If the concurrent execution capability of the standard size is insufficient, increase the number of platform nodes and accordingly increase the resource requests and limits for the platform services to create a larger deployment.
Domino recommends that you consult your Customer Success Manager for customizations and advice before you deploy this model.
| Parameter | Value |
|---|---|
Number of platform nodes | 4-5 |
CPU per node | 16 cores |
Memory per node | 64 GB |
Maximum concurrent executions | 600 |
If you use this sizing model, ensure that your platform node pool can scale up to the number of platform nodes above. Then, add the following resource request and limit overrides to the fleetcommand-agent configuration file:
release_overrides:
cluster-autoscaler:
chart_values:
resources:
limits:
cpu: 1
memory: 2Gi
requests:
cpu: 50m
memory: 100Mi
data-plane:
chart_values:
agent:
deployment:
resources:
limits:
cpu: 4
memory: 4Gi
requests:
cpu: 2
memory: 2Gi
elasticsearch:
chart_values:
esJavaOpts: '-Xms8g -Xmx8g'
replicas: 5
resources:
requests:
cpu: 1
memory: 8Gi
git:
chart_values:
persistence:
size: 160Gi
resources:
limits:
cpu: 4
memory: 4Gi
requests:
cpu: 2
memory: 2Gi
mongodb-replicaset:
chart_values:
persistentVolume:
size: 120Gi
resources:
requests:
cpu: 2
memory: 4Gi
newrelic-events:
chart_values:
resources:
limits:
memory: 1Gi
requests:
memory: 256Mi
newrelic-infrastructure:
chart_values:
resources:
limits:
memory: 1Gi
requests:
cpu: 200m
memory: 128Mi
newrelic-logging:
chart_values:
resources:
limits:
cpu: 1
memory: 600Mi
newrelic-open-metrics:
chart_values:
resources:
limits:
cpu: 2
memory: 4Gi
requests:
cpu: 1
memory: 2Gi
nucleus:
chart_values:
config:
javaMaxHeap:
dispatcher: 5G
keycloak: {}
replicaCount:
frontend: 3
resources:
dispatcher:
limits:
cpu: 5
memory: 9Gi
requests:
cpu: 4
memory: 9Gi
train:
limits:
memory: 3Gi
requests:
memory: 3Gi
prometheus:
chart_values:
server:
resources:
limits:
memory: 14Gi
requests:
cpu: 1100m
memory: 7Gi
rabbitmq-ha:
chart_values:
resources:
limits:
cpu: 2
memory: 6Gi
requests:
cpu: 1
memory: 6Gi
cost-analyzer-prometheus:
chart_values:
server:
resources:
limits:
cpu: 800m
memory: 8Gi
requests:
cpu: 500m
memory: 5GiTo check the status of your available platform resources and allocation, run the following:
kubectl describe nodes -l dominodatalab.com/node-pool=platform | grep -A 10 Allocated
Learn how to manage compute resources.