parano/aws-ec2-deploy

Deploy BentoML bundled models to AWS EC2 with autoscaling

BentoML AWS EC2 deployment tool

Prerequisites

• An active AWS account configured on the machine with AWS CLI installed and configured

  • Install instruction: https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-install.html
  • Configure AWS account instruction: https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-configure.html

• Docker is installed and running on the machine.

  • Install instruction: https://docs.docker.com/install

• Install required python packages

  • $ pip install -r requirements.txt

Deployment operations

Create a deployment

Use command line

$ python deploy.py <Bento_bundle_path> <Deployment_name> <Config_JSON default is ec2_config.json>

Example:

$ MY_BUNDLE_PATH=${bentoml get IrisClassifier:latest --print-location -q)
$ python deploy.py $MY_BUNDLE_PATH my_first_deployment ec2_config.json

Use Python API

from deploy import deploy_to_ec2

deploy_to_ec2(BENTO_BUNDLE_PATH, DEPLOYMENT_NAME, CONFIG_JSON)

Available configuration options for EC2 deployments

• region: AWS region for EC2 deployment
• ec2_auto_scale:
  • min_size: The minimum number of instances for the auto scale group.
  • desired_capacity: The desired capacity for the auto scale group. Auto Scaling group will start by launching as many instances as are specified for desired capacity.
  • max_size: The maximum number of instances for the auto scale group
• instance_type: Instance type for the EC2 deployment. See https://aws.amazon.com/ec2/instance-types/ for more info
• ami_id: The Amazon machine image (AMI) used for launching EC2 instance. The default is /aws/service/ami-amazon-linux-latest/amzn2-ami-hvm-x86_64-gp2. See https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AMIs.html for more information.
• elb:
  • health_check_interval_seconds: The approximate interval, in seconds, between health checks of an individual instance. Valid Range: Minimum value of 5. Maximum value of 300.
  • health_check_path.: The URL path for health check. Default is /healthz
  • health_check_port: Health check port. Default is 5000
  • health_check_timeout_seconds: The amount of time, in seconds, during which no response means a failed health check.
  • healthy_threshold_count: The number of consecutive health checks successes required before moving the instance to the Healthy state. Valid Range: Minimum value of 2. Maximum value of 10.

Update a deployment

Use command line

$ python update.py <Bento_bundle_path> <Deployment_name> <Config_JSON>

Use Python API

from update import update_deployment
update_deployment(BENTO_BUNDLE_PATH, DEPLOYMENT_NAME, CONFIG_JSON)

Describe deployment status and information

Use command line

$ python describe.py <Deployment_name> <Config_JSON>

Use Python API

from describe import describe_deployment
describe_deployment(DEPLOYMENT_NAME, CONFIG_JSON)

Delete deployment

Use command line

$ python delete.py <Deployment_name> <Config_JSON>

Use Python API

from  delete import delete_deployment
delete_deployment(DEPLOYMENT_NAME, CONFIG_JSON)