A Deep Water workshop was presented at H2O Open Tour Dallas. The hands-on workshop is available in a public EC2 Amazon AMI. This document describes how to load and run this workshop. Note that this requires an account on Amazon AWS.
- Log in to your your AWS account at https://aws.amazon.com.
- In the upper right corner of the Amazon Web Services page, change the location in the location drop-down to US East (N Virginia).
- Select the EC2 option under the Compute section to launch the EC2 Dashboard.
- Select Images > AMIs on left navigation.
- On the Launch screen, change the dropdown at the top to Public images , then search for the Deep Water AMI using the ID: ami-10bd9607. Click Enter to begin the search.
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After the AMI is located, click the Launch button.
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At this point, you will be directed to choose your GPU instance type. Select an instance, for example g2.2xlarge, then click Next: Configure Instance Details.
- Accept the default configuration for this instance, then click Next: Add Storage.
- Specify a value greater than or equal to 50 GB for the Size value (storage size), then click Next: Tag Instance.
- Enter a unique name tag to identify your instance, then click Next: Configure Security Group.
- Update the security group, and add rules as indicated in the following table (refer also to the image below the table):
Type | Protocol | Port Range | Source |
---|---|---|---|
SSH | TCP | 22 | Anywhere 0.0.0.0/0 |
HTTP | TCP | 80 | Anywhere 0.0.0.0/0 |
HTTPS | TCP | 443 | Anywhere 0.0.0.0/0 |
Custom TCP Rule | TCP | 8080 | Anywhere 0.0.0.0/0 |
Custom TCP Rule | TCP | 54321-54330 | Anywhere 0.0.0.0/0 |
Custom TCP Rule | TCP | 55001 | Anywhere 0.0.0.0/0 |
Custom TCP Rule | TCP | 55011 | Anywhere 0.0.0.0/0 |
Custom TCP Rule | TCP | 55021 | Anywhere 0.0.0.0/0 |
These rules are necessary to open the Flow UI, Prediction Services, Jupyter Notebook server and log in to the instance via command line. Click Review and Launch.
- Review the configuration, and then click Launch.
- A popup will appear prompting you to select a key pair. This will be used to log in to the instance via command line. You can select your existing key pair or create a new one. Be sure to accept the acknowledgement, then click Launch Instances to start the new instance.
After the instance starts, you can view/start/stop/terminate the instance from the EC2 Dashboard by clicking on Running Instances.
To open a Jupyter Notebook server, enter <Public_IP_Address>:80
in the address bar of your browser window. A message box will appear, prompting you to provide authentication. Enter deepwater
for the username, and enter the AWS Instance ID as the password.
To open the Flow UI, enter <Public_IP_Address>:54321
in the address bar of your browser window.
You can log in to this instance using ssh with Terminal (Mac/Linux) or Putty (Window). For example:
ssh -i <Private_Key_File> ubuntu@<Public_IP_Address>
Note that the public IP address will change on reboot. Also, the key pair file should have restricted permissions (chmod 400 <Private_Key_File>
).