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This week’s system design refresher:
Introduction to Generative AI (Youtube video)
Iterative, Agile, Waterfall... What are the differences between these Software Development Life Cycle models?
How to Design a System Like YouTube?
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Introduction to Generative AI
Iterative, Agile, Waterfall... What are the differences between these Software Development Life Cycle models?
The Software Development Life Cycle (SDLC) is a framework that outlines the process of developing software in a systematic way. Here are some of the most common ones:
Waterfall Model:
- A linear and sequential approach.
- Divides the project into distinct phases: Requirements, Design, Implementation, Verification, and Maintenance.
Agile Model:
- Development is done in small, manageable increments called sprints.
- Common Agile methodologies include Scrum, Kanban, and Extreme Programming (XP).
V-Model (Validation and Verification Model):
- An extension of the Waterfall model.
- Each development phase is associated with a testing phase, forming a V shape.
Iterative Model:
- Focuses on building a system incrementally.
- Each iteration builds upon the previous one until the final product is achieved.
Spiral Model:
- Combines iterative development with systematic aspects of the Waterfall model.
- Each cycle involves planning, risk analysis, engineering, and evaluation.
Big Bang Model:
- All coding is done with minimal planning, and the entire software is integrated and tested at once.
RAD Model (Rapid Application Development):
- Emphasizes rapid prototyping and quick feedback.
- Focuses on quick development and delivery.
Incremental Model:
- The product is designed, implemented, and tested incrementally until the product is finished.
Each of these models has its advantages and disadvantages, and the choice of which to use often depends on the specific requirements and constraints of the project at hand.
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How to Design a System Like YouTube?
Here’s a 9-step process:
The user creates a video upload request and provides the video files along with the details about the video.
The raw video files are uploaded to an Object Storage (such as S3).
Also, the metadata is saved in a database as well as a cache for faster retrieval when needed.
The raw video files are sent for transcoding to a special transcoding server. Transcoding is the process of encoding the videos into compatible bitrates and formats for streaming.
The transcoded video is uploaded to another object storage.
The notification for transcoding completion is sent to a special service via a message queue.
The Transcoding Status Handler updates the metadata DB and cache with the latest details of the video.
The user raises a video streaming request that goes to a Content Delivery Network (CDN).
The CDN fetches the video from the object storage for streaming. It also caches the video locally for subsequent streaming requests.
Over to you: What else would you add to make the YouTube-like system?
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