arvados-dispatch-cloud is only relevant for cloud installations. Skip this section if you are installing an on premises cluster that will spool jobs to Slurm or LSF.
The cloud dispatch service is for running containers on cloud VMs. It works with Microsoft Azure and Amazon EC2; future versions will also support Google Compute Engine.
The cloud dispatch service can run on any node that can connect to the Arvados API service, the cloud provider’s API, and the SSH service on cloud VMs. It is not resource-intensive, so you can run it on the API server node.
More detail about the internal operation of the dispatcher can be found in the architecture section.
Add or update the following portions of your cluster configuration file, config.yml. Refer to config.defaults.yml for information about additional configuration options. The DispatchPrivateKey should be the private key generated in Create a SSH keypair .
Services:
DispatchCloud:
InternalURLs:
"http://localhost:9006": {}
Containers:
CloudVMs:
# BootProbeCommand is a shell command that succeeds when an instance is ready for service
BootProbeCommand: "sudo systemctl status docker"
# --- driver-specific configuration goes here --- see Amazon and Azure examples below ---
DispatchPrivateKey: |
-----BEGIN RSA PRIVATE KEY-----
MIIEpQIBAAKCAQEAqXoCzcOBkFQ7w4dvXf9B++1ctgZRqEbgRYL3SstuMV4oawks
ttUuxJycDdsPmeYcHsKo8vsEZpN6iYsX6ZZzhkO5nEayUTU8sBjmg1ZCTo4QqKXr
FJ+amZ7oYMDof6QEdwl6KNDfIddL+NfBCLQTVInOAaNss7GRrxLTuTV7HcRaIUUI
jYg0Ibg8ZZTzQxCvFXXnjseTgmOcTv7CuuGdt91OVdoq8czG/w8TwOhymEb7mQlt
lXuucwQvYgfoUgcnTgpJr7j+hafp75g2wlPozp8gJ6WQ2yBWcfqL2aw7m7Ll88Nd
[...]
oFyAjVoexx0RBcH6BveTfQtJKbktP1qBO4mXo2dP0cacuZEtlAqW9Eb06Pvaw/D9
foktmqOY8MyctzFgXBpGTxPliGjqo8OkrOyQP2g+FL7v+Km31Xs61P8=
-----END RSA PRIVATE KEY-----
InstanceTypes:
x1md:
ProviderType: x1.medium
VCPUs: 8
RAM: 64GiB
IncludedScratch: 64GB
Price: 0.62
x1lg:
ProviderType: x1.large
VCPUs: 16
RAM: 128GiB
IncludedScratch: 128GB
Price: 1.23
To specify instance types with NVIDIA GPUs, the compute image must be built with CUDA support , and you must include an additional CUDA section:
InstanceTypes:
g4dn:
ProviderType: g4dn.xlarge
VCPUs: 4
RAM: 16GiB
IncludedScratch: 125GB
Price: 0.56
CUDA:
DriverVersion: "11.4"
HardwareCapability: "7.5"
DeviceCount: 1
The DriverVersion is the version of the CUDA toolkit installed in your compute image (in X.Y format, do not include the patchlevel). The HardwareCapability is the CUDA compute capability of the GPUs available for this instance type. The DeviceCount is the number of GPU cores available for this instance type.
See Autoscaling compute node scratch space for details about compute image configuration.
The Containers.InstanceTypes list should be modified so that all AddedScratch lines are removed, and the IncludedScratch value should be set to 5 TB. This way, the scratch space requirements will be met by all the defined instance type. For example:
InstanceTypes:
c5large:
ProviderType: c5.large
VCPUs: 2
RAM: 4GiB
IncludedScratch: 5TB
Price: 0.085
m5large:
ProviderType: m5.large
VCPUs: 2
RAM: 8GiB
IncludedScratch: 5TB
Price: 0.096
...
You will also need to create an IAM role in AWS with these permissions:
{
"Statement": [
{
"Effect": "Allow",
"Action": [
"ec2:AttachVolume",
"ec2:DescribeVolumeStatus",
"ec2:DescribeVolumes",
"ec2:DescribeTags",
"ec2:ModifyInstanceAttribute",
"ec2:DescribeVolumeAttribute",
"ec2:CreateVolume",
"ec2:DeleteVolume",
"ec2:CreateTags"
],
"Resource": "*"
}
]
}
Then set Containers.CloudVMs.DriverParameters.IAMInstanceProfile to the name of the IAM role. This will make arvados-dispatch-cloud pass an IAM instance profile to the compute nodes when they start up, giving them sufficient permissions to attach and grow EBS volumes.
When Containers.LocalKeepBlobBuffersPerVCPU is non-zero, the compute node will spin up a local Keepstore service for direct storage access. If Keep is backed by S3, the compute node will need to be able to access the S3 bucket.
If the AWS credentials for S3 access are configured in config.yml (i.e. Volumes.DriverParameters.AccessKeyID and Volumes.DriverParameters.SecretAccessKey), these credentials will be made available to the local Keepstore on the compute node to access S3 directly and no further configuration is necessary.
If config.yml does not have Volumes.DriverParameters.AccessKeyID and Volumes.DriverParameters.SecretAccessKey defined, Keepstore uses instance metadata to retrieve IAM role credentials. The CloudVMs.DriverParameters.IAMInstanceProfile parameter must be configured with the name of a profile whose IAM role has permission to access the S3 bucket(s). With this setup, arvados-dispatch-cloud will attach the IAM role to the compute node as it is created. The instance profile name is often identical to the name of the IAM role.
If you are also using EBS Autoscale feature, the role in IAMInstanceProfile must have both ec2 and s3 permissions.
The ImageID value is the compute node image that was built in the previous section.
Containers:
CloudVMs:
ImageID: ami-01234567890abcdef
Driver: ec2
DriverParameters:
# If you are not using an IAM role for authentication, specify access
# credentials here. Otherwise, omit or set AccessKeyID and
# SecretAccessKey to an empty value.
AccessKeyID: XXXXXXXXXXXXXXXXXXXX
SecretAccessKey: YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY
SecurityGroupIDs:
- sg-0123abcd
SubnetID: subnet-0123abcd
Region: us-east-1
EBSVolumeType: gp2
AdminUsername: arvados
Example policy for the IAM role used by the cloud dispatcher:
{
"Id": "arvados-dispatch-cloud policy",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ec2:CreateTags",
"ec2:Describe*",
"ec2:CreateImage",
"ec2:CreateKeyPair",
"ec2:ImportKeyPair",
"ec2:DeleteKeyPair",
"ec2:RunInstances",
"ec2:StopInstances",
"ec2:TerminateInstances",
"ec2:ModifyInstanceAttribute",
"ec2:CreateSecurityGroup",
"ec2:DeleteSecurityGroup",
"iam:PassRole"
],
"Resource": "*"
}
]
}
Using managed disks:
The ImageID value is the compute node image that was built in the previous section.
Containers:
CloudVMs:
ImageID: "zzzzz-compute-v1597349873"
Driver: azure
# (azure) managed disks: set MaxConcurrentInstanceCreateOps to 20 to avoid timeouts, cf
# https://docs.microsoft.com/en-us/azure/virtual-machines/linux/capture-image
MaxConcurrentInstanceCreateOps: 20
DriverParameters:
# Credentials.
SubscriptionID: XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX
ClientID: XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX
ClientSecret: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
TenantID: XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX
# Data center where VMs will be allocated
Location: centralus
# The resource group where the VM and virtual NIC will be
# created.
ResourceGroup: zzzzz
NetworkResourceGroup: yyyyy # only if different from ResourceGroup
Network: xxxxx
Subnet: xxxxx-subnet-private
# The resource group where the disk image is stored, only needs to
# be specified if it is different from ResourceGroup
ImageResourceGroup: aaaaa
Azure recommends using managed images. If you plan to start more than 20 VMs simultaneously, Azure recommends using a shared image gallery instead to avoid slowdowns and timeouts during the creation of the VMs.
Using an image from a shared image gallery:
Containers:
CloudVMs:
ImageID: "shared_image_gallery_image_definition_name"
Driver: azure
DriverParameters:
# Credentials.
SubscriptionID: XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX
ClientID: XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX
ClientSecret: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
TenantID: XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX
# Data center where VMs will be allocated
Location: centralus
# The resource group where the VM and virtual NIC will be
# created.
ResourceGroup: zzzzz
NetworkResourceGroup: yyyyy # only if different from ResourceGroup
Network: xxxxx
Subnet: xxxxx-subnet-private
# The resource group where the disk image is stored, only needs to
# be specified if it is different from ResourceGroup
ImageResourceGroup: aaaaa
# (azure) shared image gallery: the name of the gallery
SharedImageGalleryName: "shared_image_gallery_1"
# (azure) shared image gallery: the version of the image definition
SharedImageGalleryImageVersion: "0.0.1"
Using unmanaged disks (deprecated):
The ImageID value is the compute node image that was built in the previous section.
Containers:
CloudVMs:
ImageID: "https://zzzzzzzz.blob.core.windows.net/system/Microsoft.Compute/Images/images/zzzzz-compute-osDisk.55555555-5555-5555-5555-555555555555.vhd"
Driver: azure
DriverParameters:
# Credentials.
SubscriptionID: XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX
ClientID: XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX
ClientSecret: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
TenantID: XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX
# Data center where VMs will be allocated
Location: centralus
# The resource group where the VM and virtual NIC will be
# created.
ResourceGroup: zzzzz
NetworkResourceGroup: yyyyy # only if different from ResourceGroup
Network: xxxxx
Subnet: xxxxx-subnet-private
# Where to store the VM VHD blobs
StorageAccount: example
BlobContainer: vhds
Get the SubscriptionID and TenantID:
$ az account list
[
{
"cloudName": "AzureCloud",
"id": "XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXX",
"isDefault": true,
"name": "Your Subscription",
"state": "Enabled",
"tenantId": "YYYYYYYY-YYYY-YYYY-YYYYYYYY",
"user": {
"name": "you@example.com",
"type": "user"
}
}
]
You will need to create a “service principal” to use as a delegated authority for API access.
$ az ad app create --display-name "Arvados Dispatch Cloud (ClusterID)" --homepage "https://arvados.org" --identifier-uris "https://ClusterID.example.com" --end-date 2299-12-31 --password Your_Password
$ az ad sp create "appId"
(appId is part of the response of the previous command)
$ az role assignment create --assignee "objectId" --role Owner --scope /subscriptions/{subscriptionId}/
(objectId is part of the response of the previous command)
Now update your config.yml file:
ClientID is the ‘appId’ value.
ClientSecret is what was provided as Your_Password.
Run the cloudtest tool to verify that your configuration works. This creates a new cloud VM, confirms that it boots correctly and accepts your configured SSH private key, and shuts it down.
~$ arvados-server cloudtest && echo "OK!"
Refer to the cloudtest tool documentation for more information.
# dnf install arvados-dispatch-cloud
# apt install arvados-dispatch-cloud
# systemctl enable --now arvados-dispatch-cloud
# systemctl status arvados-dispatch-cloud
[...]
If systemctl status indicates it is not running, use journalctl to check logs for errors:
# journalctl --since -5min -u arvados-dispatch-cloud
Make sure the cluster config file is up to date on the API server host then restart the API server and controller processes to ensure the configuration changes are visible to the whole cluster.
# systemctl restart nginx arvados-controller
# arvados-server check
On the dispatch node, start monitoring the arvados-dispatch-cloud logs:
# journalctl -o cat -fu arvados-dispatch-cloud.service
In another terminal window, use the diagnostics tool to run a simple container.
# arvados-client sudo diagnostics
INFO 5: running health check (same as `arvados-server check`)
INFO 10: getting discovery document from https://zzzzz.arvadosapi.com/discovery/v1/apis/arvados/v1/rest
...
INFO 160: running a container
INFO ... container request submitted, waiting up to 10m for container to run
After performing a number of other quick tests, this will submit a new container request and wait for it to finish.
While the diagnostics tool is waiting, the arvados-dispatch-cloud logs will show details about creating a cloud instance, waiting for it to be ready, and scheduling the new container on it.
You can also use the arvados-dispatch-cloud API to get a list of queued and running jobs and cloud instances. Use your ManagementToken to test the dispatcher’s endpoint. For example, when one container is running:
~$ curl -sH "Authorization: Bearer $token" http://localhost:9006/arvados/v1/dispatch/containers
{
"items": [
{
"container": {
"uuid": "zzzzz-dz642-hdp2vpu9nq14tx0",
...
"state": "Running",
"scheduling_parameters": {
"partitions": null,
"preemptible": false,
"max_run_time": 0
},
"exit_code": 0,
"runtime_status": null,
"started_at": null,
"finished_at": null
},
"instance_type": {
"Name": "Standard_D2s_v3",
"ProviderType": "Standard_D2s_v3",
"VCPUs": 2,
"RAM": 8589934592,
"Scratch": 16000000000,
"IncludedScratch": 16000000000,
"AddedScratch": 0,
"Price": 0.11,
"Preemptible": false
}
}
]
}
A similar request can be made to the http://localhost:9006/arvados/v1/dispatch/instances endpoint.
After the container finishes, you can get the container record by UUID from a shell server to see its results:
shell:~$ arv get zzzzz-dz642-hdp2vpu9nq14tx0
{
...
"exit_code":0,
"log":"a01df2f7e5bc1c2ad59c60a837e90dc6+166",
"output":"d41d8cd98f00b204e9800998ecf8427e+0",
"state":"Complete",
...
}
You can use standard Keep tools to view the container’s output and logs from their corresponding fields. For example, to see the logs from the collection referenced in the log field:
~$ arv keep ls a01df2f7e5bc1c2ad59c60a837e90dc6+166
./crunch-run.txt
./stderr.txt
./stdout.txt
~$ arv-get a01df2f7e5bc1c2ad59c60a837e90dc6+166/stdout.txt
2016-08-05T13:53:06.201011Z Hello, Crunch!
If the container does not dispatch successfully, refer to the arvados-dispatch-cloud logs for information about why it failed.
The content of this documentation is licensed under the
Creative
Commons Attribution-Share Alike 3.0 United States licence.
Code samples in this documentation are licensed under the
Apache License, Version 2.0.