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update cpu sizing based on the hashing changes

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Closes #26490

Signed-off-by: Kamesh Akella <kamesh.asp@gmail.com>
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Kamesh Akella 2024-02-01 18:47:51 +05:30 committed by Alexander Schwartz
parent 537b0b4073
commit 4459ed66ad
1 changed files with 4 additions and 4 deletions
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8
docs/guides/high-availability/concepts-memory-and-cpu-sizing.adoc
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@ -40,7 +40,7 @@ Recommendations:
This assumes that each user connects to only one client.
Memory requirements increase with the number of client sessions per user session (not tested yet).
* For each 40 user logins per second, 1 vCPU per Pod in a three-node cluster (tested with up to 300 per second).
* For each 30 user logins per second, 1 vCPU per Pod in a three-node cluster (tested with up to 300 per second).
+
{project_name} spends most of the CPU time hashing the password provided by the user.
@ -59,7 +59,7 @@ Performance of {project_name} dropped significantly when its Pods were throttled
Target size:
* 50,000 active user sessions
* 40 logins per seconds
* 30 logins per seconds
* 450 client credential grants per second
* 350 refresh token requests per second
@ -67,7 +67,7 @@ Limits calculated:
* CPU requested: 3 vCPU
+
(40 logins per second = 1 vCPU, 450 client credential grants per second = 1 vCPU, 350 refresh token = 1 vCPU)
(30 logins per second = 1 vCPU, 450 client credential grants per second = 1 vCPU, 350 refresh token = 1 vCPU)
* CPU limit: 9 vCPU
+
@ -88,7 +88,7 @@ The following setup was used to retrieve the settings above to run tests of abou
* OpenShift 4.13.x deployed on AWS via ROSA.
* Machinepool with `m5.4xlarge` instances.
* {project_name} deployed with the Operator and 3 pods.
* Default user password hashing with PBKDF2 27,500 hash iterations (which is the default).
* Default user password hashing with PBKDF2(SHA512) 210,000 hash iterations (which is the default).
* Client credential grants don't use refresh tokens (which is the default).
* Database seeded with 100,000 users and 100,000 clients.
* Infinispan caches at default of 10,000 entries, so not all clients and users fit into the cache, and some requests will need to fetch the data from the database.