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Chapter 12. Scaling Multicloud Object Gateway performance
The Multicloud Object Gateway (MCG) performance may vary from one environment to another. In some cases, specific applications require faster performance which can be easily addressed by scaling S3 endpoints.
The MCG resource pool is a group of NooBaa daemon containers that provide two types of services enabled by default:
- Storage service
- S3 endpoint service
S3 endpoint service
The S3 endpoint is a service that every Multicloud Object Gateway (MCG) provides by default that handles the heavy lifting data digestion in the MCG. The endpoint service handles the inline data chunking, deduplication, compression, and encryption, and it accepts data placement instructions from the MCG.
The number of MultiCloud Object Gateway (MCG) endpoints scale automatically when the load on the MCG S3 service increases or decreases. OpenShift Data Foundation clusters are deployed with one active MCG endpoint. Each MCG endpoint pod is configured by default with 1 CPU and 2Gi memory request, with limits matching the request. When the CPU load on the endpoint crosses over an 80% usage threshold for a consistent period of time, a second endpoint is deployed lowering the load on the first endpoint. When the average CPU load on both endpoints falls below the 80% threshold for a consistent period of time, one of the endpoints is deleted. This feature improves performance and serviceability of the MCG.
You can scale the Horizontal Pod Autoscaler (HPA) for noobaa-endpoint using the following oc patch command, for example:
# oc patch -n openshift-storage storagecluster ocs-storagecluster \
--type merge \
--patch '{"spec": {"multiCloudGateway": {"endpoints": {"minCount": 3,"maxCount": 10}}}}'
The example above sets the minCount to 3 and the maxCount to `10.
12.2. Increasing CPU and memory for PV pool resources
MCG default configuration supports low resource consumption. However, when you need to increase CPU and memory to accommodate specific workloads and to increase MCG performance for the workloads, you can configure the required values for CPU and memory in the OpenShift Web Console.
Procedure
-
In the OpenShift Web Console, navigate to Storage
Object Storage Backing Store. - Select the relevant backing store and click on YAML.
Scroll down until you find
spec:and updatepvPoolwith CPU and memory. Add a new property of limits and then add cpu and memory.Example reference:
spec: pvPool: resources: limits: cpu: 1000m memory: 4000Mi requests: cpu: 800m memory: 800Mi storage: 50Gi- Click Save.
Verification steps
- To verfiy, you can check the resource values of the PV pool pods.
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