Adobe AD0-E104 Exam Prep Course (Premium File)
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Last updated on May 15, 2026

 AD0-E104 Practice Exam
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Last Updated: 15-May-2026
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All Adobe Experience Manager Architect certification learning material, study guide, training courses are created by a team of Adobe training experts. The Study Guide and .EXM training software files contain relevant Adobe Experience Manager Architect content, labs, practice questions and explanation. This AD0-E104 exam guide and training courses is based on the latest exam outlines available!

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The AD0-E104 Exam Prep Features:

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How to Prepare and Pass the Adobe AD0-E104 Exam

Are you interested in becoming an Adobe Certified Expert? The Adobe AD0-E104 Exam is a crucial step towards achieving that goal. In this article, we will provide you with all the necessary information about the AD0-E104 exam, including its content, preparation tips, and actionable strategies to help you pass with flying colors.

About the AD0-E104 Exam

The AD0-E104 exam, also known as the "Adobe Experience Manager Sites Architect" exam, is designed to test your knowledge and skills in architecting Adobe Experience Manager (AEM) solutions. This exam is targeted towards professionals who have a deep understanding of AEM architecture and its components, and who can design and implement AEM solutions that meet specific business requirements.

The exam consists of multiple-choice and multiple-select questions, and you will have a specific time limit to complete it. To pass the exam, you need to achieve a minimum passing score determined by Adobe. It is important to note that the exam content and passing score may be subject to change, so always refer to the official Adobe website for the most up-to-date information.

Exam Preparation Tips

Proper preparation is key to success in any exam, and the AD0-E104 exam is no exception. Here are some actionable tips to help you prepare effectively:

  1. Understand the Exam Objectives: Familiarize yourself with the exam objectives outlined by Adobe. This will give you a clear understanding of what topics and skills will be covered in the exam.
  2. Review Official Adobe Documentation: Adobe provides comprehensive documentation on Adobe Experience Manager. Study the official documentation, paying close attention to topics related to architecture, implementation, and best practices.
  3. Take Training Courses: Adobe offers training courses specifically designed for the AD0-E104 exam. Enroll in these courses to gain in-depth knowledge and hands-on experience with Adobe Experience Manager.
  4. Practice with Sample Questions: Practice makes perfect. Use sample questions and practice tests provided by Adobe to familiarize yourself with the exam format and assess your knowledge and readiness.
  5. Join Online Communities: Engage with fellow professionals and experts in online communities or forums dedicated to Adobe Experience Manager. Participating in discussions and asking questions can provide valuable insights and clarification on challenging topics.
  6. Hands-on Experience: Gain practical experience by working on real-world projects using Adobe Experience Manager. This will not only reinforce your understanding but also enhance your problem-solving skills.
  7. Manage Your Time: Develop a study schedule and allocate dedicated time for exam preparation. Be consistent and disciplined in your approach to cover all the necessary topics effectively.
  8. Stay Updated: Keep up with the latest updates and changes related to Adobe Experience Manager. Follow Adobe's official blogs, forums, and social media channels to stay informed about new features, enhancements, and best practices.

Conclusion

Preparing for and passing the Adobe AD0-E104 Exam requires a combination of knowledge, hands-on experience, and dedicated preparation. By following the tips provided in this article, you can enhance your chances of success and demonstrate your expertise in architecting Adobe Experience Manager solutions. Remember to regularly visit the official Adobe website for the most accurate and up-to-date information regarding the exam.

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Question 86:

  • Correct answer: Vertical scaling

  • Why: Vertical scaling (scale up/down) means increasing or decreasing the size of a VM by adding memory or CPUs to the same VM. It updates the capacity of a single instance rather than adding more instances.

  • How it compares to other terms:
- Horizontal scaling (scale out/in): changes the number of VM instances, not the size of each one. - Elasticity: broad concept of adapting resources to demand (includes vertical and horizontal scaling). - Agility: general capability; not specific to VM capacity.
  • Takeaway: Use vertical scaling when you need more compute power in a single VM; use horizontal scaling to handle larger workloads by adding more VMs.

Rudolfstetten, Switzerland

VirtuLearn AI

Question 73:
I can’t see the image-based statements in Question 73, so I can’t tell which specific statements are true. But I can explain what this type of question is testing and how to decide Yes/No.
What Question 73 is testing

  • Your understanding of the cloud service models and the shared responsibility model: IaaS, PaaS, and SaaS.
  • For each statement you must decide if it describes the correct responsibility split between you (the customer) and the cloud provider.

Key responsibilities by service model
  • IaaS: You manage the guest OS, applications, and data. The provider manages virtualization, servers, storage, and networking.
  • PaaS: You manage the applications and data. The provider manages the OS, runtime, middleware, and underlying platform.
  • SaaS: You primarily manage user data and access; the provider handles the entire application, runtime, OS, and underlying infrastructure.

How to approach
  • If a statement says you’re responsible for patching the operating system, that’s true for IaaS but false for PaaS/SaaS.
  • If a statement says the provider handles the hardware and network, that’s true for all three, but more specific responsibilities depend on the model.

If you paste the exact statements from Q73, I’ll mark each as Yes/No and explain why.

Rudolfstetten, Switzerland

VirtuLearn AI

Question 25:

  • Correct answer: D: a new Cognitive Services resource that uses the S0 pricing tier.

  • Why: To enable OCR and text analytics in a Cognitive Search enrichment pipeline, you must attach a Cognitive Services resource to the skillset. For cost efficiency on a large document set, choose the base standard tier (S0) rather than higher tiers or a free tier, which may limit enrichments. The OCR capability comes from the Cognitive Services (Computer Vision/Read) and the S0 tier provides a balance of capability and cost.

Singapore, Singapore

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Question 20:

  • Correct answer: D and E.

  • Why: Provisioning a QnA Maker service creates:
- Azure App Service to host the QnA Maker web API (your App Service Plan AP1 will host the App Service resource). - Azure Cognitive Search to enable fast search over the knowledge base.
  • Why not the others:
- Language Understanding, Azure SQL Database, and Azure Storage are not automatically created by QnA Maker provisioning.
  • Quick note: After provisioning, check RG1 to verify the new App Service and Cognitive Search resources.

Singapore, Singapore

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what if different between speech recognizer and speach synthesizer

  • Speech Recognizer (Speech-to-Text): Converts audio input (live mic or audio file) into text. Output is transcripts with timestamps, confidence scores, and optional punctuation. Use cases: meeting transcripts, voice commands, real-time captions.

  • Speech Synthesizer (Text-to-Speech): Converts text (or SSML) into audio output. Output is audio data (wav/mp3 or streaming). Use cases: voice prompts, IVR responses, accessibility narrations. You can choose voices, languages, and adjust prosody (rate, pitch, volume).

  • Key differences:
- Input: Recognizer takes audio; Synthesizer takes text/SSML. - Output: Recognizer ? text; Synthesizer ? audio. - Features: Recognizer provides transcripts and timing; Synthesizer provides customizable voices (neural, SSML), multiple languages. - Typical scenarios: Transcription vs. generating spoken content.
  • Quick example: Use Speech Recognizer to transcribe a meeting; use Speech Synthesizer to read a script aloud in a chosen voice.

Singapore, Singapore

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Question 17:

  • Correct answer: A Anomaly Detector.

  • Why: Anomaly Detector is designed to identify unusual values in time-series data. Your scenario has 100 machines × 50 sensors, generating minute-by-minute data, totaling 5,000 time-series. Anomaly Detector can process each time-series (or batches of series) to flag deviations that may indicate potential failures, which is exactly what you need for predictive maintenance.

  • Why not the others:
- Cognitive Search is for indexing and querying content, not for detecting anomalies in time-series data. - Form Recognizer extracts data from forms, not time-series sensor data. - Custom Vision analyzes images, not numeric sensor streams.
  • Practical note: with 5,000 time series, you’d typically run anomaly detection per series (potentially in parallel) and aggregate results to identify which machines/sensors warrant attention.

Singapore, Singapore

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Question 12:

  • Correct answers: A, B, F.

  • Why:
- A. The index size will increase. Enabling CMK encryption adds encryption metadata and key management data, which increases index size. - B. Query times will increase. Encryption/decryption overhead and key retrieval can slow queries. - F. Azure Key Vault is required. CMK means you store/manage keys in Key Vault; it’s a billable, required service for CMK.
  • Why the other options are incorrect:
- C (self-signed X.509 certificate required) is not a requirement for CMK. - D (index size will decrease) and E (query times will decrease) contradict the expected impact of CMK.

Singapore, Singapore

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GIF also we are using ?

  • No, GIF is not supported for Form Recognizer input. The allowed formats are JPG, PNG, PDF (text or scanned), or TIFF.
  • If you have GIFs, convert them to one of the supported formats (e.g., convert to JPG/PNG or PDF) before training or uploading.
  • Also ensure each file is under 50 MB and, when possible, use text-embedded PDFs to reduce errors.

Singapore, Singapore

VirtuLearn AI

Question 11:

  • Correct answers: A, C, F.

  • Why:
- Form Recognizer accepts documents in these formats: JPG, PNG, PDF (text or scanned), or TIFF. (TIFF is sometimes used in archival/scanned docs.) - Text-embedded PDFs are preferred because they minimize character extraction and location errors. - Training data must be under 50 MB per file.
  • So A, C, and F are the three files that meet these input requirements; the other options (B, D, E) likely fail one of the criteria (wrong format or too large). If you want, describe the formats of A, C, and F to confirm they meet all three criteria.

Singapore, Singapore

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Question 10:
The correct answer is B: A new query key was generated.
Explanation:

  • The REST call to:
POST .../regenerateKey?api-version=2017-04-18 with body {"keyName": "Key2"} regenerates the specified account key.
  • Since you specified Key2, only the secondary key is regenerated; the primary key (Key1) remains unchanged.
  • This operation updates the Cognitive Services account keys within Azure, not anything in Azure Key Vault.
  • “Query key” refers to the key used to authorize API requests to the service (subscription key), so regenerating Key2 yields a new value for that key.

Singapore, Singapore