Learn more about computerscience with this collection
Understanding machine learning models
Improving data analysis and decision-making
How Google uses logic in machine learning
Challenge 5: 100 Likes/second
- Scale horizontally again to handle more events -> Add multiple Dispatchers and move the subscription table into a key-value store so it's accessible to all Dispatchers.
- Dispatchers are independent from Frontend nodes and don't have persistent connections between them.
- Any Frontend node can subscribe to any Dispatcher.
- Any Dispatcher can publish events to any Frontend node.
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Challenge 2: Connection Management
- Each connection is managed by an Akka actor.
- Actors are so lightweight that there can be millions of them on a single system. Moreover, all of them can be served by a small number of threads, proportional to the number of cores. This...
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44 reads
Challenge 3: Multiple Live Videos
- Clients are subscribing to events for a particular live video i.e. they are telling the server which live video they are watching.
- The Frontend server stores all subscriptions in an in-memory table.
- Every time a new event is published, the su...
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Final architecture
- A viewer likes a video and sends an HTTP request to the Likes backend, which stores it in a database.
- The backend forwards the like to any random Dispatcher node using an HTTP request.
- Dispatcher looks up in the key-value store to find out which Frontend nodes are subscribed ...
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315 reads
Interactive Live Videos
Having a lot of people interact on live videos poses many technical challenges. Mainly because viewers generate a lot of interactions that need to be delivered fast.
To get a sense of the scale, the top live streams in the world gathered millions of concurrent users:
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The Realtime Platform
LinkedIn has built the Realtime Platform to distribute multiple types of data in real-time such as:
- Likes, comments and viewer count for Live Videos
- Typing indicators and Read receipts for Instant Messaging
- Presence i.e. the green online indicators ...
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118 reads
Related posts
- How LinkedIn displays Presence indicators in real-time: https://engineering.linkedin.com/blog/2018/01/now-you-see-me--now-you-dont--linkedins-real-time-presence-platf
- How LinkedIn measures end-to-end latency across systems: https://engineering.linked...
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Challenge 4: 10K Concurrent Viewers
- Scale horizontally to handle more concurrent viewers -> Add multiple Frontend nodes and coordinate them using a Dispatcher node.
- In a similar fashion to the Frontend node, the Dispatcher has a subscriptions table to know which frontend nodes should r...
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54 reads
Challenge 1: The Delivery Pipe
- User devices have a persistent connection to the Realtime Platform servers.
- The servers use server-sent events to stream data fast on this connection via the EventSource interface.
A persistent connection is an HTTP L...
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Bonus Challenge: Multiple data-centers
Expanding to other regions requires two steps:
- Replicate the setup in each data-center.
- Have the Dispatcher broadcast the events to its peer Dispatchers from the other data-centers.
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Performance and scale
- Each Frontend node handles 100k persistent connections. It handles only this many connections because the server is doing a lot of work processing multiple types of data (likes, comments, instant messaging etc.).
- Each Dispatcher can publish 5k events per seco...
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49 reads
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Challenge 4: 10K Concurrent Viewers
- Scale horizontally to handle more concurrent viewers -> Add multiple Frontend nodes and coordinate them using a Dispatcher node.
- In a similar fashion to the Frontend node, the Dispatcher has a subscriptions table to know which frontend nodes should r...
Performance and scale
- Each Frontend node handles 100k persistent connections. It handles only this many connections because the server is doing a lot of work processing multiple types of data (likes, comments, instant messaging etc.).
- Each Dispatcher can publish 5k events per seco...
Final architecture
- A viewer likes a video and sends an HTTP request to the Likes backend, which stores it in a database.
- The backend forwards the like to any random Dispatcher node using an HTTP request.
- Dispatcher looks up in the key-value store to find out which Frontend nodes are subscribed ...
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