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Increase the default instance sizes #1338

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Jun 23, 2022
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Increase the default instance sizes #1338

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4 changes: 2 additions & 2 deletions docs/source/installation/configuration.md
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Original file line number Diff line number Diff line change
Expand Up @@ -464,8 +464,8 @@ Control the amount of storage allocated to shared filesystem.

```yaml
storage:
conda_store: 20Gi
shared_filesystem: 10Gi
conda_store: 200Gi
shared_filesystem: 200Gi
```

## Profiles
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38 changes: 19 additions & 19 deletions docs/source/installation/existing.md
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Expand Up @@ -82,10 +82,10 @@ carefully:
- `Node IAM Role` must be the IAM role described proceeding
- "Node Group compute configuration"
- `Instance type`
- The recommended minimum vCPU and memory for a `general` node is 4 vCPU / 16 GB RAM
- The recommended minimum vCPU and memory for a `user` and `worker` node is 2 vCPU / 8 GB RAM
- The recommended minimum vCPU and memory for a `general` node is 8 vCPU / 32 GB RAM
- The recommended minimum vCPU and memory for a `user` and `worker` node is 4 vCPU / 16 GB RAM
- `Disk size`
- The recommended minimum is 20 GB for the attached EBS (block-strage)
- The recommended minimum is 200 GB for the attached EBS (block-strage)
- "Node Group scaling configuration"
- `Minimum size` and `Maximum size` of 1 for the `general` node group
- "Node Group subnet configuration"
Expand Down Expand Up @@ -172,37 +172,37 @@ local:
profiles:
jupyterlab:
- display_name: Small Instance
description: Stable environment with 1 cpu / 4 GB ram
default: true
kubespawner_override:
cpu_limit: 1
cpu_guarantee: 0.75
mem_limit: 4G
mem_guarantee: 2.5G
image: quansight/qhub-jupyterlab:v0.3.13
- display_name: Medium Instance
description: Stable environment with 2 cpu / 8 GB ram
default: true
kubespawner_override:
cpu_limit: 2
cpu_guarantee: 1.5
mem_limit: 8G
mem_guarantee: 5G
image: quansight/qhub-jupyterlab:v0.3.13
- display_name: Medium Instance
description: Stable environment with 4 cpu / 16 GB ram
kubespawner_override:
cpu_limit: 4
cpu_guarantee: 3
mem_limit: 16G
mem_guarantee: 10G
image: quansight/qhub-jupyterlab:v0.3.13
dask_worker:
Small Worker:
worker_cores_limit: 1
worker_cores: 0.75
worker_memory_limit: 4G
worker_memory: 2.5G
worker_threads: 1
image: quansight/qhub-dask-worker:v0.3.13
Medium Worker:
worker_cores_limit: 2
worker_cores: 1.5
worker_memory_limit: 8G
worker_memory: 5G
worker_threads: 2
image: quansight/qhub-dask-worker:v0.3.13
Medium Worker:
worker_cores_limit: 4
worker_cores: 3
worker_memory_limit: 16G
worker_memory: 10G
worker_threads: 4
image: quansight/qhub-dask-worker:v0.3.13
environments:
environment-dask.yaml:
name: dask
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60 changes: 30 additions & 30 deletions qhub/initialize.py
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Expand Up @@ -39,7 +39,7 @@
"jupyterlab": f"quansight/qhub-jupyterlab:{qhub_image_tag}",
"dask_worker": f"quansight/qhub-dask-worker:{qhub_image_tag}",
},
"storage": {"conda_store": "60Gi", "shared_filesystem": "100Gi"},
"storage": {"conda_store": "200Gi", "shared_filesystem": "200Gi"},
"theme": {
"jupyterhub": {
"hub_title": None,
Expand Down Expand Up @@ -120,9 +120,9 @@
"region": "nyc3",
"kubernetes_version": "PLACEHOLDER",
"node_groups": {
"general": {"instance": "g-4vcpu-16gb", "min_nodes": 1, "max_nodes": 1},
"user": {"instance": "g-2vcpu-8gb", "min_nodes": 1, "max_nodes": 5},
"worker": {"instance": "g-2vcpu-8gb", "min_nodes": 1, "max_nodes": 5},
"general": {"instance": "g-8vcpu-32gb", "min_nodes": 1, "max_nodes": 1},
"user": {"instance": "g-4vcpu-16gb", "min_nodes": 1, "max_nodes": 5},
"worker": {"instance": "g-4vcpu-16gb", "min_nodes": 1, "max_nodes": 5},
},
}
# Digital Ocean image slugs are listed here https://slugs.do-api.dev/
Expand All @@ -132,9 +132,9 @@
"region": "us-central1",
"kubernetes_version": "PLACEHOLDER",
"node_groups": {
"general": {"instance": "n1-standard-4", "min_nodes": 1, "max_nodes": 1},
"user": {"instance": "n1-standard-2", "min_nodes": 0, "max_nodes": 5},
"worker": {"instance": "n1-standard-2", "min_nodes": 0, "max_nodes": 5},
"general": {"instance": "n1-standard-8", "min_nodes": 1, "max_nodes": 1},
"user": {"instance": "n1-standard-4", "min_nodes": 0, "max_nodes": 5},
"worker": {"instance": "n1-standard-4", "min_nodes": 0, "max_nodes": 5},
},
}

Expand All @@ -143,13 +143,13 @@
"kubernetes_version": "PLACEHOLDER",
"node_groups": {
"general": {
"instance": "Standard_D4_v3",
"instance": "Standard_D8_v3",
"min_nodes": 1,
"max_nodes": 1,
},
"user": {"instance": "Standard_D2_v2", "min_nodes": 0, "max_nodes": 5},
"user": {"instance": "Standard_D4_v3", "min_nodes": 0, "max_nodes": 5},
"worker": {
"instance": "Standard_D2_v2",
"instance": "Standard_D4_v3",
"min_nodes": 0,
"max_nodes": 5,
},
Expand All @@ -163,51 +163,51 @@
"region": "us-west-2",
"kubernetes_version": "PLACEHOLDER",
"node_groups": {
"general": {"instance": "m5.xlarge", "min_nodes": 1, "max_nodes": 1},
"user": {"instance": "m5.large", "min_nodes": 1, "max_nodes": 5},
"worker": {"instance": "m5.large", "min_nodes": 1, "max_nodes": 5},
"general": {"instance": "m5.2xlarge", "min_nodes": 1, "max_nodes": 1},
"user": {"instance": "m5.xlarge", "min_nodes": 1, "max_nodes": 5},
"worker": {"instance": "m5.xlarge", "min_nodes": 1, "max_nodes": 5},
},
}

DEFAULT_PROFILES = {
"jupyterlab": [
{
"display_name": "Small Instance",
"description": "Stable environment with 1 cpu / 4 GB ram",
"description": "Stable environment with 2 cpu / 8 GB ram",
"default": True,
"kubespawner_override": {
"cpu_limit": 1,
"cpu_guarantee": 0.75,
"mem_limit": "4G",
"mem_guarantee": "2.5G",
"cpu_limit": 2,
"cpu_guarantee": 1.5,
"mem_limit": "8G",
"mem_guarantee": "5G",
},
},
{
"display_name": "Medium Instance",
"description": "Stable environment with 2 cpu / 8 GB ram",
"description": "Stable environment with 4 cpu / 16 GB ram",
"kubespawner_override": {
"cpu_limit": 2,
"cpu_guarantee": 1.5,
"mem_limit": "8G",
"mem_guarantee": "5G",
"cpu_limit": 4,
"cpu_guarantee": 3,
"mem_limit": "16G",
"mem_guarantee": "10G",
},
},
],
"dask_worker": {
"Small Worker": {
"worker_cores_limit": 1,
"worker_cores": 0.75,
"worker_memory_limit": "4G",
"worker_memory": "2.5G",
"worker_threads": 1,
},
"Medium Worker": {
"worker_cores_limit": 2,
"worker_cores": 1.5,
"worker_memory_limit": "8G",
"worker_memory": "5G",
"worker_threads": 2,
},
"Medium Worker": {
"worker_cores_limit": 4,
"worker_cores": 3,
"worker_memory_limit": "16G",
"worker_memory": "10G",
"worker_threads": 4,
},
},
}

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