Optimizing Server Size for a Streaming App with 100,000 Concurrent Users

As a startup considering the architecture for a streaming app that supports up to 100,000 concurrent users, you're faced with a complex decision: determining the right server size and cloud provider. This article will guide you through the process, breaking down key considerations and providing recommendations tailored to your needs.

Factors to Consider

User Engagement Streaming Quality

User Engagement: Understand the number of users who will be actively streaming simultaneously. For instance, if you expect 10 out of 10,000 users to stream concurrently, this affects server requirements significantly. Streaming Quality: The resolution and bitrate of your streams impact bandwidth and server load. For example: 720p: ~2.5 Mbps per stream 1080p: ~5 Mbps per stream 4K: ~25 Mbps per stream

Consider the total bandwidth needs for 10,000 concurrent 1080p streams:

Total Bandwidth 10,000 * 5 Mbps 50,000 Mbps or ~6,250 MB/s

Backend Architecture

Use a microservices architecture to scale components independently. This includes services for transcoding, authentication, and databases. Here's an example of how to handle each component:

Transcoding Streaming: Use services like AWS Elemental Media Services or GCloud Video Intelligence. Authentication: Ensure secure and efficient authentication methods. Databases: Store user data and metadata using services like DynamoDB or Firestore.

Data Transfer Load Balancing

Factor in the total data transfer for video streaming and additional data like chat notifications. Use load balancers to distribute traffic across multiple servers, ensuring availability and performance:

Use Auto Scaling Groups to adjust the number of instances based on real-time demand. Start with 10-20 instances and monitor performance closely.

CDN Storage

Integrate a Content Delivery Network (CDN) to reduce latency and improve load times. Employ object storage for video content, such as S3 for AWS or Cloud Storage for GCloud, to handle high traffic and video storage needs.

CDN: Cache and deliver video content closer to users to enhance user experience. Storage: Store video files and metadata efficiently using the cloud provider's object storage.

Estimated Server Requirements

Compute Resources

Consider the following compute resources:

AWS EC2 Instances: Start with instances that have at least 8 vCPUs and 32 GB RAM for transcoding and streaming tasks. For heavier workloads, consider instances with 16 vCPUs and 64 GB RAM. GCloud Compute Engine: Similarly, opt for instances with minimum 8 vCPUs and 32 GB RAM.

Scaling

To ensure scalability:

Auto Scaling Groups: Frequently monitor performance and dynamically scale resources based on demand. Start with 10-20 instances and monitor performance to fine-tune the configuration.

Example Architecture

Frontend: A web or mobile app for user interaction.

Load Balancer: Distributes incoming traffic across multiple instances, ensuring high availability and performance.

Streaming Servers: Handle the actual video streaming using services like AWS Elemental Media Services or GCloud Video Intelligence.

Database: Store user data and metadata using DynamoDB (AWS) or Firestore (GCloud).

CDN: Implements caching and delivery of video content closer to users, enhancing load times and user experience.

Conclusion

Begin with a well-defined architecture, and be prepared to scale based on user demand. Regularly monitor your app’s performance and adjust resources as needed. AWS and GCloud both offer flexible pricing and scaling options that can help you optimize costs as your user base grows.