Deploy to Cloud and Migrate to Cloud-Based Datastore

[Rich-T-kid]

Objective

Deploy the scraper to a real cloud server (AWS or Google Cloud) to ensure it works in a production environment. Migrate to a cloud-based database for persistent storage and link traversal tracking.

Tasks

1. Cloud Deployment:

   • Deploy the scraper to a cloud server (e.g., AWS EC2, Google Cloud Compute Engine).
   • Test the scraper's performance and functionality in a cloud environment.

2. Database Migration:

   • Migrate the local database to a cloud-based datastore (e.g., AWS RDS, Google Cloud SQL, or Firestore).
   • Ensure all data (e.g., scraped links, traversed link tracking) is correctly stored in the new cloud database.

3. Link Traversal Tracking:

   • Integrate a caching mechanism (e.g., Redis or a cloud-based equivalent) to check if links have already been traversed.
   • Ensure this mechanism is efficient and scalable for large datasets.

4. Testing:

   • Test the scraper end-to-end in the cloud environment, including database integration and link traversal tracking.
   • Fix any issues encountered during deployment or migration.

5. Documentation:

   • Document the deployment process for AWS/Google Cloud.
   • Provide instructions for managing the cloud database and scaling the scraper.

Acceptance Criteria

• The scraper is deployed to a cloud server and works without issues in a production environment.
• Data is successfully migrated to a cloud-based database, and all interactions work as intended.
• Link traversal tracking is functional and scalable in the cloud setup.
• Documentation is complete and easy to follow.

Additional Notes

• Use Terraform or similar tools for infrastructure as code to simplify deployment and future scaling.
• Optimize the cloud environment for cost-effectiveness while maintaining performance.