OneLab - Future Internet Testbeds

nepi-ng - troubleshooting


In this page we are going to see a few guidelines for troubleshooting a nepi-ng script.

This tuto is organized in several parts

  • Common mistakes : works as a simple checklist that should let you figure out the most common mistakes.

  • Code updates : check to see if you're running the latest versions of the code

  • Verbosity : how to enable more logging messages from your script

  • Hanging : how to deal with a scheduler that never completes and you do not understand why

Check for the obvious

Before you start diving in the code, it is always a good idea to step back a little, and to check for the following common mistakes.

This is especially true when you start with nepi-ng and R2lab, and your scripts are not sophisiticated enough to do all these checks by themselves.

The following common sources of glitches happen frequently in situations where you were working on your scenario, and then your time went up. So you just come back to the testbed, you should check for the following:

Do you have a valid reservation on the testbed ?

If your script does not check for that, it's a good idea to double check on e.g.

Can you reach faraday via ssh ?

Try to enter the gateway with this simple command


If this does not work, then double check that your private ssh key is known to your ssh agent - especially if you have recently logged out :

ssh-add -l

Are the nodes up ? Do they run the expected image ?

You can check all your nodes directly in the RUN page on the web site, or with a session like this (when logged in faraday), assuming that you need nodes 4, 6 and from 10 to 13 inclusive :

$ rleases --check
Checking current reservation for inria_r2lab.tutorial OK

# select your nodes
inria_r2lab.tutorial@faraday:~$ n 4 6 10-13
export NODES="fit04 fit06 fit10 fit11 fit12 fit13"
export NBNODES=6

# check they are reachable through ssh - use the --timeout option if needed
inria_r2lab.tutorial@faraday:~$ rwait
<Node fit04>:ssh OK
<Node fit06>:ssh OK
<Node fit10>:ssh OK
<Node fit11>:ssh OK
<Node fit12>:ssh OK
<Node fit13>:ssh OK

# what image are they all running ?
inria_r2lab.tutorial@faraday:~$ map rimage
fit04:2016-11-29@00:12 - built-on fit03 - from-image fedora-23-v10-wireless-names - by inria_r2lab.tutorial
fit10:2016-11-29@00:12 - built-on fit03 - from-image fedora-23-v10-wireless-names - by inria_r2lab.tutorial
fit06:2016-11-29@00:12 - built-on fit03 - from-image fedora-23-v10-wireless-names - by inria_r2lab.tutorial
fit13:2016-11-29@00:12 - built-on fit03 - from-image fedora-23-v10-wireless-names - by inria_r2lab.tutorial
fit11:2016-11-29@00:12 - built-on fit03 - from-image fedora-23-v10-wireless-names - by inria_r2lab.tutorial
fit12:2016-11-29@00:12 - built-on fit03 - from-image fedora-23-v10-wireless-names - by inria_r2lab.tutorial

Otherwise, check out the next section on code updates..

The software involved in R2lab, either nepi-ng or the shell utilities, are evolving quickly, especially during the current rollout period.

So here's how you can check for possibly out-dated versions of either of these :


Please double check that you

  • indeed run python-3.6 or higher
  • and that you indeed use python3 to run your script - it is so easy to forget the 3 in python3 !


You can make sure that you run the latest version of nepi-ng by running

[sudo] pip3 install --upgrade apssh

Alternatively, you can check the currently running versions by doing on your laptop

$ python3 -c 'from asynciojobs import version; print(version.__version__)'
$ python3 -c 'from apssh import version; print(version.__version__)'

and then compare them against the latest release numbers for these 2 libraries, that can be found :

  • either by searching,
  • or in the respective documentation pages for asynciojobs and apssh.

r2lab python library

Similarly, you may have to upgrade the python library

[sudo] pip3 install -U r2lab

shell tools

The shell tools are used

  • on faraday itself, but you can consider this is always up-to-date,
  • as well as on the nodes themselves; and in this case, the version of the R2lab convenience tools - like turn-on-data or other r2lab-id or similar tools - that you use depends on the date where your image was created.

This is why it is always a good idea to have your shell scripts, whenever they source /root/r2lab-embedded/shell/, call git-pull-r2lab which will update the whole repository /root/r2lab-embedded from the latest version published on github.

Otherwise, check out the next section on verbosity in your scripts..

OK, so you have tried everything else, you can't seem to find why your script does not behave like you expected it to. Here's a brief description of the various levels of verbosity that you can enable in your script.


In all our examples so far, you have noticed that we always run a scheduler like this :

# run the scheduler
ok =
# give details if it failed
ok or scheduler.debrief()

This means that, if ever run() does not return True, we run the debrief() method on that scheduler.

Keep in mind that run orchestration returns False only in either of these 2 cases:

  • one of the critical jobs inside the scheduler has raised an exception,
  • or, when dealing with a scheduler that has an attached timeout
    • e.g. created as Scheduler(timeout=120) - if the total duration of run exceeds that timeout.

So if run() returns False, and you have not specified a global timeout, it means you are in the first situation; and by calling debrief() like we have done in all the tutorials, you will see more details on the critical job that has caused the scheduler to bail out.

Structure of the scheduler

The programming style used to create a Scheduler instance and to add jobs in it can sometimes lead to unexpected results. Typical mistakes generally involve

  • erroneous required relationsships,
  • and jobs with wrong criticality.

You have several means to check it for mistakes

Checking contents

The Scheduler.list() method allows you to see an overview of your Scheduler object, in terms of the jobs it contains, and their required relationship. You can use it anytime, before or after you orchestrate the scheduler, but if your script behaves oddly it might be a good idea to check the scheduler before running it

 # just before you trigger run()

You can even ask for more details


Scheduler.list() uses some symbols in the hope to provide meaningful information in a condensed way, you can refer to this page to see the meaning of the different symbols, but in a nutshell:

  • : critical
  • : raised an exception
  • : went through fine (no exception raised)
  • : complete
  • : running
  • : idle
  • : forever

Graphical view

As we have already seen in C3bis, it is rather easy to produce a png file that depicts the jobs in a scheduler, together with their relationships.

import os
os.system("dot -Tpng -o foo.png")

You will need to install graphviz so that you can use the dot program in this fragment.


You can also enable more verbosity in any of the following classes.


Setting verbose=True on an instance of SshNode results in messages being printed about ssh connections and sessions being open and closed. The scripts in the tutorial implement a -v option that does just that, it is really useful especially for beginners.

If you do not set this, failures to create ssh connections go unnoticed.

Implementation note: this flag is in actuality passed to the underlying formatter object.


Setting verbose=True on a SshJob instance results in all its commands being run in verbose mode.

Run and other commands

  • Run : in verbose mode, shows the command that is run, and its return code once it's done
  • RunScript and RunScript : in verbose mode, remote script is run using bash -x; expect a lot of output here
  • Push and Pull : print actual arguments to the SFTP get and put


Finally you can set verbose=True on a Scheduler object, which will give you details of the jobs being started, and their are done.

Sometimes a scheduler may exhibit the symptom of not completing as you expect it to, and it may be a little hard to understand which job is causing the issue.

There are several tricks that can come in handy in this sort of situations:

Making the scheduler verbose

If you create your Scheduler instance with the verbose attribute set to True (this can be safely done manually late on), then while running it will issue debug-level statements like these:

12:32:55.397 3D + 2R + 1I = 6 DONE    : 5 ⚠ ☉ ☓   <SshJob ...
12:32:55.398 3D + 2R + 1I = 6 STARTING: 6 ⚠   ⚐   <SshJob ...

That should be interpreted as follows:

  • at that time (12:32:55) the running scheduler has
    • 3 done jobs
    • 2 running jobs
    • 1 idle job
    • which amounts to a total of 6 jobs
  • at that moment, job #5 has just completed,
  • and as a result, a millisecond later, job #6 has been started

Interrupting the Scheduler

Another simple trick is to replace a simple call to scheduler.Run() by the following idiom:

    success =
except KeyboardInterrupt:
    print("OOPS ! ")

This way when the execution hangs, you can interrupt it by typing Ctrl-C, which will dump the status of the various jobs, like e.g.:

^COOPS - current status
----- FINE
1 ⚠ ☉ ☓   <SshJob `rhubarbe leases --check`> OK
2 ⚠ ☉ ↺   <SshJob `RunScript: run-cefore-sim`> OK requires={1}
3 ⚠ ☉ ☓   <SshJob `RunScript: run-cefore-publisher`> OK requires={1}
4 ⚠ ☉ ☓   <PrintJob `settling for 15 seconds`> [[ -> None]] requires={1}
5 ⚠ ☉ ☓   <SshJob `cd NS3/sourc ...`> OK requires={4}
6 ⚠ ☉ ☓   <SshJob `Pull: remote path /root/NS3/source/ns-3-dce/files-2/tmp/OutFile into .`> OK requires={5}

where you can see that job #2 is still running.

Using the Service class

Very often, when an SshJob does not complete as you expect it to, it is because it starts background processes that do not properly daemonize.

When the remote process still has an open std channel (in, out or err) open, the session will cowardly refuse to hang up in the fear to lose such information.

In order to ease the management of such service-oriented activities, the apssh library comes with a Service class, that leverages the now general availability of systemd on all the major linux distributions, as an attempt to provide easier and more robust path.

Please see the Service class documentation for more details.