Understanding the 'sdiag' Command in SLURM (with examples)

The sdiag command is an essential tool for administrators and users of SLURM (Simple Linux Utility for Resource Management), a highly scalable cluster management and job scheduling system for large and small Linux clusters. With sdiag, you can delve into various performance metrics and status reports associated with the execution of slurmctld, SLURM’s central management daemon. This command helps users monitor, diagnose, and optimize the performance and health of the SLURM controller process.

Use case 1: Show all performance counters related to the execution of slurmctld

Code:

sdiag --all

Motivation for the Example:

Fetching all performance counters is crucial for gaining insight into the overall performance and efficiency of the SLURM controller. By using this command, cluster administrators can evaluate how well slurmctld is performing and make informed decisions to improve cluster management and job scheduling.

Explanation:

• sdiag: This is the command that provides diagnostic information about slurmctld.
• --all: This option tells sdiag to display all available performance counters, offering a comprehensive view of various metrics collected over time, such as job scheduling rates, event processing statistics, and daemon up-time, among others.

Example Output:

Diagnostics information as of 2023-10-01
Jobs scheduled: 15000
Jobs started: 14500
Events processed (by type): 
    3500 JobSubmit
    3250 JobComplete
    8500 NodeTransition
Daemon uptime: 99.8%

Use case 2: Reset performance counters related to the execution of slurmctld

Code:

sdiag --reset

Motivation for the Example:

Resetting performance counters is essential for establishing a new baseline to evaluate performance trends accurately over a specific period. This can be particularly useful after maintenance events, software upgrades, or when testing new scheduling configurations.

Explanation:

• sdiag: Used to access SLURM’s diagnostic tools.
• --reset: This argument resets all gathered performance counters to zero, effectively clearing historical data and starting over the collection of metrics.

Example Output:

All performance counters have been reset.

Use case 3: Specify the output format

Code:

sdiag --all --json

Motivation for the Example:

Specifying the output format allows you to integrate SLURM diagnostics with other tools or software systems more seamlessly. For example, a JSON format is especially useful for automated analysis and for visualization using various graphing tools.

Explanation:

• sdiag: Accesses the diagnostics for SLURM.
• --all: Displays all diagnostic performance counters.
• --json: Outputs the information in JSON format, which is ideal for parsing and manipulating in scripts, or integrating within applications and data pipelines.

Example Output:

{
    "jobs_scheduled": 15000,
    "jobs_started": 14500,
    "events_processed": {
        "JobSubmit": 3500,
        "JobComplete": 3250,
        "NodeTransition": 8500
    },
    "daemon_uptime": 99.8
}

Use case 4: Specify the cluster to send commands to

Code:

sdiag --all --cluster=cluster_name

Motivation for the Example:

In environments where multiple SLURM clusters are managed concurrently, specifying the cluster is vital for retrieving the correct performance data. This helps ensure diagnostics are accurate and relevant to the specific cluster of interest.

Explanation:

• sdiag: To perform diagnostics on slurmctld.
• --all: Command to retrieve comprehensive diagnostic information.
• --cluster=cluster_name: This option specifies the target cluster for the diagnostics command. Replace cluster_name with the actual name of the cluster to direct the diagnostic query to the appropriate system.

Example Output:

Showing diagnostics for cluster 'cluster_name'
Jobs scheduled: 8000
Jobs started: 7800
Daemon uptime: 98.5%

Conclusion:

Utilizing the sdiag command efficiently can significantly enhance your ability to manage SLURM clusters. Whether you are resetting counters, choosing output formats, or directing diagnostics to specific clusters, these use cases provide versatile, real-world applications of sdiag in performance monitoring and management within SLURM environments. By mastering these commands and their options, administrators can ensure their clusters operate at peak efficiency and troubleshoot issues more effectively.