AIP-C01 Study Hub
Implementation Week 2 · Wednesday

Day 10: Integration Patterns + CI/CD + Q Business/Developer

Learning Objectives

  • - Distinguish Q Business (enterprise internal search) from Q Developer (coding assistant)
  • - Design CI/CD pipelines for GenAI applications with Bedrock Evaluations
  • - Understand Bedrock Flows as a no-code workflow builder
  • - Know Q Business 40+ connectors and ACL-respecting retrieval
  • - Apply GenAIOps principles for scaling GenAI workloads

Tasks

Tasks

0/5 completed
  • Read30m

    Amazon Bedrock Flows Documentation

    No-code workflow builder for sequential prompt chains with conditional branching.

  • Read30m

    Amazon Q Business Documentation

    Enterprise internal search, 40+ connectors, built-in ACL, provided UI.

  • Read20m

    Amazon Q Developer Documentation

    Code generation, completion, security scanning, /transform for Java upgrades.

  • Blog25m

    GenAIOps - Operationalizing GenAI at Scale

    Standardized repos, reusable components, automated evaluation at scale.

  • Hands-on45m

    AWS GenAI CI/CD Suite (GitHub Actions + Bedrock Code Review)

    Explore the CI/CD integration patterns for GenAI applications.

Exam Skills

Write your understanding, then reveal the reference answer.

0/6 reviewed

Hands-On Lab

Build real muscle memory with these activities.

intermediate 45 min

Configure Q Business with an S3 Data Source

Set up Amazon Q Business with S3 documents to create an enterprise search assistant.

  1. 1 Open Amazon Q Business console and click 'Create application'
  2. 2 Name the application and configure IAM Identity Center for user access
  3. 3 Add an S3 data source and point it to a bucket containing company documents
  4. 4 Configure the sync schedule and start the initial sync
  5. 5 Open the Q Business web experience and test queries against your documents
Open Lab
beginner 30 min

Explore Q Developer Code Generation Features

Use Q Developer in your IDE to test code generation, completion, and security scanning.

  1. 1 Install the Amazon Q extension in VS Code or JetBrains IDE
  2. 2 Open a Python file and type a comment: '# Function to invoke Bedrock Claude with streaming'
  3. 3 Accept the auto-generated code suggestion
  4. 4 Open Q Developer chat and ask: 'Write a Lambda handler that calls Bedrock InvokeModel'
  5. 5 Run Q Developer security scan on the generated code to check for vulnerabilities
Open Lab

Scenarios

Think through each scenario before revealing the answer.

D2: ImplementationMedium
#10

CI/CD Pipeline for Prompt Quality

A development team wants to automatically test prompt quality before deploying prompt changes to production. They use CodePipeline for CI/CD. Design the pipeline.
Think First
  • Where are prompt templates stored as code?
  • Which service runs automated evaluations against test datasets?
  • What happens if evaluation scores are below threshold?

Practice Questions

10 questions across 3 difficulty levels.

Further Reading

Go deeper into today's topics.