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document memory recommendations #125

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merged 1 commit into from
Nov 17, 2023

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also include default username/password for grafana

Signed-off-by: Michael Kalantar <[email protected]>
@kalantar kalantar requested a review from Alan-Cha November 17, 2023 16:24
@kalantar kalantar self-assigned this Nov 17, 2023
kubectl config set-context --current --namespace=modelmesh-serving
```
1. Ensure that you have the [`kubectl`](https://kubernetes.io/docs/reference/kubectl/) and [`helm`](https://helm.sh/) CLIs installed.
2. Have access to a cluster running [KServe ModelMesh Serving](https://github.com/kserve/modelmesh-serving). For example, you can create a modelmesh-serving [Quickstart](https://github.com/kserve/modelmesh-serving/blob/release-0.11/docs/quickstart.md) environment. If using the Quickstart environment, your default namespace will be changed to `modelmesh-serving`. If using a local cluster (for example, [Kind](https://kind.sigs.k8s.io/) or [Minikube](https://minikube.sigs.k8s.io/docs/)), we recommend providing the cluster with at least 16GB of memory.
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2. Have access to a cluster running [KServe ModelMesh Serving](https://github.com/kserve/modelmesh-serving). For example, you can create a modelmesh-serving [Quickstart](https://github.com/kserve/modelmesh-serving/blob/release-0.11/docs/quickstart.md) environment. If using the Quickstart environment, your default namespace will be changed to `modelmesh-serving`. If using a local cluster (for example, [Kind](https://kind.sigs.k8s.io/) or [Minikube](https://minikube.sigs.k8s.io/docs/)), we recommend providing the cluster with at least 16GB of memory.
2. Have access to a cluster running [KServe ModelMesh Serving](https://github.com/kserve/modelmesh-serving). For example, you can create a modelmesh-serving [Quickstart](https://github.com/kserve/modelmesh-serving/blob/release-0.11/docs/quickstart.md) environment. If using the Quickstart environment, your default namespace will be changed to `modelmesh-serving`. If using a local cluster (for example, [Kind](https://kind.sigs.k8s.io/) or [Minikube](https://minikube.sigs.k8s.io/docs/)), we recommend providing the cluster with at least 16GB of memory.

@kalantar kalantar merged commit 0509db2 into iter8-tools:main Nov 17, 2023
@kalantar kalantar deleted the memory-recommendations branch December 11, 2023 19:25
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