Bird
Raised Fist0
HLDsystem_design~10 mins

Video upload and processing pipeline in HLD - Interactive Code Practice

Choose your learning style10 modes available
LearnWhyDeepArchPracticeChallengeDesignRecallScale

Start learning this pattern below

Jump into concepts and practice - no test required

or
Recommended
Test this pattern10 questions across easy, medium, and hard to know if this pattern is strong
Practice - 5 Tasks
Answer the questions below
1fill in blank
easy

Complete the code to identify the first step in the video upload pipeline.

HLD
The first component in the pipeline is the [1] which receives the video file from the user.
Drag options to blanks, or click blank then click option'
AEncoding Service
BLoad Balancer
CUpload Server
DDatabase
Attempts:
3 left
💡 Hint
Common Mistakes
Confusing the encoding service as the first step
Choosing the database as the first component
2fill in blank
medium

Complete the code to specify the component responsible for converting videos into multiple formats.

HLD
After upload, the video is sent to the [1] which converts it into different resolutions and formats.
Drag options to blanks, or click blank then click option'
AEncoding Service
BContent Delivery Network
CUpload Server
DMetadata Store
Attempts:
3 left
💡 Hint
Common Mistakes
Selecting Upload Server instead of Encoding Service
Choosing CDN which is for delivery, not processing
3fill in blank
hard

Fix the error in naming the storage component for processed videos.

HLD
Processed videos are stored in the [1] for fast retrieval and streaming.
Drag options to blanks, or click blank then click option'
AObject Storage
BEncoding Service
CLoad Balancer
DUpload Server
Attempts:
3 left
💡 Hint
Common Mistakes
Confusing Upload Server with storage
Choosing Load Balancer which is for traffic management
4fill in blank
hard

Fill both blanks to complete the request flow for video processing and delivery.

HLD
User uploads video to [1], then the video is processed by [2] before storage.
Drag options to blanks, or click blank then click option'
AUpload Server
BContent Delivery Network
CEncoding Service
DDatabase
Attempts:
3 left
💡 Hint
Common Mistakes
Mixing up CDN with processing
Choosing Database instead of processing service
5fill in blank
hard

Fill all three blanks to complete the architecture components for video upload, processing, and delivery.

HLD
The [1] handles incoming video files, the [2] converts videos, and the [3] delivers videos to users.
Drag options to blanks, or click blank then click option'
AUpload Server
BEncoding Service
CContent Delivery Network
DMetadata Store
Attempts:
3 left
💡 Hint
Common Mistakes
Confusing Metadata Store with delivery
Mixing up Upload Server and Encoding Service roles

Practice

(1/5)
1. Which component in a video upload and processing pipeline is primarily responsible for converting raw uploaded videos into multiple formats suitable for playback?
easy
A. Content delivery network (CDN)
B. Video processing service
C. Metadata database
D. Upload service

Solution

  1. Step 1: Identify the role of each component

    The upload service handles receiving videos, the metadata database stores info, and CDN delivers content. The processing service converts videos.

  2. Step 2: Match the function to the question

    Converting raw videos into multiple formats is done by the video processing service to ensure compatibility.

  3. Final Answer:

    Video processing service -> Option B

  4. Quick Check:

    Conversion = Video processing service [OK]
Hint: Processing means converting video formats [OK]
Common Mistakes:
  • Confusing upload service with processing
  • Thinking CDN does video conversion
  • Assuming metadata database handles video files
2. Which of the following is the correct sequence of steps in a typical video upload and processing pipeline?
easy
A. Storage -> Upload service -> Video processing -> Metadata update
B. Video processing -> Upload service -> Metadata update -> Storage
C. Metadata update -> Upload service -> Storage -> Video processing
D. Upload service -> Video processing -> Storage -> Metadata update

Solution

  1. Step 1: Understand the logical flow

    Users first upload videos, then videos are processed, stored, and metadata is updated last.

  2. Step 2: Match the sequence to options

    Upload service -> Video processing -> Storage -> Metadata update correctly shows upload first, then processing, storage, and metadata update.

  3. Final Answer:

    Upload service -> Video processing -> Storage -> Metadata update -> Option D

  4. Quick Check:

    Upload first, then process, store, update metadata [OK]
Hint: Upload happens before processing and storage [OK]
Common Mistakes:
  • Starting with processing before upload
  • Updating metadata before storage
  • Mixing storage and upload order
3. Consider a video upload pipeline where the upload service places video metadata into a queue for processing. If the processing service crashes and stops consuming messages, what will happen to the queue and user experience?
medium
A. Upload service will reject new uploads immediately
B. Queue will empty quickly; users get instant processing
C. Queue will fill up, causing delays; users see slow processing
D. Metadata database will automatically process videos

Solution

  1. Step 1: Understand queue behavior when consumer stops

    If the processing service crashes, it stops consuming messages, so the queue fills up with unprocessed metadata.

  2. Step 2: Impact on user experience

    Since processing is delayed, users experience slow video availability or processing delays.

  3. Final Answer:

    Queue will fill up, causing delays; users see slow processing -> Option C

  4. Quick Check:

    Processing down -> queue fills -> delays [OK]
Hint: No consumer means queue backs up [OK]
Common Mistakes:
  • Assuming queue empties without consumer
  • Thinking upload service rejects uploads immediately
  • Believing metadata DB processes videos automatically
4. In a video processing pipeline, a developer notices that some videos fail to process and the system does not retry them. Which change will fix this issue?
medium
A. Implement a retry mechanism in the processing service for failed jobs
B. Remove the queue to speed up processing
C. Store videos only after processing completes
D. Disable metadata updates to avoid conflicts

Solution

  1. Step 1: Identify cause of failure handling

    Failures without retries mean the system lacks a retry mechanism for failed processing jobs.

  2. Step 2: Choose fix to handle failures

    Adding retries ensures failed jobs are re-attempted, improving reliability.

  3. Final Answer:

    Implement a retry mechanism in the processing service for failed jobs -> Option A

  4. Quick Check:

    Retries fix failed processing [OK]
Hint: Retries fix failed processing jobs [OK]
Common Mistakes:
  • Removing queue breaks asynchronous design
  • Storing before processing causes errors
  • Disabling metadata updates unrelated to retries
5. You need to design a scalable video upload and processing pipeline that supports millions of daily uploads with minimal user wait time. Which architectural choice best supports this goal?
hard
A. Use asynchronous upload service with message queues and distributed processing workers
B. Process videos synchronously during upload to ensure immediate availability
C. Store all videos on a single server to simplify management
D. Update metadata only after manual verification to ensure accuracy

Solution

  1. Step 1: Analyze scalability and user wait time needs

    Millions of uploads require asynchronous handling and distributed processing to avoid bottlenecks and reduce wait time.

  2. Step 2: Evaluate architectural options

    Asynchronous upload with queues and distributed workers allows parallel processing and smooth scaling.

  3. Final Answer:

    Use asynchronous upload service with message queues and distributed processing workers -> Option A

  4. Quick Check:

    Asynchronous + distributed = scalable and fast [OK]
Hint: Async + queues + distributed workers scale best [OK]
Common Mistakes:
  • Synchronous processing causes delays
  • Single server storage limits scalability
  • Manual metadata delays pipeline