Day 5 of The Cloud Boot Camp MultiCloud | DevOps | AI challenge has wrapped. The challnge wrapped up incorporating the BigQuery Real-Time Analytics from Google Cloud Platform (GCP) and Azure AI Language for Sentiment Analysis. These services allowes tracking of language used in the AI Agent to visualize sentiment data.

Today’s steps:

  1. To start new front and backend code needed to be deployed
    • Frontend was quick to deploy with the pipeline setup on Day 3
    • The backend needed to be deployed manually This is on the ToDo List after the Challenge
  2. Setup the BigQuery API in GPC
    • Enable APIs and Services
    • Created a Data Set in BigQuery
    • Created a table named “cloudmart-orders”
      • Schema: 
            - id: STRING
    - items: JSON
    - userEmail: STRING
    - total: FLOAT
    - status: STRING
    - createdAt: TIMESTAMP
    • Configured Lambda function
  3. Created more DynamoDB tables in AWS using Terraform
    • updated current Terraform file to keep state and everything together
  4. Created Azure Text Analytics
    • In Azure console created new resource for Text Aanlytics
  5. Added the Azure Endpoint and API Key to the backend yaml configuration file and redeployed backend 
    kubectl apply -f cloudmart-backend.yaml

Overall a successful 5 day challenge. I had a lot of fun and I see doing a lot more of these in teh future. Thank You to everyone at The Cloud Bootcamp for putting together this challenge I had a lot of fun running through the “real-world” type scenario.

Challenge Certificate