Sizing Worksheet

Performance_Scale_Sizing_Worksheet.md

Sizing Worksheet

I am writing this article to document data related to sizing classification for RHACM 2.2 deployments.

We define three generic size classifications, based on the number of managed clusters under management.

Then, we deploy RHACM 2.2 into each of the size classifications, and measure the system based on the workload.

Today, we will keep the workload very generic.

Workload

The workload that we will use are:

• number of managed clusters being managed
• number of grc policies applied to the managed clusters
• number of applications defined and applied to the managed clusters
• Observability component is enabled on worker nodes

This deployment consists of the core RHACM platform with Observability enabled. The hub cluster is running on AWS via IPI deployment.

SIZING CLASSIFICATION

TSHIRT SIZE	cpu master	cpu worker	ram GB master	ram GB worker	pvc storage	# managed clusters	# grc policies	# app
POC/small	12 core	12 core	48 GB	48 GB		<= 10	100s	100s
medium	24 core	72 core	96 GB	288 GB	3212 Gi**	<= 50	100s	100s
large	24 core	x	96 core	x		<= 1000	100s	100s

RESULTS

Here, we show the results for testing on the small tshirt sizing. The usage data is across the RHACM namespaces or worker nodes.

label	peak cpu usage	mean cpu usage	peak mem usage	mean mem usage	pvc storage	# managed clusters	# grc policies	# applications
POC/small	8.43 core	3.81 core	32.19 GB	23.22 GB	186.3 Gi	10	500	500
medium***	26.40 core	10.18 core	283.34 GB	154.54 GB	**	50	500	500
large	tbd

• The Observability reciever pvc needed to be adjusted to handle data collection from 10 managed clusters and workload.
• 500 apps and policies were deployed. These are policies and apps that create configmap resources on the managed clusters, allowing us not to be bound by CPU on the target managed clusters. Even at this load, the CPU usage on the target managed clusters was between 50%-70%.
• The PVC storage default for Observability reciever is 10GB. With this workload, we needed to be increased to 100GB.

** The actual pvc storage data was not collected for this run, so the claim size is listed as a reference. The conclusion is RHACM with Observability enabled, you will able to run on a small tshirt size, with this kind of workload.

*** This test run was conducted on a cluster with 6 workers @ 8 CPU/64GB RAM for each worker node.

Network traffic

For now, I'll just include the screenshot.

I include here our data for Network

• USE METHOD CLUSTER TX/RX

NOTE: The gap above is from updating the OBS component settings.

• TX/RX open-cluster-management namespace

• TX/RX open-cluster-management-observability

1. include api latency data