But without navigation bar, it's quiet inconvenient 😢 ...Do you known why? SuccessfulKoala55

I know why, because i used the old apiserver.conf, i set fixed_users. After log in http://xxx:8080/login , it's ok now

Do you mean i send the old one to you?

Sorry , my poor english, it means upgrade by script.
Good news is it's fine now, I try to upgrade ES (although it fails), and i try to go through the necessary steps in this: https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_linux_mac

SuccessfulKoala55 It seems ok

SuccessfulKoala55
Even if with Logger.report_scatter2d() the result is still so large ,and i found where the digits change: https://github.com/allegroai/trains/blob/master/trains/utilities/plotly_reporter.py#L122
Tolist will change the digits , but i haven't figure out why.

SuccessfulKoala55
I have manually control the number of data under 800K, because i found the budget would be 0 if len(series_sizes) = 1, https://github.com/allegroai/trains/blob/master/trains/utilities/plotly_reporter.py#L101

AgitatedDove14 OK, i see, thanks so much!

SuccessfulKoala55 Thanks, If restarting server wont stop running experiments, then what i say is not necessary !

GrumpyPenguin23
It seems the solution 3 is the fastest way, and i can reuse my code easily. It works now~ That's quite interesting, but the learning curve seems a bit steep for me.Do you have any material or suggestion for learning that?

https://stackoverflow.com/questions/28287261/connection-timeout-with-elasticsearch
How to set the timeout?

I found plotly dash cannot be exported to html file, so it may cannot be used here

Maybe plotly dash can help, is there is any other solution?

GrumpyPenguin23 Ok, i will open a request now!

AppetizingMouse58 Ok, this is the full log, here seems a error:

My docker-compose is lateset, download by this:
curl https://raw.githubusercontent.com/allegroai/clearml-server/master/docker/docker-compose.yml -o /opt/clearml/docker-compose.yml

SuccessfulKoala55 And i try to create ~/trains.conf with verify_certificate = False, but i still cannot init task, it seems doesn't work for the version i'm using.

@<1523701205467926528:profile|AgitatedDove14>
Hi, after rounding down numbers, the plot size decrease to 300Kb from 11M.This really works, thanks!

CostlyOstrich36 I'm afraid even i change to ClearML, the problem still exists...

Hi SuccessfulKoala55 I have run this in step 2

Hi GrumpyPenguin23 ,
Thanks your reply.
In 2, dose that mean i should develop another tool to parse the json standalone? 3 is a good solutionAnd i think what i actually need is the solution to integrate application based server,such as plotly dash or bokeh server in web ui?

SuccessfulKoala55 Ok, thanks, i will have a try.

HI: AgitatedDove14
2. I mean if my server break down, and i start a new server in another machine, can i migrate my backup experiments to the new server?
3. Not only change the info in web ui, can i connect to the old experiment , and report a new graph to that?

AppetizingMouse58 Great, Thanks so much! You have done a great work.
Another question, how to configure elasticsearch to run as a cluster with 2 or more nodes on the same or different machine 😅

AppetizingMouse58 Ok , i see, thanks!

SuccessfulKoala55
Do you mean even if the json is so large, if i use Logger.report_scatter2d() , it wont cause TransportError(429, 'circuit_breaking_exception ?

And actually the problem here is round doesn't work before tolist

Hi SuccessfulKoala55 :
I have make sure that all my data are roud to 4, but i still found my plotly data json is so large. And after checking the json ,i found there are many data with many digits, maybe those are info of plotly?
Here is my code:
` from plotly.subplots import make_subplots
import plotly.graph_objects as go
def draw_pr(self,precisions,recalls,score,distance,dataset):
score = np.round(score,4)
for i in range(4):
pre = np.around(precisions[i], 4)
recall...

And i try to upgrade elastic by your script, but it cannot success, the log shows :