These instructions are for getting Vagrant running and building and publishing a new AMI using Packer. We plan to eventually move this process to a Docker container and eliminate the use of Vagrant and Ansible for simplicity.
- Vagrant 1.8+
- VirtualBox 4.3+
- Python 2.7
- Ansible 2.1+
| Name | Description |
|---|---|
setup |
Bring up the virtual machine and install dependent software on it |
First, set the RASTER_VISION_DATA_DIR environment variable on your host machine. All data including datasets and results should be stored in a single directory outside of the repo. The Vagrantfile maps the RASTER_VISION_DATA_DIR environment variable on the host machine to /opt/data on the guest machine. Within the project root, execute the following commands to setup and then log into the VM.
$ ./scripts/setup
$ vagrant sshIf you get an error message about the Docker daemon not being started, you
may want to run vagrant provision.
In order to run scripts on GPUs and in parallel, we use AWS Batch.
Use deployment/batch_amis.py to update the Batch environment AMI. This requires your raster-vision AWS profile to be configured.
$ aws --profile raster-vision configure
$ cd deployment
$ pip install -r requirements.txt
$ ./batch_amis.py build-amis --aws-profile raster-vision
...
==> Builds finished. The artifacts of successful builds are:
--> raster-vision-gpu: AMIs were created:
us-east-1: ami-fb5c7980Use the AMI ID provided above, to update the ComputeResources > imageId field in deployment/batch/compute_environment_{gpu,cpu}.json. To apply these changes, delete the existing Batch environments using the AWS Console, and then re-run the steps in the section above.
Prune any old AMIs by using the prune-amis command to batch_amis.py
$ ./batch_amis.py prune-amis --keep 10