This page documents the interface for Tango's Virtual Machine Management Systems' (VMMSs) API and instructions for setting up VMMSs. See the vmms directory in Tango for example implementations.
The functions necessary to implement the API are documented here. Note that for certain implementations, some of these methods will be no-ops since the VMMS doesn't require any particular instructions to perform the specified actions. Furthermore, throughout this document, we use the term "VM" liberally to represent any container-like object on which Tango jobs may be run.
Creates a new VM instance for the VMMS based on the fields of
vm, which is a
TangoMachine object defined in
waitVM(self, vm, max_secs)
Waits at most
max_secs for a VM to be ready to run jobs. Returns an error if the VM is not ready after
copyIn(self, vm, inputFiles)
Copies the input files for a job into the VM.
inputFiles is a list of
InputFile objects defined in
tangoObjects.py. For each
file.localFile is the name of the file on the Tango host machine and
file.destFile is what the name of the file should be on the VM.
runJob(self, vm, runTimeout, maxOutputFileSize)
Runs the autodriver binary on the VM. The autodriver runs
make on the VM (which in turn runs the job via the
Makefile that was provided as a part of the input files for the job). The output from the autodriver most likely should be redirected to some feedback file to be used in the next method of the API.
copyOut(self, vm, destFile)
Copies the output file for the job out of the VM into
destFile on the Tango host machine.
Removes a VM from the Tango system.
Removes a VM from the Tango system and makes sure that it has been removed.
Returns a complete list of VMs associated with this Tango system.
Docker VMMS Setup
This is a guide to set up Tango to run jobs inside Docker containers.
Install docker on host machine by following instructions on the docker installation page. Ensure docker is running:
$ docker ps # CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
Build base Docker image from root Tango directory.
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cd path/to/Tango docker build -t autograding_image vmms/ docker images autograding_image # Check if image built
# in config.py VMMS_NAME = "localDocker"
Amazon EC2 VMMS Setup
This is a guide to set up Tango to run jobs on an Amazon EC2 VM.
Create an AWS Account or use an existing one.
secret_access_keyby following the instructions here.
Add AWS Credentials to a file called
~/.botousing the following format:
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[Credentials] aws_access_key_id = MYAMAZONTESTKEY12345 aws_secret_access_key = myawssecretaccesskey12345
Tango uses the Boto Python package to interface with Amazon Web Services
In the AWS EC2 console, create an Ubuntu 14.04+ EC2 instance and save the
.pemfile in a safe location.
Copy the directory and contents of
autodriver/in the Tango repo into the EC2 VM. For more help connecting to the EC2 instance follow this guide
chmod 400 /path/my-key-pair.pem scp -i /path/my-key-pair.pem -r autodriver/ ubuntu@<ec2-host-name>.compute-1.amazonaws.com:~/
The autodriver is used as a sandbox environment to run the job inside the VM. It limits Disk I/O, Disk Usage, monitors security, and controls other valuable
In the EC2 VM, compile the autodriver.
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$ cd autodriver/ $ make clean; make $ cp -p autodriver /usr/bin/autodriver
autogradeLinux user and directory. All jobs will be run under this user.
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$ useradd autograde $ mkdir autograde $ chown autograde autograde $ chown :autograde autograde
In the AWS EC2 console, create an AMI image from your EC2 VM. Use this guide to create a custom AMI.
Exit the EC2 instance and edit the following values in
config.pyin the Tango directory.
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# VMMS to use. Must be set to a VMMS implemented in vmms/ before # starting Tango. Options are: "localDocker", "distDocker", # "tashiSSH", and "ec2SSH" VMMS_NAME = "ec2SSH" ###### # Part 5: EC2 Constants # EC2_REGION = 'us-east-1' # EC2 Region EC2_USER_NAME = 'ubuntu' # EC2 username DEFAULT_AMI = 'ami-4c99c35b' # Custom AMI Id DEFAULT_INST_TYPE = 't2.micro' # Instance Type DEFAULT_SECURITY_GROUP = 'autolab-autograde-ec2' # Security Group with full access to EC2 SECURITY_KEY_PATH = '/path/to/my-key-pair.pem' # Absolute path to my-key-pair.pem DYNAMIC_SECURITY_KEY_PATH = '' # Leave blank SECURITY_KEY_NAME = 'my-key-pair' # Name of the key file. Ex: if file name is 'my-key-pair.pem', fill value with 'my-key-pair' TANGO_RESERVATION_ID = '1' # Leave as 1 INSTANCE_RUNNING = 16 # Status code of a running instance, leave as 16
You should now be ready to run Tango jobs on EC2! Use the Tango CLI to test your setup.