”—will help you work with the system safely, efficiently, and in a way that scales to many users.