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In 10 days our product is featured in a tv-show at prime time.

We expect 50k visitors on our website.

Cause we are a small company (5 users) we would like to avoid a load balancing server scenario for this single visitor peak.

Question 1: Is this configuration working for this case?

- Hardware: Google Cloud instance with 64 vCPUs, 240gb RAM, 20gb SSD

- Debian: default

- Nginx: default

- Odoo: 10 community - fresh database with 30 products and this modules: Ecommerce, Sales, Purchase, Manufacturing, Inventory, Accounting, no custom modules

workers = 100

limit_memory_hard = 1677721600 (1,6GB)

limit_memory_soft = 1073741824 (1GB)

limit_request = 8192

limit_time_cpu = 60

limit_time_real = 120

- Postgres: max_connections = 6500 (100 worker * 64 connections)

Question 2: How can I simulate the load to locate bottelnecks?

Has anyone experience with www.loader.io ?

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TV-Show is done and Odoo ran stable.

Visitors: 27k, concurrend 10k

with this settings:

- Hardware: Google Cloud instance with 64 vCPUs, 240gb RAM, 20gb SSD

- workers = 100

- limit_memory_hard = 1677721600 (1,6GB)

- limit_memory_soft = 1073741824 (1GB)

- http://pgtune.leopard.in.ua/

Load average:

CPUs: 30%

RAM: 25GB

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Hello Martin Schubert,

By Setting only workers is not enough you have to configure few things,

: (parameter of odoo/postgres database).

1> IN odoo config :   

    limit-memory-soft,limit-memory-hard

2> IN postgres (database) :

    max_connections,shared_buffers,effective_cache_size,work_mem

    maintenance_work_mem,checkpoint_segments,checkpoint_completion_target

    wal_buffers,default_statistics_target.

  • To share the workload between workers mostly you need to divide and allocate memory in such a way so its depending on the system config. (e.g Hard disc Type, Memory (RAM), Size of it,version of postgres and your O.S) .

You do not need to worry about it ,just go through either of below URL to boost up your server speed.

http://pgtune.leopard.in.ua

https://github.com/gregs1104/pgtune

HOPE this will help you a lot !

Many Thanks.


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