Functional & Non-Functional Requirements

The primary goal of the live video streaming platform is to deliver high-quality video streams to users around the globe while allowing real-time interactions. The platform must support various genres including gaming, sports, music, and educational content, appealing to a diverse audience. Key requirements include the ability to handle many simultaneous streams and viewers, low latency streaming, and support for multiple resolutions and devices.

Real-time interaction features such as live chat, upvotes, or reactions are essential for audience engagement. Content moderation tools need to be robust enough to filter inappropriate content promptly. Additionally, we must ensure that the system is scalable to handle varying loads and is resilient to failures to provide a seamless experience.

Capacity Estimation

In estimating the system's needs, consider the user base. For our initial deployment, we might target 10,000 simultaneous viewers with an aim to scale up to 1 million concurrently as the platform gains popularity. Each stream can be roughly estimated to require 2 Mbps of bandwidth for decent quality.

The cost of infrastructure, including CDNs, servers, storage, and bandwidth, needs careful consideration. Using cloud services can help reduce upfront costs, allowing us to scale efficiently as demand grows. We should initially allocate resources for load testing to determine our exact requirements more accurately.

API Design

Our API should adhere to RESTful principles, allowing for intuitive interactions. Key endpoints might include:

• POST /streams to create a new stream
• GET /streams/{id} to fetch stream details
• POST /streams/{id}/chat to send messages to the chat
• DELETE /streams/{id} to end a stream

Authentication is critical, and we should implement OAuth2.0. Additionally, websockets can be utilized for real-time interactions like live chat and notifications.

Database Design

The database schema will have to support various entities like Users, Streams, and Messages. Users can have roles such as Admin, Moderator, and Viewer. Streams will hold metadata including title, genre, stream status, and creator information. Messages will contain chat logs relevant to each stream.

We will likely use a relational database (e.g., PostgreSQL) for structured data and a NoSQL solution (e.g., Redis) for fast access to chat messages and real-time notifications. This hybrid approach will allow for both robust data integrity and high speed.

High Level Design

The high-level architecture involves clients connecting to a Load Balancer that distributes traffic among multiple Streaming Servers. Each Streaming Server will handle live encoding and can draw on a Content Delivery Network (CDN) for broad distribution and lower latency. A separate service will manage real-time interactions and moderation.

The database will interact with the API to manage user data, stream metadata, and chat messages. Caches will be employed to improve response times for frequently accessed data, such as chat history. Queue services will manage incoming requests and processing workloads.

Request Flows

The request flow begins with a user sending a request to create a stream via the API. The Load Balancer receives this request and routes it to an available Streaming Server. Upon successful stream creation, the server initiates the encoding process and registers the stream in the database.

As viewers join, they connect through the Load Balancer to the Streaming Server serving the active stream. Chat messages sent during the stream are relayed through Websockets to the moderation service before being displayed. All interactions are logged for auditing and further analysis.

Detailed Component Design

Key components of the system include:

• Client Application: The user interface for stream creation and viewer interaction
• Streaming Server: Handles video processing and delivery
• Load Balancer: Distributes the traffic evenly among servers
• Moderation Service: Monitors chat for inappropriate content
• CDN: Deliver streams efficiently to users worldwide

Each component should operate independently yet integrate seamlessly to enhance user experience.

Trade-offs & Tech Choices

The primary trade-off relates to balancing quality and cost. Using higher-quality streaming formats or lower latency configurations will increase infrastructure costs. While opting for cheaper resources or compression can reduce expenses, it may impact user experience negatively.

Another trade-off is between real-time interaction quality and server load. Enabling extensive interactive features for all viewers simultaneously can lead to performance degradation. Careful management of system resources and prioritization of interactions can help mitigate these issues.

Failure Scenarios & Bottlenecks

Potential failure scenarios need to be anticipated, such as server outages, network congestion, or database failures. Implementing redundancy in our architecture can help us recover quickly from server failures by switching to backup servers.

We should also consider how to handle network failures during a live event. Implementing a multi-availability zone deployment can allow users to switch to a different region if their local CDN fails. Real-time alerts for admins will also aid in swiftly addressing these issues.

Future Improvements

To enhance the platform continually, we might explore incorporating AI-driven content recommendations based on viewer preferences. Implementing integration with social media platforms can enhance engagement by allowing users to share live streams easily.

Additionally, we could consider introducing monetization features for streamers such as subscriptions or advertisements, offering them better incentives. Ongoing performance monitoring and optimization based on user feedback will be vital for keeping the platform competitive.

High Level Architecture Diagram

Database ER Diagram

Request Flow Sequence Diagram