Monitor your jobs
Introduction
This guide outlines how to monitor your jobs. Use this guide to check on your jobs’ statuses, check on their standard output/error messages, or connect to a running job.
Table of Contents
Watch your jobs with condor_watch_q
For a real-time view of your jobs’ status, run the condor_watch_q tool. For example:
[netid@ap2002 ~]$ condor_watch_q
BATCH IDLE INPUT RUN DONE TOTAL JOB_IDS
4839429 - - 1 - 1 4839429.0 [====================]
4839838 1 6 - 3 10 4839838.1 ... 4839838.9 [-->>>>>>>>>>>>######]
Total Progress: [----->>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>=====###################]
Total: 11 jobs; 3 completed, 1 idle, 7 running
Updated at 2026-04-06 16:13:39
Press any key to exit
condor_watch_q updates every second with color-coded output on your terminal by reading your HTCondor log file (specified by the log attribute in your submit file).
Check your jobs’ status with condor_q
To check the status of your jobs, use the command condor_q on the Access Point. For example:
[netid@ap2002]$ condor_q
-- Schedd: ap2002.chtc.wisc.edu : <128.104.101.92:9618?... @ 04/14/23 15:35:17
OWNER BATCH_NAME SUBMITTED DONE RUN IDLE TOTAL JOB_IDS
netid ID: 3606214 4/14 12:31 2 1 _ 3 36062145.0-2
3 jobs; 2 completed, 0 removed, 0 idle, 1 running, 0 held, 0 suspended
condor_q options
Additional options are available for the condor_q command. See the table below.
| Command | Use | Notes |
|---|---|---|
condor_q |
displays status of your submitted jobs; jobs are batched by default | |
condor_q -nobatch |
displays status of your submitted jobs without the batched view | |
condor_q <job_ID> |
displays status of the job(s) associated with job_ID |
|
condor_q -l <job_ID> |
lists all attributes of the job(s) associated with job_ID |
This will generate a lot of output; don’t use for more than one job at a time! |
condor_q -hold <job_ID> |
displays the hold reason for job(s) associated with job_ID |
|
condor_q -better-analyze <job_ID> |
displays simulated results of the matching process associated with the job | This is a starting point for troubleshooting jobs sitting in the idle state. |
condor_q -run |
displays your running jobs | |
condor_q -dag |
organizes the condor_q output by DAGs |
|
condor_q -af <attribute1> <attribute2> |
displays specific attributes of jobs. | See the attributes from condor_q -l or HTCondor job attributes. |
⛔ Do not run
watch condor_q
Do not run
watch condor_qor any equivalent command that queriescondor_qin high frequency. This will overwhelm the scheduler and reduce operational efficiency for all users.Use
condor_watch_qinstead, or contact us for help on addressing your specific needs.
Check the your jobs’ progress with condor_tail
To check on the progress of currently running jobs, you can use condor_tail <job_ID> to read the last few lines of a file in your job’s scratch directory. For example:
[netid@ap2002 ~]$ condor_tail 4839838.6
inflating: data/8724.jpg
inflating: data/8725.jpg
inflating: data/8726.jpg
inflating: data/8727.jpg
inflating: data/8728.jpg
By default, condor_tail prints the standard output.
| Command | Use |
|---|---|
condor_tail <job_ID> |
print the last few lines of the standard output |
condor_tail -stderr <job_ID> |
print the last few lines of the standard error |
condor_tail <job_ID> <filename> |
print the last few lines of <filename> in the job’s scratch directory |
Connect to your job with condor_ssh_to_job
You can connect to a currently running job by using condor_ssh_to_job. When you’re done with the session, type exit to return to the Access Point.
[netid@ap2002 ~]$ condor_ssh_to_job 4839849.0
Welcome to slot1_135@e4031.chtc.wisc.edu!
Your condor job is running with pid(s) 3406940.
== NOTICE: THIS NODE IS ON PUPPET ENVIRONMENT "puppet8" ==
[netid@e4031 scratch]$ exit
logout
Connection to condor-job.e4031.chtc.wisc.edu closed.
⚠️ Policy for
condor_ssh_to_job
This tool is intended for quick checks and troubleshooting. This is NOT intended for interactive job submission. For interactive jobs, use the
-iflag, i.e.,
condor_submit -i <submit_file>.
condor_ssh_to_jobis NOT available for GPU jobs on CHTC’s shared GPU machines. See our interactive GPU jobs guide for more details.