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Tuning resources
In high throughput cluster, it is common practice to optimizing the allocation and usage of computing resources. In such environments, where the volume of transactions or operations per second is very high, resource tuning is essential to ensure that the cluster performs optimally.
The following is an example of how to use that practice in a large cluster. Further tweaks may required for different clusters.
agent:
alligator:
requests:
memory: 300Mi
cpu: 160m
limits:
memory: 700Mi
cpu: 800m
k8sWatcher:
resources:
requests:
cpu: 50m
memory: 300Mi
limits:
cpu: 100m
memory: 500Mi
portal:
resources:
requests:
cpu: 50m
memory: 100Mi
limits:
cpu: 100m
memory: 256Mi
clickhouse:
resources:
requests:
cpu: 600m
memory: 4096Mi
limits:
memory: 6000Mi
opentelemetry-collector:
replicaCount: 2
requests:
cpu: 500m
memory: 1024Mi
limits:
cpu: 1200m
memory: 2048Mi
metrics-ingester:
resources:
limits:
cpu: 750m
memory: 512Mi
requests:
cpu: 250m
memory: 256Mi
victoria-metrics-single:
server:
resources:
requests:
cpu: 1000m
memory: 5000Mi
limits:
cpu: 1000m
memory: 5000Mi
custom-metrics:
extraArgs:
remoteWrite.maxHourlySeries: "1000000"
remoteWrite.maxDailySeries: "10000000"
resources:
requests:
cpu: 500m
memory: 512Mi
limits:
cpu: 1000m
memory: 1Gi
Last modified 29d ago