From legacy to cloud serverless - Part 4

Note: This article was originally published on Feb 5, 2024

Hello and welcome to this article in a journey of migrating a legacy-built app to the cloud. In this section, we will focus on three aspects: interfacing the application with Cloud Firestore, automating deployment, and exploring how Binary Authorization can reinforce supply chain security while aligning with security policies.

If you're joining us midway, I encourage you to take a look at the previous articles to get up to speed. Otherwise, let's dive in! 😊

integrating the app with Cloud Firestore

Our previous code interacted with MongoDB. With the migration to Google Cloud, we are transitioning away from MongoDB in favor of Firestore, which is Google Cloud's managed NoSQL document database built for automatic scaling, high performance, and ease of application development. To achieve this, we'll need to make modifications to our code, ensuring that our application seamlessly integrates and functions with Firestore.

We will replace the old MongoDB code with the following Firestore integration:

Old:

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from pymongo import MongoClient

from bson.objectid import ObjectId

import mongomock

...

if os.environ.get('TESTING'):

    client = mongomock.MongoClient()

else:

    client = MongoClient(os.environ['MONGO_URI'])

db = client.flask_db

todos = db.todos

New:

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from google.auth import compute_engine

from google.cloud import firestore

...

credentials = compute_engine.Credentials()

db = firestore.Client(credentials=credentials)

todos = db.collection('todos')

1. from google.auth import compute_engine: This line imports the compute_engine module from the google.auth library, which is used for authentication in Google Cloud environments




2. from library, enabling interaction with Google Cloud Firestore.




3. The compute_engine.Credentials() call retrieves the default credentials provided by Google Cloud in its environment. These credentials are essential for authenticating with Firestore. In a local or non-Google Cloud service environment, you would need to generate a service account key before being able to authenticate with Firestore. However, in our case, since the code will be deployed on Cloud Run, authentication will be handled using the default service account of Cloud Run.




4. todos = db.collection('todos'). Here, we're defining a Firestore collection. Collections are used to organize documents in Firestore.

Data Insertion: When a POST request is made, the new todo item is added to the Firestore collection 'todos' using the add method. The data is stored as a dictionary.

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@app.route('/', methods=['GET', 'POST'])

def index():

    if request.method == 'POST':

        content = request.form.get('content')

        degree = request.form.get('degree')

        todos.add({'content': content, 'degree': degree})

Old:

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todos.insert_one({'content': content, 'degree': degree})

New:

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todos.add({'content': content, 'degree': degree})

This modification reflects the adjustment needed in the code for Firestore, moving from the insert_one method in MongoDB to the add method in Firestore for adding documents.

Data Retrieval: In the new code, we utilize () to iterate over documents and convert them to a dictionary format for retrieval. The '_id' field represents the document ID in Firestore.

Data Deletion: In the new code, we employ todos.document(id).delete() to remove a document from the Firestore collection. In the old code, we used todos.delete_one({"_id": ObjectId(id)}) to delete a document from the MongoDB collection.

Old:

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todos.delete_one({"_id": ObjectId(id)})

New:

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todos.document(id).delete()

The todos.document(id).delete() method is used to delete a specific document by its ID in Firestore.

After all these updates, the new ()), and deletion (todos.document(id).delete()), along with integrating the appropriate syntax for Firestore operations.

Testing the new code

To ensure the correctness of the new '': Specifies the Docker image to be used for this step, which, in this case, is the Google Cloud SDK image.

entrypoint: 'gcloud': Sets the Docker entrypoint to 'gcloud,' the command-line interface for Google Cloud Platform.

args: A list of arguments passed to the 'gcloud' command.

• 
  'run' 'deploy' '$_SERVICE_NAME': Deploys a new revision of the Cloud Run service identified by $_SERVICE_NAME.


• 
  '--image' '$_ for the setup of Binary Authorization."
  
  
  

  This concludes the article. Thank you for reading. You can find the configurations and code for this project in the following Git repository.

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