Python Library for Windows Azure
Project description
Simple Azure deploys Azure Templates and launches Virtual Machines with Service Management API with a few steps like other cloud providers e.g. AWS. [Documentation](https://simple-azure.readthedocs.org/)
QuickStart
Starting 101-vm-sshkey template:
>>> from simpleazure import SimpleAzure
>>> saz = SimpleAzure()
# aqst is for Azure QuickStart Templates
>>> vm_sshkey_template = saz.aqst.get_template('101-vm-sshkey')
# arm is for Azure Resource Manager
>>> saz.arm.load_template(vm_sshkey_template)
>>> saz.arm.set_parameter("sshKeyData", "ssh-rsa AAAB... hrlee@quickstart")
>>> saz.arm.deploy()
Docker Image
Simple Azure is available in Docker image to run.
Simple Azure only:
docker run -i -t lee212/simpleazure
With IPython Notebook:
docker run -d -p 8888:8888 lee212/simpleazure_with_ipython
Open a browser with the port number 8888.
Installation
From github.com:
git clone https://github.com/lee212/simpleazure.git
cd simpleazure
pip install -r requirements.txt
python setup.py install
from Pypi:
pip install simpleazure
Caveats
Classic (legacy) Python SDK is based on https://github.com/Azure/azure-sdk-for-python/blob/master/azure-servicemanagement-legacy
Virtual Machines, Cloud Services and Storage are only used in the classic mode to deploy virtrual machines.
Prerequisite
Azure Cli installation
sudo apt-get install nodejs-legacy
sudo apt-get install npm
sudo npm install -g azure-cli
Account Setup for ASM
Open a browser to http://go.microsoft.com/fwlink/?LinkId=254432
*-DD-MM-YYYY-credentials.publishsettings is downloaded on a local directory
Run azure config mode as # To run azure cli tool via the classic service management certificate.
Run azure account import <publishsettings file>
Run azure account cert export ~/.azure/managementCertificate.pem
Example (classic mode for launching VMs)
Create a VM on Windows Azure (ubuntu 14.04 is a default image)
from simpleazure import SimpleAzure as saz
azure = saz()
azure.asm.create_vm()
Status can be seen here.
print vars(azure.get_status())
{'error': None, 'http_status_code': u'200', 'id': u'', 'status': u'Succeeded'}
or
print vars(azure.get_deployment())
{'configuration': u'<ServiceConfiguration xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://schemas.microsoft.com/ServiceHosting/2008/10/ServiceConfiguration">\r\n <Role name="myvm-20735">\r\n <Instances count="1" />\r\n </Role>\r\n</ServiceConfiguration>',
'created_time': u'2013-07-22T16:10:18Z',
'deployment_slot': u'Production',
'extended_properties': {},
'input_endpoint_list': None,
'label': u'bXl2bS0yMDczNQ==',
'last_modified_time': u'',
'locked': False,
'name': u'myvm-20735',
'persistent_vm_downtime_info': None,
'private_id': u'17071ce8bea345cf1575341c8510c84a',
'role_instance_list': <azure.servicemanagement.RoleInstanceList at 0x333b5d0>,
'role_list': <azure.servicemanagement.RoleList at 0x333b610>,
'rollback_allowed': False,
'sdk_version': u'',
'status': u'Running',
'upgrade_domain_count': u'1',
'upgrade_status': None,
'url': u'http://myvm-20735.cloudapp.net/'}
Example for multiple deployment (classic)
cluster() function helps to deploy several VMs at once.
azure = saz()
azure.asm.create_cluster()
my-cluster-vm-0-87412
{'request_id': '88c94c00288d42acaf877783f09c4558'}
my-cluster-vm-1-61293
{'request_id': 'abfd563c2c4f4926872b6b1dba27a93b'}
my-cluster-vm-2-96085
{'request_id': '29b55f6cb5e94cfdbf244a7c848c854d'}
my-cluster-vm-3-46927
{'request_id': 'b1a3446ebafe47a295df4c9d1b7d743c'}
Example for multiple deployment with Azure Data Science Core
Deploy 5 VMs with Azure Data Science Core at West Europe
azure = saz()
q = azure.asm.get_registered_image(name="Azure-Data-Science-Core")
azure.asm.set_image(image=q,refresh=True)
azure.asm.set_location("West Europe")
azure.asm.create_cluster(num=5)
List of VMs
vars(azure.asm.list_deployments().hosted_services)
Terminating VM
azure.asm.delete_vm()
or
azure.asm.delete_vm('vm-name')
Clustering
TBD
Contact
hroe.lee at gmail.com
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