Creating a Cloud Storage bucket

The following instructions detail how to create a Cloud Storage bucket.Buckets are the basic containers that hold your data in Cloud Storage.

1. In your terminal window, create a Cloud Storage bucket, whereYOUR_BUCKET_NAME represents the name of your bucket:

   gcloudstoragebucketscreategs://YOUR_BUCKET_NAME

2. To view uploaded images in the Bookshelf app, set the bucket's Identity and Access Managementpolicy to grant thelegacyObjectReader role toallUsers:

   gcloudstoragebucketsadd-iam-policy-bindinggs://YOUR_BUCKET_NAME--member=allUsers--role=roles/storage.legacyObjectReader

Cloning the sample app

The sample app is available on GitHub atGoogleCloudPlatform/getting-started-python.

1. Clone the repository:

   gitclonehttps://github.com/GoogleCloudPlatform/getting-started-python.git-bsteps

2. Go to the sample directory:

   cdgetting-started-python/7-gce

Configuring the app

1. Openconfig.py for editing.

   • Set the value ofPROJECT_ID to your project ID.

   • Set the valueCLOUD_STORAGE_BUCKET to the name of your Cloud Storagebucket.

2. Save and closeconfig.py.

Running the app on your local computer

1. Create an isolated Python environment, and install dependencies:

   Linux/macOS

   virtualenv-ppython3envsourceenv/bin/activatepipinstall-rrequirements.txt

   Windows

   virtualenv-ppython3envenv\scripts\activatepipinstall-rrequirements.txt

2. Run the application:

   pythonmain.py

3. In your browser, enter the following address:

   http://localhost:8080

To stop the local web server, pressControl+C. If you want to exitthe virtual environment, enterdeactivate.

Deploying the sample app

Push your code to a repository

You can get your code onto a running Compute Engine instance in severalways. One way is to useCloud Source Repositories.Every project includes a Git repository that is available toCompute Engine instances. Your instances then pull the latest version ofyour app's code during startup. Using a Git repository is convenient becauseupdating your app doesn't require configuring new images or instances; justrestart an existing instance or create one.

1. For your first time using Git, usegit config --global to set upyour identity.

2. In your Google Cloud console, create a repository:

   Create repository

3. Then push your app code to your project's repository where[YOUR_PROJECT_ID] is your project ID and[YOUR_REPO] is the nameof your repository:

   gitcommit-am"Updating configuration"gitconfigcredential.helpergcloud.shgitremoteaddcloudhttps://source.developers.google.com/p/[YOUR_PROJECT_ID]/r/[YOUR_REPO]gitpushcloudmaster

Create the deployment

After your configuration is committed and your code is uploaded toCloud Source Repositories, you can use the Deployment Managerto create the deployment:

1. Go to thedeployment_manager directory:

   cdgetting-started-python/7-gce/gce/deployment_manager

2. Create the deployment:

   gclouddeployment-managerdeploymentscreatemy-deployment--configconfig.yaml

3. View a list of all the deployments:

   gclouddeployment-managerdeploymentslist

4. Get a description of the deployment and the resources it created:

   gclouddeployment-managerdeploymentsdescribemy-deployment

View your app

After you create the forwarding rule, it can take several minutes for yourconfiguration to propagate and for traffic to be routed to your instances.

1. To check the progress:

   gcloudcomputebackend-servicesget-healthbookshelf-my-deployment-frontend--global

2. When at least one of your instances reportsHEALTHY, get the forwarding IPaddress for the load balancer:

   gcloudcomputeforwarding-ruleslist--global

   Your forwarding-rules IP address is in theIP_ADDRESS column.

3. In your browser, enter the IP address from the list.

   Your app is now running on Google Cloud.

Understanding the code

Configure the deployment

You can see how the deployment is configured inconfig.yaml:

imports:-name:bookshelf.jinjapath:./bookshelf.jinjaresources:-name:bookshelftype:bookshelf.jinjaproperties:zone:us-central1-fmachine-type:n1-standard-1machine-image:https://www.googleapis.com/compute/v1/projects/debian-cloud/global/images/family/debian-9min-instances:1max-instances:10target-utilization:0.6scopes:-https://www.googleapis.com/auth/cloud-platform

The configuration file imports the template file as a resource and uses it todefine a resource namedbookshelf. The template takes several properties asparameters. For more information about creatingDeployment Manager configuration files, seeCreating a configuration.

Configure the deployment template's schema

Look at the schema filebookshelf.jinja.schema, which defines anddocuments the parameters that the deployment is expected to provide in itsconfiguration file. For more information about configuration schemas, seeUsing schemas.

info:title:BookshelfGCEDeployauthor:GoogleInc.description:CreatesaGCEDeploymentimports:-name:startup-scriptpath:../startup-script.shrequired:-zone-machine-type-min-instances-max-instances-scopesproperties:zone:description:Zonetocreatetheresourcesin.type:stringmachine-type:description:Typeofmachinetousetype:stringmachine-image:description:TheOSimagetouseonthemachinestype:stringmin-instances:description:TheminimumnumberofVMstheautoscalerwillcreatetype:integermax-instances:description:ThemaximumnumberofVMstheautoscalerwillcreatetype:integertarget-utilization:description:ThetargetCPUusagefortheautoscalertobaseitsscalingontype:numberscopes:description:AlistofscopestocreatetheVMwithtype:arrayminItems:1items:type:string

Configure the deployment template

The template defines several resources needed to create an autoscaled, load-balanced, managed instance group. For a full description of the resourcescreated, see the comments in the template and review theBookshelf on Compute Engine tutorial.

Keep in mind that Deployment Manager provides a way todeclaratively define resources, but most of the configuration for a givenresource is defined by its API. For example, most of the configuration optionsfor the instance template resource are found in theinstance template resource definition in the reference documentation for theCompute Engine API.

The template is written using theJinja templating language. When writing Deployment Manager templates,you can either use Jinja or Python. Jinja has the advantage of being moredeclarative, which can be more readable and easier to understand than Python.For some complex deployments, the full expressiveness of Python might makethings simpler. In this case, Jinja is sufficient to create the necessaryresources.

In a template, certain environment variables are automatically set, and you canaccess these variables by using theenv dictionary. In this case, the name ofthe deployment is referenced as a name to be reused when assigning names to theresources that are created. For more information about available environmentvariables, seeUsing environment variables in the Deployment Manager documentation:

{%setNAME="bookshelf-"+env["deployment"]%}{%setSERVICE="bookshelf-"+env["deployment"]+"-frontend"%}

The template uses the same startup script that is used in theCompute Engine tutorial.The script's content is inserted into the template, and theJinja indent directive indents the content correctly:

value:|{{imports['startup-script']|indent(14, true)}}

In a Deployment Manager Jinja template, you can also refer toresources created elsewhere in the template. In the following example, thebackend service uses the reference of the managed instance group to obtain theinstance group it should point to:

-group:$(ref.{{ NAME }}-frontend-group.instanceGroup)zone: {{ properties['zone'] }}

Properties specified inconfig.yaml can be used in the template:

minNumReplicas: {{ properties['min-instances'] }}maxNumReplicas: {{ properties['max-instances'] }}loadBalancingUtilization:utilizationTarget: {{ properties['target-utilization'] }}