SDK in the Cloud¶
Once a cluster is up, you need to upload the SDK and the project to it.
Loading the SDK to a Cluster¶
To load a project in the cloud the first step is to upload the SDK images. This step may take a while but it is only required to be done once per bastion. You can reuse the same images for each cluster.
genvid-sdk upload-images-sdk --cloud-provider azure
The next step is to set up the SDK.
genvid-sdk -c myclusterid setup
After this step, some services are available in Cluster-UI. You can open Cluster-UI with the following command.
genvid-sdk -c myclusterid monitor
Although the list of jobs is empty, you can find the list of nodes at the top.
It may take some time for some nodes to show up, like the game
node.
Note
On average, a Windows server will finish configuring after between 15 and 25 minutes, although it can take up to an hour. If your setup is taking longer than that, check with your cloud provider to see if the node will eventually come up or if there are other issues with it.
Even without all the nodes available, you can load the SDK configuration into the cluster:
genvid-sdk -c myclusterid load-config-sdk
The SDK definition is loaded and now there is one job: services
.
Building the Tutorial Sample for the Cloud¶
Assuming the Docker host was set up correctly, you can build the images for the tutorial. (See Building Images Using Docker for more information.)
Prepare for building.
py tutorial.py prepare
Build the project and the website.
py tutorial.py build-cloud
Upload the images and load the project definition.
py tutorial.py -c myclusterid upload-images --update-config py tutorial.py -c myclusterid load
After this step, the images are available on S3 and the project configuration is loaded and ready to use in the cloud.
Open the Jobs page.
genvid-sdk -c myclusterid monitor
Click the Start all button.
Click the Tutorial Demo link.
Check that everything is working correctly.
When you’re finished click the Stop All button to stop the services.
Note that the Unity Sample and Unreal Cube sample can be run in the cloud with similar steps.