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Odoo 12 Server Memory always increasing and never drops

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Få besked, når der er aktivitet på dette indlæg

Dette spørgsmål er blevet anmeldt
memory_usageodoo-server.confodoo12
1 Svar
11631 Visninger
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Paulo Matos

Hello gurus,

I have been fighting for months with tunning up my Odoo 12 server in regards to memory consumption.

I read a lot about it and made lots of tests without success.

My problem is, memory consumption is always increasing and never drops even if no one is using Odoo.

I am sure it is related to Odoo, because if I restart the service, memory is freed drastically.

Usually it begins at about 4%-5% and starts increasing (10, 15, 20… 50, 80…) as users starts using Odoo.

As per the CPU it is great. Sometimes it goes over 50% (on higher loads) but usually it is below 15% and I can see its consumption is being recicled/cleaned.

My Server
UBUNTU 18.04 – 4CPU / 8GB RAM
ODOO 12

odoo-server.conf


limit_memory_hard = 2684354560
limit_memory_soft = 2147483648
limit_request = 8192
limit_time_cpu = 300
limit_time_real = 600
limit_time_real_cron = -1
max_cron_threads = 2
workers=8

Tried to manage by changing “limit_memory_hard” and “limit_memory_soft” and use lower values but if the values are too low it raises an error:

"LongPolling Virtual memory limit reached"

What could be the problem and what are the advisable settings for this server specs?

Thank you very much
0
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Kassér
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Hilar Andikkadavath
Bedste svar

Lets recheck your memory handling calculations:

RAM: 8GB

Core: 4

So workers = (core * 2) + 1 = (4*2)+1(Cron Worker)

workers = 8+1=9

limit_memory_soft = 640 * 9 * 1024 * 1024 = 6039797760

limit_memory_hard = 768*9*1024*1024 = 7247757312

so your odoo conf must contain following calculations

limit_memory_soft = 6039797760
limit_memory_hard = 7247757312
workers = 9

Deatils:

  Multiprocessing options:
    --workers=WORKERS   Specify the number of workers, 0 disable prefork mode.
    --limit-memory-soft=LIMIT_MEMORY_SOFT
                        Maximum allowed virtual memory per worker, when
                        reached the worker be reset after the current request
                        (default 671088640 aka 640MB).
    --limit-memory-hard=LIMIT_MEMORY_HARD
                        Maximum allowed virtual memory per worker, when
                        reached, any memory allocation will fail (default
                        805306368 aka 768MB).
    --limit-time-cpu=LIMIT_TIME_CPU
                        Maximum allowed CPU time per request (default 60).
    --limit-time-real=LIMIT_TIME_REAL
                        Maximum allowed Real time per request (default 120).
    --limit-request=LIMIT_REQUEST
                        Maximum number of request to be processed per worker
                        (default 8192).



3
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Kassér
Paulo Matos
Forfatter

Hi Hillar,
Thank you very much for taking your time.
I will try with settings you sent me and keep you updated.
I thought increasing “memory limits” would make the system “recycle memory” later and I need it to be as fast as possible in order to release it.
I will keep you updated
Thank you once again

Paulo Matos
Forfatter

@Hillar,

The week has started and now I will be able to track the settings more easily because I will have several users using the system.

For now I'm using the settings you sent me and just decided to reduce the "db_maxconn" a bit to 10 (before it was 15).

So far everything seems to be working fine, but I will continue to follow.

Thanks again and I will keep you updated.

Paulo Matos
Forfatter

@Hillar
Thank you very much once again.

Two days and RAM is still below 50%.

Sometimes it goes over 60% but as expected, most of the time it’s below 50%.

Thank you very much

Tadeusz Jan Karpiński

It will be auto generated after starting odoo with config creation. Python odoo-bin -s

Obay Abdelgadir

I noticed that in the limit_memory_soft examply you multiplied by the number of workers 9. But this is not correct, the limit_memoy_soft and limit_memory_hard are per workers, thus you should not multiple by that, just 1024 * 1024 * SIZE_IN_MB

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