dc dotCreds
Microsoft AI-200 Practice Test

Microsoft AI-200 Practice Test

Start today’s free 10-question Microsoft AI-200 set with source-backed explanations, local progress, and a fresh rotation every morning.

10 Free Daily Questions Source-backed Explanations 200 Verified Questions

Questions updated at Aug 22, 2026, 8:53 PM CDT

Go Pro - One Time Unlock

Unlock the full AI-200 bank

200 verified questions Exam Mode Practice Mode Detailed explanations Weak-area review No subscription - one-time unlock

Get the complete source-backed bank with Interview Questions, the full Study Guide, full Course Notes, detailed explanations, weak-area review, and exam-style practice.

Interview Questions Full Study Guide Full Course Notes Exam Mode Practice Mode Guided Course Detailed explanations Weak-area review No subscription
$4.99 One-time payment
See bundle and PDF options

We will confirm your site email in one quick checkout step.

Why DotCreds?

Practice with explanations that teach.

Source links for every answer Every wrong answer explained Guided Course included Practice and Exam Mode Weak-area tracking Same verified bank across web practice

What you get with free practice

10 Free Questions Daily Fresh set every day from the live bank
Detailed Explanations Learn with clear source-backed answers
Track Your Progress Daily history and performance insights
Upgrade Anytime Unlock the full bank when you are ready
Today's 10 Microsoft AI-200 questions

Use this Microsoft AI-200 practice test to review Microsoft AI-200. Questions rotate daily and each answer links back to the source used to write it.

Today’s Set
10 questions
Rotates at 10:00 AM local time
Progress
0/10
Answered on this page
Accuracy
0%
Loading countdown…

200 verified questions are in the live bank. Free daily questions are selected from a rotating sample set. Unlock Pro to access the full question bank.

Preparing today’s free questions... Ordering the final locked-bank set before showing the practice cards.
Question 1 of 10
Objective Monitor and troubleshoot Azure solutions Secure, monitor, and troubleshoot Azure solutions (20%-25%)

A legacy log column contains text such as model=gpt-x;tokens=420;status=ok, and analysts need tokens as a queryable field. Which KQL approach is designed to extract structured values from the text pattern?

Concept tested:
Question 2 of 10
Objective Develop AI solutions by using Azure Cosmos DB for NoSQL Develop AI solutions by using Azure data management services (25%-30%)

A proposed partition key is currentMonth for a workload that writes almost all data to the current month. What risk should be identified?

Concept tested:
Question 3 of 10
Objective Develop event- and message-based AI solutions Connect to and consume Azure services (20%-25%)

Operations wants to intentionally remove a message from normal delivery while recording a diagnostic reason for manual review. Which settlement action is appropriate?

Concept tested:
Question 4 of 10
Objective Implement container application hosting Develop containerized solutions on Azure (20%-25%)

A custom container restarts frequently but the image tag still resolves to the same manifest. Why are subsequent starts normally faster than the first pull on the same worker?

Concept tested:
Question 5 of 10
Objective Implement secure Azure solutions Secure, monitor, and troubleshoot Azure solutions (20%-25%)

One application uses the same configuration key name in development and production but needs different values in each environment. Which App Configuration feature should distinguish them cleanly?

Concept tested:
Question 6 of 10
Objective Implement container-orchestrated solutions Develop containerized solutions on Azure (20%-25%)

An engineer changes the container image and a scale rule in properties.template. What should be expected?

Concept tested:
Question 7 of 10
Objective Develop AI solutions by using Azure Database for PostgreSQL Develop AI solutions by using Azure data management services (25%-30%)

A latency-critical HNSW endpoint is over-searching and can tolerate somewhat lower recall. Which tuning direction is consistent with that tradeoff?

Concept tested:
Question 8 of 10
Objective Develop and implement Azure Functions Connect to and consume Azure services (20%-25%)

A function app runs from a package stored in private Blob Storage. Security policy prohibits embedding a long-lived SAS token in configuration. What authentication approach should be used?

Concept tested:
Question 9 of 10
Objective Implement container application hosting Develop containerized solutions on Azure (20%-25%)

A registry resource already has a CanNotDelete Azure resource lock, but engineers can still overwrite an image tag. Why?

Concept tested:
Question 10 of 10
Objective Integrate Azure Managed Redis in AI solutions Develop AI solutions by using Azure data management services (25%-30%)

A conventional disposable cache sets TTLs on all entries and wants least-recently-used expired candidates removed under pressure. Which family of policy fits better than noeviction?

Concept tested:
Locked preview

You are viewing today’s free 10. Unlock 190 more questions.

Unlock full bank
Daily sample Rotating practice Free daily questions are selected from a rotating sample set.
Pro bank Full access Unlock Pro to access the full question bank, Exam Mode, Practice Mode, and random tests.
AI-200 Pro $4.99 one-time

Best if you only need this one certification.

50 Exam Practice Test $1.99 one-time

A 50-question AI-200 PDF for short review sessions. Questions come first, then the answer review and explanations later in the file.

Microsoft Access $6.99/month

Unlock Microsoft, Azure, Power Platform, Copilot, and AI practice exams.

Why it fitsUnlock Microsoft, Azure, Power Platform, Copilot, and AI practice exams, Includes MS-700 Managing Microsoft Teams, Includes current and future Microsoft practice banks on dotCreds, Best for learners taking more than one Microsoft exam, PDF downloads sold separately where available

Choose an unlock option to continue. We will confirm your site email in one quick checkout step.

Secure checkout powered by Stripe. Source-backed questions. Not brain dumps. Checkout stays on this page and unlocks the same Pro builder on this practice page.

Purchase options

Unlock the full AI-200 bank.

Get the full bank, Exam Mode, Practice Mode, question sets, random tests, readiness tracking, saved box scores, and review tools for this exam.

The PDF versions keep questions first and move the answer review, explanations, and distractor notes to the back of the file.

200 verified exam-style questions Every choice explained Exam Mode and Practice Mode Question sets and random tests Readiness score and trends Previous test box scores

You've answered 0/10 questions in today's set.

Locked: 190 more questions in the full bank.

Locked: exam simulation mode, practice mode, readiness tracking, and saved review history.

Checkout stays on this page, so you can keep practicing, unlock the full bank, and start Exam Mode or Practice Mode when you are ready.

Cheat Sheets

7-day score keeper

Answer questions today and this will become a rolling 7-day scorecard.

Local history
Optional progress sync

Keep today’s practice moving

Guest progress saves automatically on this device. Add an email later when you want a magic link that keeps your daily AI-200 practice in sync across browsers.

Guest progress saves on this device automatically

Guest progress is available without an account.

Source-backed answer review

The free daily Microsoft AI-200 set includes crawlable question text, answer choices, correct answer labels, objective mapping, and source links. Only the first SEO card includes answer explanations and any extra learning features. Pro-only bank questions stay locked; this section mirrors only the 10 free daily questions already shown on this page.

Question 1 A legacy log column contains text such as model=gpt-x;tokens=420;status=ok, and analysts need tokens as a queryable field. Which KQL approach is designed to extract structured values from the text pattern?

Answer choices

  1. A. Use arg_max to parse tokens.
  2. B. Use union to split a string into fields.
  3. C. Use summarize before extracting the value.
  4. D. Use parse or an appropriate extraction function to derive structured columns from the text.

Correct answer

Use parse or an appropriate extraction function to derive structured columns from the text.

KQL parsing and extraction operators/functions can turn structured patterns embedded in text into separate queryable columns. Therefore, use parse or an appropriate extraction function to derive structured columns from the text.

Wrong-answer review

  • A. Use arg_max to parse tokens.: Use arg_max to parse tokens. can be valid in a different design, but it does not satisfy the decisive requirement in this scenario. KQL parsing and extraction operators/functions can turn structured patterns embedded in text into separate queryable columns.
  • B. Use union to split a string into fields.: Use union to split a string into fields. can be valid in a different design, but it does not satisfy the decisive requirement in this scenario. KQL parsing and extraction operators/functions can turn structured patterns embedded in text into separate queryable columns.
  • C. Use summarize before extracting the value.: Use summarize before extracting the value. can be valid in a different design, but it does not satisfy the decisive requirement in this scenario. KQL parsing and extraction operators/functions can turn structured patterns embedded in text into separate queryable columns.

Extra learning features

Why candidates miss this

The ‘arg_max’ choice is tempting because it’s a common function for data manipulation. However, it doesn’t directly address the requirement of extracting structured values from the text pattern. The decisive clue is the need for a function specifically designed for parsing and transforming text data into a structured format, which KQL provides. Likely wrong answer: Use arg_max to parse tokens. Review focus: Learn common Kusto Query Language operators

Interview question

Q: KQL parsing and extraction operators/functions can turn structured patterns embedded in text into separate queryable columns. Strong answer: KQL parsing and extraction operators/functions can turn structured patterns embedded in text into separate queryable columns.

  • KQL parsing and extraction operators/functions can turn structured patterns embedded in text into separate queryable columns.
  • arg_max
  • union
  • summarize

Caution: Do not restate the multiple-choice stem or ask the learner merely to name a product, rule, or term.

Objective/domain: Secure, monitor, and troubleshoot Azure solutions (20%-25%)

Source: Learn common Kusto Query Language operators

Question 2 A proposed partition key is currentMonth for a workload that writes almost all data to the current month. What risk should be identified?

Answer choices

  1. A. The key disables indexing on all other properties.
  2. B. The active month can become a hot logical partition because most writes share one partition-key value.
  3. C. The key guarantees even distribution because dates are sortable.
  4. D. The key forces Strong consistency.

Correct answer

The active month can become a hot logical partition because most writes share one partition-key value.

Objective/domain: Develop AI solutions by using Azure data management services (25%-30%)

Source: Partitioning and horizontal scaling in Azure Cosmos DB

Question 3 Operations wants to intentionally remove a message from normal delivery while recording a diagnostic reason for manual review. Which settlement action is appropriate?

Answer choices

  1. A. ReceiveAndDelete it and then try to recover it.
  2. B. Dead-letter the message explicitly with a reason/description.
  3. C. Defer it without preserving its sequence number.
  4. D. Complete it successfully.

Correct answer

Dead-letter the message explicitly with a reason/description.

Objective/domain: Connect to and consume Azure services (20%-25%)

Source: Service Bus dead-letter queues

Question 4 A custom container restarts frequently but the image tag still resolves to the same manifest. Why are subsequent starts normally faster than the first pull on the same worker?

Answer choices

  1. A. App Service converts the image into a Functions ZIP package after first start.
  2. B. The container stops checking ACR after the first successful deployment.
  3. C. ACR permanently pushes all layers into the web app content share.
  4. D. App Service retains image layers on local disk and pulls only changed layers when the image is fetched again.

Correct answer

App Service retains image layers on local disk and pulls only changed layers when the image is fetched again.

Objective/domain: Develop containerized solutions on Azure (20%-25%)

Source: Configure a custom container for Azure App Service

Question 5 One application uses the same configuration key name in development and production but needs different values in each environment. Which App Configuration feature should distinguish them cleanly?

Answer choices

  1. A. Use Service Bus sessions as configuration labels.
  2. B. Create a new Key Vault for every nonsecret setting.
  3. C. Use labels to store environment-specific variants of the same key.
  4. D. Encode the environment into the application binary.

Correct answer

Use labels to store environment-specific variants of the same key.

Objective/domain: Secure, monitor, and troubleshoot Azure solutions (20%-25%)

Source: What is Azure App Configuration?

Question 6 An engineer changes the container image and a scale rule in properties.template. What should be expected?

Answer choices

  1. A. A new revision is created because template changes are revision-scope.
  2. B. Only the running replica count changes; no revision is created.
  3. C. The existing revision is modified in place while remaining immutable.
  4. D. The change affects only the Container Apps environment, not the app.

Correct answer

A new revision is created because template changes are revision-scope.

Objective/domain: Develop containerized solutions on Azure (20%-25%)

Source: Update and deploy changes in Azure Container Apps

Question 7 A latency-critical HNSW endpoint is over-searching and can tolerate somewhat lower recall. Which tuning direction is consistent with that tradeoff?

Answer choices

  1. A. Set IVFFlat lists equal to zero.
  2. B. Rebuild the index as a B-tree.
  3. C. Increase ef_search indefinitely.
  4. D. Reduce hnsw.ef_search after validating recall remains acceptable.

Correct answer

Reduce hnsw.ef_search after validating recall remains acceptable.

Objective/domain: Develop AI solutions by using Azure data management services (25%-30%)

Source: Optimize performance when using pgvector in Azure Database for PostgreSQL

Question 8 A function app runs from a package stored in private Blob Storage. Security policy prohibits embedding a long-lived SAS token in configuration. What authentication approach should be used?

Answer choices

  1. A. Put the package bytes in Azure App Configuration.
  2. B. Make the package container public.
  3. C. Grant the function app managed identity access to the package blob and use identity-based access where supported.
  4. D. Embed a storage account key directly in source code.

Correct answer

Grant the function app managed identity access to the package blob and use identity-based access where supported.

Objective/domain: Connect to and consume Azure services (20%-25%)

Source: Run your functions from a package file in Azure

Question 9 A registry resource already has a CanNotDelete Azure resource lock, but engineers can still overwrite an image tag. Why?

Answer choices

  1. A. The lock applies only after geo-replication is enabled.
  2. B. The resource lock protects registry management operations; image data needs repository/image-level protection such as locking or appropriate permissions.
  3. C. A CanNotDelete lock disables image pulls but not pushes.
  4. D. Tags in ACR are always immutable regardless of permissions.

Correct answer

The resource lock protects registry management operations; image data needs repository/image-level protection such as locking or appropriate permissions.

Objective/domain: Develop containerized solutions on Azure (20%-25%)

Source: Lock container images in Azure Container Registry

Question 10 A conventional disposable cache sets TTLs on all entries and wants least-recently-used expired candidates removed under pressure. Which family of policy fits better than noeviction?

Answer choices

  1. A. Use noeviction if the explicit goal is to free memory automatically.
  2. B. Use vector KNN distance as the eviction score.
  3. C. Disable all expirations and rely on infinite memory.
  4. D. Use an LRU-based eviction policy appropriate to whether all keys or only TTL-bearing keys may be evicted.

Correct answer

Use an LRU-based eviction policy appropriate to whether all keys or only TTL-bearing keys may be evicted.

Objective/domain: Develop AI solutions by using Azure data management services (25%-30%)

Source: Caching guidance

Where to go after the daily web set

How are Microsoft AI-200 questions generated?

dotCreds builds Microsoft AI-200 practice questions from public exam objectives and Microsoft Learn and exam-objective references. The questions are written for realistic study practice, not copied from exam dumps.

How are explanations sourced?

Each question includes an explanation and, when available, a source link back to the provider documentation or reference used to validate the answer. That keeps the practice tied to study material you can actually review.

What score do I get?

The page tracks today's answered count and accuracy for the 10-question daily set, then saves a 7-day score history on this device so you can see your recent practice trend.

Why use this site?

The site is the fastest way to start Microsoft AI-200 practice without installing anything. It is built for daily recall, quick weak-topic discovery, and source-backed explanations you can review immediately.