Genomics Annotation Service

Directory contents are as follows:

• /ann - Annotator files
• /aws - AWS user data files
• /web - Web application files
• /util - Utility scripts for notifications, archival, and restoration

Architecture

Setup

1. Run python launch_instance.py in your local machine to create an EC2 instance you can SSH later. You can add the suffix web, ann, or util to the instance tag once it starts for use clarity.
2. Add from AWS Instances console and your to your remote SSH config file, like this:

Host <PREFERED-HOST-DENOMINATION>
    HostName <PUBLIC-IPv4-DNS>
    IdentityFile `~/.ssh/<CNET-ID>.pem`
    User ec2-user
    ForwardAgent yes

Then, SSH into instance.

3. Activate virtual environment source mpcs-cc/bin/activate.
4. Go into the mpcs-cc directory and clone the repository for the project, as: git clone https://github.com/MPCS-51083-Cloud-Computing/final-project-benjaleivas gas. This will create a folder gas in your instance with all the necessary code.
5. If instance handles the web app:
   • Go to /home/ec2-user/mpcs-cc/gas/web and create .env file according to instructions in final_project.pdf, then run source .env.
   • Run python manage.py db init, then python manage.py db migrate, and finally python manage.py db upgrade (only once!).
   • Go to /home/ec2-user/mpcs-cc/gas/web/config.py and replace '' with your corresponding ID.
   • Download deployment certification and keys using aws s3 cp s3://mpcs-cc-resources/ssl/privkey.pem /home/ec2-user/mpcs-cc and aws s3 cp s3://mpcs-cc-resources/ssl/fullchain.pem /home/ec2-user/mpcs-cc, and modify the .env file to update the SSL_CERT_PATH and SSL_KEY_PATH to these new files.
   • Run chmod 755 run_gas.sh to make file executable, then run ./run_gas.sh console, and then go to https://bleiva.mpcs-cc.com:4433, the webpage should be up.

Troubleshooting

If you run into trouble with the instances, particularly with the web app, and need to reboot them, please follow this process. In your local machine:

1. Run python /Users/bleiva/Desktop/CAPP/quarters/2023-2024/3_spring/cc/mpcsdomain delete --subdomain bleiva --ip <PUBLIC IPv4 ADDRESS> with the public IP address of the instance that (currently) handles the web app.

2. Terminate the web app instance in the AWS Instances console.

3. Run python launch_instance.py and tag it as <CNETID>-gas-web.

4. Once the instance is running, run python /Users/bleiva/Desktop/CAPP/quarters/2023-2024/3_spring/cc/mpcsdomain create --subdomain bleiva --ip <PUBLIC IPv4 ADDRESS> in your local machine with the public IP adress of the new instance.

5. Then, we initate an archive-retrieval job to bring back the result files from the user's vault back to the S3 bucket. This job is also suscribed to the thaw process' topic ARN, so that we can know when the retrieval is done and the output is ready for download.

6. After initiating all these processes, we delete the message that was received by the GLACIER_RESTORE queue.

7. On the other hand, thaw.py has another queue GLACER_THAW listening to the messages described in step 4.

8. Once this message is received, the output is retrieved, the s3_key_result_file is re-generated, and the previously vaulted result files are saved back into the S3 bucket.