AI-200 Data Management Services And Vector Search Practice Question
When configuring vector search in Azure Cosmos DB for NoSQL, which TWO steps are required to prepare a container for vector search before inserting documents? (Choose two)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Define the vectorEmbeddingPolicy at container creation or update
Preparing a Cosmos DB container for vector search requires adding a vector embedding policy and defining vector indexes in the indexing policy.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Define the vectorEmbeddingPolicy at container creation or update
Why this is correct
The vector embedding policy defines paths, dimensions, data types, and distance functions.
- ✓
Define vectorIndexes within the indexingPolicy
Why this is correct
Vector indexes are required in the indexing policy to enable vector queries.
- ✗
Mount an NFS network share for vector file storage
Why it's wrong here
Cosmos DB manages its own storage internally.
- ✗
Install the pgvector extension on the container
Why it's wrong here
pgvector is for PostgreSQL, not Azure Cosmos DB.
- ✗
Create a relational foreign key constraint to Azure SQL
Why it's wrong here
Cosmos DB is a NoSQL database and does not use relational foreign keys.
About these practice questions
One of 503 original AI-200 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-200 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-200 exam.