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     <h1>Tag: gce</h1>


     <div class="post">

     <h2 class="post-title"><a href="/blog/2014/02/18/libcloud-0-14-and-google-cloud-platform.html">Libcloud 0.14 and Google Cloud Platform</a></h2>

   <span class="post-date-author">By Rick Wright on Feb 18, 2014</span>

   <div class="post-content">
     <p><em>This is a guest post by <a href="https://github.com/wrigri">Rick Wright</a>. Rick is an engineer at Google and
 the main contributor to the Libcloud Google Compute Engine driver.</em></p>

 <p>As anyone following this blog knows, Libcloud 0.14 was <a href="/blog/2014/01/22/libcloud-0-14-0-released.html">recently released</a>.
 Included in this release is new support for the Google Compute Engine service
 that was recently made generally available.</p>

 <p>The first Libcloud driver for Google Compute Engine was initially released last
 summer, and has been continually updated to support new Compute Engine
 features. Support for the Compute Engine Load Balancer was also recently added.</p>

 <p>Libcloud had previously added support for Google Cloud Storage through the S3
 compatibility API.</p>

 <p>In this post, we’ll show you how to get up and running with Google Compute
 Engine with Libcloud, show you how to create some instances (nodes) and point
 you to additional resources. We also show you how you can start up 20
 instances in under a minute.</p>

 <div class="imginline">
   <p><a href="https://cloud.google.com/" target="_blank">
   <img src="/images/posts/gce/image03.png" class="img-responsive inline" />
   </a></p>
 </div>

 <h2 id="getting-started">Getting Started</h2>

 <p>If you haven’t yet signed up for Google Compute Engine, more information can
 be found on the <a href="https://cloud.google.com/">Google Cloud Platform</a> site. We hope that you will look at
 the Google Cloud Platform and consider Compute Engine for workloads of any
 size.</p>

 <p>If you are familiar with Libcloud, using the driver for Compute Engine will
 also be familiar to you as nearly all of the standard Libcloud API methods for
 Compute and Load Balancing are supported by the Compute Engine drivers.</p>

 <h2 id="setting-up-authentication">Setting up Authentication</h2>

 <p>Google Compute Engine uses OAuth2 for authentication and Libcloud supports two
 different authentication methods for Compute Engine: Service Accounts and
 Installed Applications. More information can be found about these options in
 the <a href="https://libcloud.readthedocs.org/en/latest/compute/drivers/gce.html">driver documentation</a>, but here is a simple walk-through for getting
 your Service Account credentials (note that the Service Account authentication
 requires the PyCrypto library):</p>

 <p>From the Console (<a href="https://cloud.google.com/console">https://cloud.google.com/console</a>), select your project. When
 your project is open, select “APIs &amp; auth” and then “Credentials” as shown
 below:</p>

 <div class="imginline">
   <p><img src="/images/posts/gce/image01.png" class="img-responsive inline" /></p>
 </div>

 <p>To create a new Service Account ID, click on “Create New Client ID”</p>

 <div class="imginline">
   <p><img src="/images/posts/gce/image04.png" class="img-responsive inline" /></p>
 </div>

 <p>Select “Service account” and click “Create Client ID”</p>

 <div class="imginline">
   <p><img src="/images/posts/gce/image00.png" class="img-responsive inline" /></p>
 </div>

 <p>This will create and download a PCKS-12 private key to your local machine. You
 will need to convert this to a .pem format key. (See additional instructions
 in the <a href="https://libcloud.readthedocs.org/en/latest/compute/drivers/gce.html">driver documentation</a>).</p>

 <div class="imginline">
   <p><img src="/images/posts/gce/image02.png" class="img-responsive inline" /></p>
 </div>

 <p>To connect to Compute Engine from Libclould, you will need to provide both the
 “Email address” for the service account and the path to the key file.</p>

 <h2 id="creating-an-instance">Creating an Instance</h2>

 <p>The Compute Engine driver supports the normal Libcloud ways of doing things.
 For example, to create the driver you would do something like this:</p>

 <pre>
 from libcloud.compute.types import Provider
 from libcloud.compute.providers import get_driver
 Driver = get_driver(Provider.GCE)
 gce = Driver('your_service_account_email', 'path_to_pem_file',
              datacenter='us-central1-a',
              project='your_project_id')
 </pre>

 <p>Then, you may want to get a list of machine sizes or images to use for your
 node creation:</p>

 <pre>
 sizes = gce.list_sizes()
 images = gce.list_images()
 </pre>

 <p>and then filter them to find the correct size/image object to create your
 node. For example:</p>

 <pre>
 size_obj = [s for s in sizes if s.id == 'n1-standard-1'][0]
 image_obj = [i for i in images if i.name == 'debian-7'][0]
 </pre>

 <p>Finally, you would create the node using the create_node() method:</p>

 <pre>
 new_node = gce.create_node(name='my_node', size=size_obj,
                            image=img_obj)
 </pre>

 <p>The GCE driver also supports the ability to pass in size/image by name instead
 of by object, so you could create your new node like this, without looking up
 the sizes/images:</p>

 <pre>
 new_node = gce.create_node(name='my_node', size='n1-standard-1',
                            image='debian-7')
 </pre>

 <p>In this case a new node will be created using the “n1-standard-1” machine
 type and will use the latest “debian-7” image that is available.</p>

 <h2 id="creating-multiple-instances">Creating Multiple Instances</h2>

 <p>We have added an extra method to the Compute Engine driver to help in the
 creation of multiple instances/nodes in parallel.  This is the
 “ex_create_multiple_nodes()” method, and it can be used like this:</p>

 <pre>
 base_name = 'multiple-nodes'
 number = 20
 start_time = time.time()
 multi_nodes = gce.ex_create_multiple_nodes(
     base_name, 'n1-standard-1', 'debian-7', number)
 end_time = time.time()

 print('Created the following %s nodes in %.2f seconds' % (
    number, end_time-start_time))

 for node in multi_nodes:
    print('   %s' % node.name)
 </pre>

 <p>Running this gives the following output (timing will likely vary somewhat):</p>

 <pre>
 Created the following 20 nodes in 35.77 seconds
   multiple-nodes-000
   multiple-nodes-001
   multiple-nodes-002
   multiple-nodes-003
   multiple-nodes-004
   ...
 </pre>

 <h2 id="onward">Onward</h2>

 <p>This post showed you how to get started, and additional example code can be
 found in the <a href="https://github.com/apache/libcloud/blob/trunk/demos/gce_demo.py">Libcloud Compute Engine demo code</a>. The demo code can show you
 how to use most of the features of the driver, including: Creating disks,
 firewalls and addresses; setting tags; attaching and detaching disks and
 deleting resources. There is <a href="https://github.com/apache/libcloud/blob/trunk/demos/gce_lb_demo.py">separate demo code</a> for the Load Balancer
 functions which shows how to quickly set up 3 web servers with a Load Balancer
 controlling the traffic to them. In addition, the driver documentation
 contains the documentation for the extra methods that cover nearly all of the
 features of the Compute Engine API.</p>

 <p>We are excited to be able to contribute to the Libcloud project and hope that
 you will find it useful. We like working with Libcloud and have used it as the
 basis for contributing code to other open source projects such as <a href="http://ansible.com/">Ansible</a>
 and <a href="http://www.saltstack.com/">SaltStack</a>. If you run into problems or find bugs, please
 <a href="https://issues.apache.org/jira/browse/LIBCLOUD">report them</a> (or send a <a href="https://github.com/apache/libcloud">pull request</a>) and we will be happy to continue
 to fix and enhance the Compute Engine driver in Libcloud.</p>


   </div>

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       <p>Tags: <a href="/blog/tags/articles.html" rel="tag">articles</a>, <a href="/blog/tags/providers.html" rel="tag">providers</a>, <a href="/blog/tags/gce.html" rel="tag">gce</a></p>
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	<h1>Tag: gce</h1>




	<div class="post">

	<h2 class="post-title"><a href="/blog/2014/02/18/libcloud-0-14-and-google-cloud-platform.html">Libcloud 0.14 and Google Cloud Platform</a></h2>

	<span class="post-date-author">By Rick Wright on Feb 18, 2014</span>

	<div class="post-content">
	<p><em>This is a guest post by <a href="https://github.com/wrigri">Rick Wright</a>. Rick is an engineer at Google and
	the main contributor to the Libcloud Google Compute Engine driver.</em></p>

	<p>As anyone following this blog knows, Libcloud 0.14 was <a href="/blog/2014/01/22/libcloud-0-14-0-released.html">recently released</a>.
	Included in this release is new support for the Google Compute Engine service
	that was recently made generally available.</p>

	<p>The first Libcloud driver for Google Compute Engine was initially released last
	summer, and has been continually updated to support new Compute Engine
	features. Support for the Compute Engine Load Balancer was also recently added.</p>

	<p>Libcloud had previously added support for Google Cloud Storage through the S3
	compatibility API.</p>

	<p>In this post, we’ll show you how to get up and running with Google Compute
	Engine with Libcloud, show you how to create some instances (nodes) and point
	you to additional resources. We also show you how you can start up 20
	instances in under a minute.</p>

	<div class="imginline">
	<p><a href="https://cloud.google.com/" target="_blank">
	<img src="/images/posts/gce/image03.png" class="img-responsive inline" />
	</a></p>
	</div>

	<h2 id="getting-started">Getting Started</h2>

	<p>If you haven’t yet signed up for Google Compute Engine, more information can
	be found on the <a href="https://cloud.google.com/">Google Cloud Platform</a> site. We hope that you will look at
	the Google Cloud Platform and consider Compute Engine for workloads of any
	size.</p>

	<p>If you are familiar with Libcloud, using the driver for Compute Engine will
	also be familiar to you as nearly all of the standard Libcloud API methods for
	Compute and Load Balancing are supported by the Compute Engine drivers.</p>

	<h2 id="setting-up-authentication">Setting up Authentication</h2>

	<p>Google Compute Engine uses OAuth2 for authentication and Libcloud supports two
	different authentication methods for Compute Engine: Service Accounts and
	Installed Applications. More information can be found about these options in
	the <a href="https://libcloud.readthedocs.org/en/latest/compute/drivers/gce.html">driver documentation</a>, but here is a simple walk-through for getting
	your Service Account credentials (note that the Service Account authentication
	requires the PyCrypto library):</p>

	<p>From the Console (<a href="https://cloud.google.com/console">https://cloud.google.com/console</a>), select your project. When
	your project is open, select “APIs & auth” and then “Credentials” as shown
	below:</p>

	<div class="imginline">
	<p><img src="/images/posts/gce/image01.png" class="img-responsive inline" /></p>
	</div>

	<p>To create a new Service Account ID, click on “Create New Client ID”</p>

	<div class="imginline">
	<p><img src="/images/posts/gce/image04.png" class="img-responsive inline" /></p>
	</div>

	<p>Select “Service account” and click “Create Client ID”</p>

	<div class="imginline">
	<p><img src="/images/posts/gce/image00.png" class="img-responsive inline" /></p>
	</div>

	<p>This will create and download a PCKS-12 private key to your local machine. You
	will need to convert this to a .pem format key. (See additional instructions
	in the <a href="https://libcloud.readthedocs.org/en/latest/compute/drivers/gce.html">driver documentation</a>).</p>

	<div class="imginline">
	<p><img src="/images/posts/gce/image02.png" class="img-responsive inline" /></p>
	</div>

	<p>To connect to Compute Engine from Libclould, you will need to provide both the
	“Email address” for the service account and the path to the key file.</p>

	<h2 id="creating-an-instance">Creating an Instance</h2>

	<p>The Compute Engine driver supports the normal Libcloud ways of doing things.
	For example, to create the driver you would do something like this:</p>

	<pre>
	from libcloud.compute.types import Provider
	from libcloud.compute.providers import get_driver
	Driver = get_driver(Provider.GCE)
	gce = Driver('your_service_account_email', 'path_to_pem_file',
	datacenter='us-central1-a',
	project='your_project_id')
	</pre>

	<p>Then, you may want to get a list of machine sizes or images to use for your
	node creation:</p>

	<pre>
	sizes = gce.list_sizes()
	images = gce.list_images()
	</pre>

	<p>and then filter them to find the correct size/image object to create your
	node. For example:</p>

	<pre>
	size_obj = [s for s in sizes if s.id == 'n1-standard-1'][0]
	image_obj = [i for i in images if i.name == 'debian-7'][0]
	</pre>

	<p>Finally, you would create the node using the create_node() method:</p>

	<pre>
	new_node = gce.create_node(name='my_node', size=size_obj,
	image=img_obj)
	</pre>

	<p>The GCE driver also supports the ability to pass in size/image by name instead
	of by object, so you could create your new node like this, without looking up
	the sizes/images:</p>

	<pre>
	new_node = gce.create_node(name='my_node', size='n1-standard-1',
	image='debian-7')
	</pre>

	<p>In this case a new node will be created using the “n1-standard-1” machine
	type and will use the latest “debian-7” image that is available.</p>

	<h2 id="creating-multiple-instances">Creating Multiple Instances</h2>

	<p>We have added an extra method to the Compute Engine driver to help in the
	creation of multiple instances/nodes in parallel. This is the
	“ex_create_multiple_nodes()” method, and it can be used like this:</p>

	<pre>
	base_name = 'multiple-nodes'
	number = 20
	start_time = time.time()
	multi_nodes = gce.ex_create_multiple_nodes(
	base_name, 'n1-standard-1', 'debian-7', number)
	end_time = time.time()

	print('Created the following %s nodes in %.2f seconds' % (
	number, end_time-start_time))

	for node in multi_nodes:
	print(' %s' % node.name)
	</pre>

	<p>Running this gives the following output (timing will likely vary somewhat):</p>

	<pre>
	Created the following 20 nodes in 35.77 seconds
	multiple-nodes-000
	multiple-nodes-001
	multiple-nodes-002
	multiple-nodes-003
	multiple-nodes-004
	...
	</pre>

	<h2 id="onward">Onward</h2>

	<p>This post showed you how to get started, and additional example code can be
	found in the <a href="https://github.com/apache/libcloud/blob/trunk/demos/gce_demo.py">Libcloud Compute Engine demo code</a>. The demo code can show you
	how to use most of the features of the driver, including: Creating disks,
	firewalls and addresses; setting tags; attaching and detaching disks and
	deleting resources. There is <a href="https://github.com/apache/libcloud/blob/trunk/demos/gce_lb_demo.py">separate demo code</a> for the Load Balancer
	functions which shows how to quickly set up 3 web servers with a Load Balancer
	controlling the traffic to them. In addition, the driver documentation
	contains the documentation for the extra methods that cover nearly all of the
	features of the Compute Engine API.</p>

	<p>We are excited to be able to contribute to the Libcloud project and hope that
	you will find it useful. We like working with Libcloud and have used it as the
	basis for contributing code to other open source projects such as <a href="http://ansible.com/">Ansible</a>
	and <a href="http://www.saltstack.com/">SaltStack</a>. If you run into problems or find bugs, please
	<a href="https://issues.apache.org/jira/browse/LIBCLOUD">report them</a> (or send a <a href="https://github.com/apache/libcloud">pull request</a>) and we will be happy to continue
	to fix and enhance the Compute Engine driver in Libcloud.</p>


	</div>

	<div class="row section post-meta">
	<div class="col-md-12 post-tags">
	<p>Tags: <a href="/blog/tags/articles.html" rel="tag">articles</a>, <a href="/blog/tags/providers.html" rel="tag">providers</a>, <a href="/blog/tags/gce.html" rel="tag">gce</a></p>
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