Study guide · Flashcards & memory notes

Azure AI Cloud Developer Flashcards & Memory Notes

40 recall cards for the distinctions AI-200 keeps testing: where the container runs, how vectors and caches serve the app, how messages and Functions connect it, and which signal names the fault.

Exam: AI-2004 decks · 40 cardsNo sign-up required

How to use these cards: Say the answer out loud before you flip the card, and mark it honestly. Revisit the cards you missed tomorrow rather than rereading them right away. Progress is kept only while this page is open. For the full explanations behind each card, see the core notes.

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Deck 1 · Containers

ACR, App Service containers, Container Apps, AKS, and troubleshooting.

10 cards
1.1What does Azure Container Registry store?

Container images and tags. A host such as App Service, Container Apps, or AKS must pull and run the image.

1.2What can ACR Tasks rebuild automatically?

Application images when a base image updates or on a schedule. That keeps patched bases from waiting on a manual push.

1.3When do you choose Azure Container Apps?

When you want revisions, environments, and KEDA scaling without managing Kubernetes nodes. AKS is the full Kubernetes path.

1.4What is a Container Apps revision?

An immutable deployment of the app. You can split traffic across revisions and roll back by shifting weight.

1.5What does KEDA scale on?

Event sources such as HTTP load or queue depth. Replica count can drop when idle according to the rules you set.

1.6When do you choose AKS instead of Container Apps?

When you need full Kubernetes manifests, custom controllers, or cluster-level troubleshooting. Container Apps abstracts that control plane.

1.7Where should container secrets live?

Outside the image, in Key Vault references or secret app settings. Do not bake passwords into layers.

1.8What should you read first when an AKS pod restarts?

Pod logs and Kubernetes events. Then check connectivity before resizing the node pool.

1.9What does ImagePullBackOff usually mean?

A pull problem: authentication, tag name, or network path to the registry. It is not a Cosmos RU issue.

1.10How does App Service fit containers on AI-200?

It hosts a web or API container with platform scaling without writing Kubernetes YAML. ACR still stores the image.

Deck 2 · Data for AI

Cosmos DB, PostgreSQL with pgvector, Redis, RAG, and change feed.

10 cards
2.1When do you choose Cosmos DB for NoSQL for AI data?

Documents plus vector similarity search, with RU and consistency awareness, and change feed for processors.

2.2What do request units measure?

The throughput cost of Cosmos reads and writes. Broader queries and stronger consistency cost more.

2.3What does the Cosmos change feed provide?

A stream of inserts and updates for downstream processors without polling the whole container.

2.4When do you choose Azure Database for PostgreSQL?

Relational schemas, SQL joins, and pgvector similarity with metadata filters for RAG.

2.5What does pgvector add?

Embedding storage and vector similarity search inside PostgreSQL. Pair it with filters for tenancy or document type.

2.6Why filter metadata in a RAG query?

To keep the wrong tenant or document type out of the prompt context. Similarity alone is not enough.

2.7What is Azure Managed Redis for on this exam?

Caching with expiration and invalidation, plus optional vector indexing for low-latency lookups.

2.8What is the difference between cache expiration and invalidation?

Expiration removes a key after a TTL. Invalidation deletes or refreshes it when the source data changes.

2.9Why size PostgreSQL memory for vectors?

Vector indexes and similarity queries are memory sensitive. Under-provisioned memory shows up as slow retrieval.

2.10Cosmos versus Redis for documents?

Cosmos is a durable document store. Redis is the hot cache, not the only system of record.

Deck 3 · Messaging and Functions

Service Bus, Event Grid, triggers, bindings, and DLQ.

10 cards
3.1When do you choose a Service Bus queue?

When one competing consumer path should pull durable work later. A topic fans out to subscriptions.

3.2When do you choose a Service Bus topic?

When one publish must reach many subscriptions, optionally filtered. Each handler gets its own copy path.

3.3What is the dead-letter queue for?

Messages that exceed max delivery attempts or are dead-lettered for inspection. Fix the consumer, then reprocess or dispose.

3.4What does Event Grid add?

Filtered delivery of Azure or custom events to handlers, with retries. Plan a dead-letter path when handlers stay down.

3.5What starts an Azure Function?

A trigger such as HTTP, Service Bus, Event Grid, or timer.

3.6What do bindings provide?

Declarative inputs and outputs to other services so you write less glue code. Authorization still matters.

3.7Queue versus Event Grid?

Queues hold a backlog for competing consumers. Event Grid routes filtered events; use Service Bus when you need DLQ and competing pull semantics.

3.8Where should Function secrets live?

In Key Vault or app setting references, not in the deployment package.

3.9What does an HTTP-triggered Function enable?

A serverless API without a long-lived host you manage. Configure and deploy the function app for repeatable releases.

3.10What happens if peek-lock expires mid-processing?

Another consumer may receive the same message. Make handling idempotent or adjust lock duration.

Deck 4 · Security and monitoring

Key Vault, App Configuration, OpenTelemetry, and KQL.

10 cards
4.1Key Vault versus App Configuration?

Key Vault stores secrets with rotation and retrieval. App Configuration stores non-secret settings and feature flags.

4.2Where does a database password belong?

In Key Vault, retrieved at runtime, often with managed identity. Not in App Configuration or the image.

4.3What does secret rotation require of the app?

It must retrieve the current version and refresh so old credentials stop working.

4.4When do you use App Configuration feature flags?

When behavior must change without rebuilding the container image. The app still needs a refresh strategy.

4.5What do OpenTelemetry SDKs create?

Distributed traces with spans across services so you can see which hop is slow or failing.

4.6Trace versus KQL log query?

A trace follows one request across services. KQL aggregates logs or metrics over a time window.

4.7How should a container authenticate to Key Vault?

With managed identity and least-privilege access on the vault, not a long-lived client secret in the image.

4.8What should a KQL investigation usually filter first?

Time range and the relevant resources or tables, then severity, operation id, or custom dimensions.

4.9Why propagate trace context?

So one request id links Container Apps, Functions, and downstream calls in a single distributed trace.

4.10App Configuration holds a password. What is wrong?

Passwords are secrets and belong in Key Vault. App Configuration is for non-secret settings and flags.

Memory notes

Groupings that make the highest-yield AI-200 distinctions easier to recall.

Store, revise, orchestrate

  • ACR stores the image
  • App Service simple web container
  • Container Apps revisions and KEDA
  • AKS full manifests

Documents, SQL, cache

Cosmos DB holds documents, vectors, and change feed. PostgreSQL with pgvector fits SQL joins and metadata filters. Redis is the hot cache with TTL and invalidation, not the only durable store.

Queue, topic, event, function

  • Queue competing consumers
  • Topic fan-out subscriptions
  • Event Grid filtered events and retries
  • Functions triggers start; bindings inject

Secret versus setting

Key Vault stores and rotates secrets. App Configuration holds feature flags and non-secret settings. Managed identity retrieves Key Vault values at runtime.

Path versus count

OpenTelemetry traces follow one request across services. KQL queries logs and metrics over a time window. Use the trace to name the slow hop, then KQL to count how often it happens.

AZ-204 to AI-200

AZ-204 retired on July 31, 2026. AI-200 is the current Azure developer associate path, with stronger weight on containers, vector data stores, messaging, Functions, Key Vault, App Configuration, OpenTelemetry, and KQL.

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Overview

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Core Notes

Reference notes for containers, data for AI, messaging, Functions, security, and observability.

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Flashcards & Memory Notes

40 recall cards in four decks, plus memory notes for containers, vectors, messaging, and secrets.

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