RAM or CPU show nothing
sundh4 opened this issue · 8 comments
Hello,
I've been trying this extensions but it seems nothing happened. I use Kubernetes for deployment. Here my versions:
jupyter-client 5.3.4
jupyter-console 6.1.0
jupyter-core 4.6.3
jupyter-rsession-proxy 1.1
jupyter-server-proxy 1.3.2
jupyterhub 1.0.0
jupyterlab 1.2.13
jupyterlab-server 1.1.1
nbresuse 0.3.4
notebook 6.0.2
prometheus-client 0.7.1
psutil 5.7.0
Some of error logs shown:
[E 2020-04-30 06:15:22.373 SingleUserLabApp ioloop:763] Exception in callback functools.partial(<bound method IOLoop._discard_future_result of <tornado.platform.asyncio.AsyncIOMainLoop object at 0x7f896ed2f668>>, <Future finished exception=AttributeError("can't set attribute",)>)
Traceback (most recent call last):
File "/opt/conda/lib/python3.6/site-packages/tornado/ioloop.py", line 743, in _run_callback
ret = callback()
File "/opt/conda/lib/python3.6/site-packages/tornado/ioloop.py", line 767, in _discard_future_result
future.result()
File "/opt/conda/lib/python3.6/site-packages/tornado/gen.py", line 191, in wrapper
result = func(*args, **kwargs)
File "/opt/conda/lib/python3.6/site-packages/nbresuse/prometheus.py", line 34, in __call__
metrics = self.apply_memory_limits(memory_metrics())
File "/opt/conda/lib/python3.6/site-packages/nbresuse/prometheus.py", line 49, in apply_memory_limits
metrics.max_memory = self.config.mem_limit
AttributeError: can't set attribute
Here the configurations that i use to spawn the notebook:
c.KubeSpawner.args = ['--disable-user-config', '--no-browser', '--allow-root',
'--config=/etc/jupyter/jupyter_notebook_config.py',
'--ResourceUseDisplay.track_cpu_percent=True']
Appreciate for helping. Thank you.
Thanks @sundh4 for opening the issue.
Would it be possible to try with nbresuse==0.3.3
?
I've tried nbresuse 0.3.3 its only work fine for RAM usage
The issue with 0.3.4
is tracked in jupyter-server/jupyter-resource-usage#36.
Which version of jupyterlab-system-monitor
are you using? The latest with the CPU indicator is 0.6.0
.
I've tried nbresuse 0.3.3 its only work fine for RAM usage
The issue with
0.3.4
is tracked in yuvipanda/nbresuse#36.Which version of
jupyterlab-system-monitor
are you using? The latest with the CPU indicator is0.6.0
.
Hi @jtpio
Here my extensions version:
JupyterLab v1.2.13
Known labextensions:
app dir: /opt/conda/share/jupyter/lab
@jupyter-widgets/jupyterlab-manager v1.1.0 enabled OK
@jupyterlab/server-proxy v2.0.1 enabled OK
@lckr/jupyterlab_variableinspector v0.4.0 enabled OK
jupyterlab-plotly v4.6.0 enabled OK
jupyterlab-system-monitor v0.4.1 enabled OK
jupyterlab-topbar-extension v0.4.0 enabled OK
plotlywidget v4.6.0 enabled OK
I tried upgrade jupyterlab-system-monitor to v0.6.0 but i got error msg version not compatible like below:
"jupyterlab-system-monitor@0.6.0" is not compatible with the current JupyterLab
Conflicting Dependencies:
JupyterLab Extension Package
>=1.2.6 <1.3.0 >=2.0.0 <3.0.0 @jupyterlab/application
So, this mean the extensions only work for Jupyterlab version 2.x.x right?
So, this mean the extensions only work for Jupyterlab version 2.x.x right?
Yes, version 0.5.0 and above only support JupyterLab 2.0.
The CPU indicator was added after the update to 2.0 and will not be backported to 1.x. Most of the extensions in the list above should now be compatible with the latest JupyterLab. Is it possible to upgrade to JupyterLab 2.x on your setup?
So, this mean the extensions only work for Jupyterlab version 2.x.x right?
Yes, version 0.5.0 and above only support JupyterLab 2.0.
The CPU indicator was added after the update to 2.0 and will not be backported to 1.x. Most of the extensions in the list above should now be compatible with the latest JupyterLab. Is it possible to upgrade to JupyterLab 2.x on your setup?
Thanks @jtpio
I see, will try upgrade my setup with version 2.xx. I will update the result here.
Hi @jtpio
You are right, after upgrading Jupyterlab with version 2.1.1 and use nbresuse==0.3.3 now RAM and CPU usage are shown.
Thanks
Nice, thanks @sundh4!
Closing as answered. Feel free to comment here or on jupyter-server/jupyter-resource-usage#36 if you have more questions.