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Codemotion 2019: A million likes/second: Real-time interactions on Live Video

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Akhilesh Gupta
Akhilesh Gupta

Codemotion 2019 Conference Presentation When someone like Reid Hoffman streams a live video on LinkedIn about a popular topic like startups, tens of thousands of viewers will watch it concurrently. Typically, hundreds of likes on the video will be distributed in real-time to all of these viewers. That amounts to a million likes/second distributed to viewers per live video. How do we make this massive real-time interaction possible across the globe? In this talk, I’ll do a technical deep-dive into how we use the Play/Akka Framework and a scalable distributed system to enable live interactions like likes/comments at massive scale.

Software
1 of 149
A million likes/second Real-time interactions on Live Video Akhilesh Gupta Realtime Engineer, LinkedIn
What is a Live Video?
Which was the largest live stream in the world? (largest number of concurrent viewers) ?
INDIA VS NEW ZEALAND WORLD CUP Largest Live Stream >25.3M viewers
What are real-time interactions on Live Video?
Mobile LINKEDIN LIVE Likes/Comments Concurrent Viewer Counts
LINKEDIN LIVE Desktop Likes/Comments Concurrent Viewer Counts
Distribution of Likes A S
Distribution of Likes A S Simple HTTP Request
Distribution of Likes A S Simple HTTP Request ?
Problem 1: The delivery pipe
The delivery pipe Real-time Delivery A S Likes Backend (Publisher)
The delivery pipe Real-time Delivery A S Likes Backend (Publisher) Simple HTTP Request
The delivery pipe Real-time Delivery A S Likes Backend (Publisher) Persistent Connection
The delivery pipe Real-time Delivery A S Likes Backend (Publisher) Persistent Connection
Persistent Connection Real-time Delivery
TRY IT! Login at linkedin.com Persistent Connection tiny.cc/realtime
EVENTSOURCE INTERFACE CLIENT REQUEST HTTP Long Poll with Server Sent Events GET /connect HTTP/1.1 Accept: text/event-stream
EVENTSOURCE INTERFACE SERVER RESPONSE HTTP Long Poll with Server Sent Events HTTP/1.1 200 OK - RESPONSE HEADERS - Content-Type: text/event-stream
EVENTSOURCE INTERFACE SERVER RESPONSE HTTP Long Poll with Server Sent Events HTTP/1.1 200 OK - RESPONSE HEADERS - Content-Type: text/event-stream - RESPONSE BODY - data: {“like” object}
EVENTSOURCE INTERFACE SERVER RESPONSE HTTP Long Poll with Server Sent Events HTTP/1.1 200 OK - RESPONSE HEADERS - Content-Type: text/event-stream - RESPONSE BODY - data: {“like” object} .. data: {“comment” object}
EVENTSOURCE INTERFACE SERVER RESPONSE HTTP Long Poll with Server Sent Events HTTP/1.1 200 OK - RESPONSE HEADERS - Content-Type: text/event-stream - RESPONSE BODY - data: {“like” object} .. data: {“comment” object} .. data: {“like” object}
WEB EventSource Client Libraries var evtSource = new EventSource("https://www.linkedin.com/realtime/connect"); evtSource.onmessage = function(e) { var likeObject = JSON.parse(e.data); }
ANDROID & IOS SUPPORT EventSource Client Libraries Android: https://github.com/tylerjroach/eventsource-android iOS Swift: https://github.com/inaka/EventSource
Next Problem? Real-time Delivery
Next Problem: Multiple Connections Real-time Delivery
Problem 2:Connection Management
PLAY & AKKA Connection Management Akka is a toolkit for building highly concurrent, distributed, and resilient message-driven applications
AN AKKA ACTOR Connection Management State Behavior
AN AKKA ACTOR Connection Management State Behavior ABC Mailbox
 One per Actor
AN AKKA ACTOR Connection Management State Behavior ABC Mailbox
 One per Actor
AN AKKA ACTOR Connection Management State Behavior ABC Mailbox
 One per Actor Millions of Actors
AN AKKA ACTOR Connection Management State Behavior ABC Mailbox
 One per Actor No. of threads proportional to
 no. of cores Millions of Actors
AN AKKA ACTOR Connection Management Connection Publish Event ABC Events to be published Millions of Connections
INITIALIZE AN AKKA ACTOR Server: Accepting a EventSource connection // Client A connects to the server and is assigned connectionIdA public Result listen() { }
INITIALIZE AN AKKA ACTOR Server: Accepting a EventSource connection // Client A connects to the server and is assigned connectionIdA public Result listen() { return ok(EventSource.whenConnected(eventSource -> { String connectionId = UUID.randomUUID().toString(); })); }
INITIALIZE AN AKKA ACTOR Server: Accepting a EventSource connection // Client A connects to the server and is assigned connectionIdA public Result listen() { return ok(EventSource.whenConnected(eventSource -> { String connectionId = UUID.randomUUID().toString(); // construct an Akka Actor with the new EventSource connection identified by a random connection identifier Akka.system().actorOf( ClientConnectionActor.props(connectionId, eventSource), connectionId); })); }
Publish Events Using Akka Actors Akka 
 Actor Real-time 
 Delivery 
 System Connection ID
 cid1
EVENT PUBLISH FROM PUBLISHER Publish Events Using Akka Actors Actor 1 Real-time 
 Delivery 
 System Actor 2 Actor 3 Actor 4 Actor 5 Akka
 Supervisor
 Actor cid1 cid2 cid3 cid4 cid5
EVENT PUBLISH FROM SUPERVISOR TO CHILD ACTORS Publish Events Using Akka Actors Actor 1 Real-time 
 Delivery 
 System Actor 2 Actor 3 Actor 4 Actor 5 Akka
 Supervisor
 Actor cid1 cid2 cid3 cid4 cid5
EVENT PUBLISH FROM CHILD ACTORS TO CLIENT CONNECTIONS Publish Events Using Akka Actors Actor 1 Real-time 
 Delivery 
 System Actor 2 Actor 3 Actor 4 Actor 5 Akka
 Supervisor
 Actor cid1 cid2 cid3 cid4 cid5
EVENT PUBLISH FROM CHILD ACTORS TO CLIENT CONNECTIONS Publishing on EventSource eventSource.send(<like object>);
EVENT PUBLISH FROM CHILD ACTORS TO CLIENT CONNECTIONS Publish Events Using Akka Actors Actor 1 Real-time 
 Delivery 
 System Actor 2 Actor 3 Actor 4 Actor 5 Akka
 Supervisor
 Actor cid1 cid2 cid3 cid4 cid5
EVENT PUBLISH FROM CHILD ACTORS TO CLIENT CONNECTIONS Publish Events Using Akka Actors Actor 1 Real-time 
 Delivery 
 System Actor 2 Actor 3 Actor 4 Actor 5 Akka
 Supervisor
 Actor cid1 cid2 cid3 cid4 cid5
EVENTSOURCE INTERFACE Received Events on the Clients HTTP/1.1 200 OK - RESPONSE HEADERS - Content-Type: text/event-stream - RESPONSE BODY - data: {“User A liked the video…” object}
Next Problem? Real-time Delivery
Next Problem: Multiple Live Videos Real-time Delivery
Problem 3:Multiple Live Videos
START WATCHING LIVE VIDEO Multiple Live Videos cid3 cid5 Live Video 1 Live Video 2 Real-time 
 Delivery 
 System
HTTP SUBSCRIPTION REQUEST Viewers subscribe to Live Videos Topic ConnectionId In-Memory 
 Subscriptions
 Table cid3 cid5 Live Video 1 Live Video 2 /subscribe
IN-MEMORY SUBSCRIPTION ENTRY Viewers subscribe to Live Videos Topic ConnectionId In-Memory 
 Subscriptions
 Table cid5 Live Video 2 /subscribe /subscribe cid3Live Video 1
IN-MEMORY SUBSCRIPTION ENTRY Viewers subscribe to Live Videos Topic ConnectionId In-Memory 
 Subscriptions
 Table cid3 cid5 Live Video 1 Live Video 2 /subscribe /subscribe
Publish using Subscription Actor 1 Actor 2 Actor 3 Actor 4 Actor 5 Supervisor cid1 cid2 cid3 cid4 cid5 Live Video 1 cid3 Live Video 2 cid5 Live Video 2 cid1 Live Video 1 cid4 Live Video 2 cid2
PUBLISHER PUBLISH TO SUPERVISOR ACTOR Publish using Subscription Actor 1 Actor 2 Actor 3 Actor 4 Actor 5 Supervisor cid1 cid2 cid3 cid4 cid5 Live Video 1 cid3 Live Video 2 cid5 Live Video 2 cid1 Live Video 1 cid4 Live Video 2 cid2
SUBSCRIBER LOOKUP FROM IN MEMORY TABLE Publish using Subscription Actor 1 Actor 2 Actor 3 Actor 4 Actor 5 Supervisor cid1 cid2 cid3 cid4 cid5 Live Video 1 cid3 Live Video 2 cid5 Live Video 2 cid1 Live Video 1 cid4 Live Video 2 cid2
PUBLISH TO CLIENT CONNECTIONS Publish using Subscription Actor 1 Actor 2 Actor 3 Actor 4 Actor 5 Supervisor cid1 cid2 cid3 cid4 cid5 Live Video 1 cid3 Live Video 2 cid5 Live Video 2 cid1 Live Video 1 cid4 Live Video 2 cid2
PUBLISHER PUBLISH TO SUPERVISOR ACTOR Publish using Subscription Actor 1 Actor 2 Actor 3 Actor 4 Actor 5 Supervisor cid1 cid2 cid3 cid4 cid5 Live Video 1 cid3 Live Video 2 cid5 Live Video 2 cid1 Live Video 1 cid4 Live Video 2 cid2
SUBSCRIBER LOOKUP FROM IN MEMORY TABLE Publish using Subscription Actor 1 Actor 2 Actor 3 Actor 4 Actor 5 Supervisor cid1 cid2 cid3 cid4 cid5 Live Video 1 cid3 Live Video 2 cid5 Live Video 2 cid1 Live Video 1 cid4 Live Video 2 cid2
PUBLISH TO CLIENT CONNECTIONS Publish using Subscription Actor 1 Actor 2 Actor 3 Actor 4 Actor 5 Supervisor cid1 cid2 cid3 cid4 cid5 Live Video 1 cid3 Live Video 2 cid5 Live Video 2 cid1 Live Video 1 cid4 Live Video 2 cid2
Next Problem? Real-time Delivery
Next Problem: 10K Concurrent Viewers Real-time Delivery
Problem 4:10K Concurrent Viewers
10K Concurrent Viewers Real-time Delivery
S C A L I N G B A C K E N D S Y S T E M S When in doubt, add a machine!
10K Concurrent Viewers Real-time Delivery
10K Concurrent Viewers Frontend Frontend
10K Concurrent Viewers Frontend Frontend
DISPATCHES BETWEEN FRONTEND NODES Real-time Dispatcher Frontend Frontend Real-time Dispatcher
Frontend Node Subscriptions node1 node2 Live Video 1 Live Video 2 Frontend Frontend Real-time Dispatcher
HTTP SUBSCRIPTION REQUEST Frontend Node Subscriptions node1 node2 Live Video 1 Live Video 2 Frontend Frontend Topic Frontend Host Real-time Dispatcher Subscriptions
 Table /subscribe
SUBSCRIPTIONS TABLE ENTRY Frontend Node Subscriptions node1 node2 Live Video 1 Live Video 2 Frontend Frontend Topic Frontend Host Real-time Dispatcher Subscriptions
 Table /subscribe /subscribe
SUBSCRIPTIONS TABLE ENTRY Frontend Node Subscriptions node1 node2 Live Video 1 Live Video 2 Frontend Frontend Topic Frontend Host Real-time Dispatcher Subscriptions
 Table /subscribe /subscribe
SUBSCRIPTIONS TABLE ENTRY Frontend Node Subscriptions node1 node2 Live Video 1 Live Video 2 Frontend Frontend Topic Frontend Host Real-time Dispatcher Subscriptions
 Table /subscribe /subscribe
Publish to Frontend Nodes node1 Real-time Dispatcher Frontend node2 Frontend node3 Frontend node4 Frontend node5 Frontend Live Video 1 node3 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2
PUBLISHER PUBLISH TO DISPATCHER Publish to Frontend Nodes node1 Live Video 1 node3 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2 Real-time Dispatcher Frontend node2 Frontend node3 Frontend node4 Frontend node5 Frontend Dispatcher
SUBSCRIBER LOOKUP Publish to Frontend Nodes node1 Live Video 1 node3 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2 Real-time Dispatcher Frontend node2 Frontend node3 Frontend node4 Frontend node5 Frontend Dispatcher
PUBLISH TO SUBSCRIBED FRONTEND NODES Publish to Frontend Nodes node1 Live Video 1 node3 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2 Real-time Dispatcher Frontend node2 Frontend node3 Frontend node4 Frontend node5 Frontend Dispatcher
Frontend Node to Client Publish Frontend
Frontend Node to Client Publish Frontend
What’s the next problem? Frontend Frontend Frontend Frontend Frontend Dispatcher Live Video 1 node3 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2
Problem 5:100 Likes/second
100 Likes/second Frontend Frontend Frontend Frontend Frontend Dispatcher Live Video 1 node3 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2
S C A L I N G B A C K E N D S Y S T E M S When in doubt, add a machine!
100 Likes/second Frontend Frontend Frontend Frontend Frontend Dispatcher Live Video 1 node3 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2
100 Likes/second Frontend Frontend Frontend Frontend Frontend Dispatcher Live Video 1 node7 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2 Dispatcher Frontend Frontend
COUCHBASE/REDIS ETC. Key-Value Store for Subscriptions Frontend Frontend Frontend Frontend Frontend Dispatcher Dispatcher Frontend Frontend Live Video 1 node7 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2 Key-Value Store Dispatcher
Publish to Dispatcher Nodes Frontend Frontend Frontend Frontend Frontend Dispatcher Dispatcher Frontend Frontend Key-Value Store Dispatcher Live Video 1 node7 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2
Subscriber lookup from KV Store Frontend Frontend Frontend Frontend Frontend Dispatcher Dispatcher Frontend Frontend Key-Value Store Dispatcher Live Video 1 node7 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2 node1 node2 node3 node4 node5 node6 node7
Publish to Frontend Nodes Frontend Frontend Frontend Frontend Frontend Dispatcher Dispatcher Frontend Frontend Key-Value Store Dispatcher Live Video 1 node7 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2 node1 node2 node3 node4 node5 node6 node7
Publish to Frontend Nodes Frontend Frontend Frontend Frontend Frontend Dispatcher Dispatcher Frontend Frontend Key-Value Store Dispatcher node1 node2 node3 node4 node5 node6 node7 Live Video 1 node7 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2
Publish to Frontend Nodes Frontend Frontend Frontend Frontend Frontend Dispatcher Dispatcher Frontend Frontend Key-Value Store Dispatcher node1 node2 node3 node4 node5 node6 node7 Live Video 1 node7 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2
Publish to Client Devices Frontend Frontend
Publish to Client Devices Frontend Frontend
The Overall Flow Frontend Dispatcher Key-Value Store
Problem 6: 10K Viewers, 100 Likes/s Distribution of 1M Likes/s
Mobile LINKEDIN LIVE Likes
The Subscription Flow Frontend Dispatcher Key-Value Store 1
START WATCHING LIVE VIDEO Viewers subscribing to Live Video Likes cid3 cid5 Live Video 1 Live Video 2 Frontend
HTTP SUBSCRIPTION REQUEST Viewers subscribing to Live Video Likes Topic ConnectionId cid3 cid5 Live Video 1 Live Video 2 /subscribe Frontend In-Memory 
 Subscriptions Table
FRONTEND IN-MEMORY SUBSCRIPTION ENTRY Viewers subscribing to Live Video Likes Topic ConnectionId cid5 Live Video 2 /subscribe /subscribe cid3Live Video 1 Frontend In-Memory 
 Subscriptions Table
FRONTEND IN-MEMORY SUBSCRIPTION ENTRY Viewers subscribing to Live Video Likes Topic ConnectionId cid3 cid5 Live Video 1 Live Video 2 /subscribe /subscribe Frontend In-Memory 
 Subscriptions Table
FRONTEND IN-MEMORY SUBSCRIPTION ENTRY Viewers subscribing to Live Video Likes Topic ConnectionId cid3 cid5 Live Video 1 Live Video 2 /subscribe /subscribe Frontend In-Memory 
 Subscriptions Table
The Subscription Flow Frontend Dispatcher Key-Value Store 1 2 3
FRONTEND RECEIVES SUBSCRIPTION REQUEST Frontend Node Subscriptions in Dispatcher node1 node2 Live Video 1 Live Video 2 Frontend Frontend Key-Value Store Dispatcher Dispatcher
FRONTEND HTTP SUBSCRIPTION REQUEST TO DISPATCHER Frontend Node Subscriptions in Dispatcher node1 node2 Live Video 1 Live Video 2 Frontend Frontend Topic Frontend Host /subscribe Key-Value Store Dispatcher Dispatcher
DISPATCHER SUBSCRIPTION ENTRY IN KV STORE Frontend Node Subscriptions in Dispatcher node1 node2 Live Video 1 Live Video 2 Frontend Frontend Topic Frontend Host /subscribe /subscribe Dispatcher Dispatcher Key-Value Store
DISPATCHER SUBSCRIPTION ENTRY IN KV STORE Frontend Node Subscriptions in Dispatcher node1 node2 Live Video 1 Live Video 2 Frontend Frontend Topic Frontend Host /subscribe /subscribe Dispatcher Dispatcher Key-Value Store
The Publish Flow Frontend Dispatcher Key-Value Store 1
Viewers liking Live Videos Likes Backend (Publisher)
Likes Published to Backend Likes Backend (Publisher)
The Publish Flow Frontend Dispatcher Key-Value Store 1 2 345
The Publish Flow Frontend Dispatcher Key-Value Store 2 345
BACKEND PUBLISH TO DISPATCHER NODES Dispatcher Publish to Frontend Nodes Frontend Frontend Frontend Frontend Frontend Dispatcher Dispatcher Frontend Frontend Key-Value Store Dispatcher Live Video 1 node3 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2
SUBSCRIBER LOOKUP FROM KV STORE Dispatcher Publish to Frontend Nodes Frontend Frontend Frontend Frontend Frontend Dispatcher Dispatcher Frontend Frontend Key-Value Store Dispatcher Live Video 1 node7 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2 node1 node2 node3 node4 node5 node6 node7
SUBSCRIBER LOOKUP FROM KV STORE Dispatcher Publish to Frontend Nodes Frontend Frontend Frontend Frontend Frontend Dispatcher Dispatcher Frontend Frontend Key-Value Store Dispatcher Live Video 1 node7 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2 node1 node2 node3 node4 node5 node6 node7
PUBLISH TO FRONTEND NODES Dispatcher Publish to Frontend Nodes Frontend Frontend Frontend Frontend Frontend Dispatcher Dispatcher Frontend Frontend Key-Value Store Dispatcher node1 node2 node3 node4 node5 node6 node7 Live Video 1 node7 Live Video 2 node5 Live Video 2 node1 Live Video 1 node4 Live Video 2 node2
The Publish Flow Frontend Dispatcher Key-Value Store 5
DISPATCHER PUBLISH TO FRONTEND NODE SUPERVISOR ACTOR Frontend Publish to Mobile Clients Actor 1 Actor 2 Actor 3 Actor 4 Actor 5 Supervisor cid1 cid2 cid3 cid4 cid5 Live Video 1 cid3 Live Video 2 cid5 Live Video 2 cid1 Live Video 1 cid4 Live Video 2 cid2 Dispatcher Frontend In-Memory 
 Subscriptions
 Table
SUBSCRIBED CLIENT CONNECTION LOOKUP FROM IN-MEMORY TABLE Frontend Publish to Mobile Clients Actor 1 Frontend Actor 2 Actor 3 Actor 4 Actor 5 Supervisor cid1 cid2 cid3 cid4 cid5 Live Video 1 cid3 Live Video 2 cid5 Live Video 2 cid1 Live Video 1 cid4 Live Video 2 cid2 Dispatcher In-Memory 
 Subscriptions
 Table
PUBLISH TO MOBILE CLIENTS Frontend Publish to Mobile Clients Actor 1 Frontend Actor 2 Actor 3 Actor 4 Actor 5 Supervisor cid1 cid2 cid3 cid4 cid5 Live Video 1 cid3 Live Video 2 cid5 Live Video 2 cid1 Live Video 1 cid4 Live Video 2 cid2 Dispatcher In-Memory 
 Subscriptions
 Table
Performance & Scale
How many persistent connections can a single machine hold? Frontend Server ?
> 100,000
ROYAL WEDDING Second Largest Stream >18M viewers
> 100,000 We can hold those 18M connections with just 180 machines
LINKEDIN ENGINEERING BLOG tiny.cc/ linkedinscaling >100K
LinkedIn Realtime Performance Persistent Connections/machine 5K/s Dispatcher Publish QPS/machine 75ms E2E Publish Latency >100K
Dispatcher Performance Frontend Frontend Frontend Frontend Frontend Dispatcher How many events per second can be published to a single dispatcher machine? ?
Dispatcher Performance Number of frontend nodes to publish to is limited per event Frontend Frontend Frontend Frontend Frontend Dispatcher ?
Dispatcher Performance Frontend Frontend Frontend Frontend Frontend Dispatcher ?
5K We can publish 50K likes per second with just 10 machines
LinkedIn Realtime Performance >100K Persistent Connections/machine Dispatcher Publish QPS/machine 75ms E2E Publish Latency 5K
E2E Publish Latency Frontend Dispatcher t1 Key-Value Store
E2E Publish Latency Frontend Dispatcher t1 Key-Value Store t2 t2-t1 = 75ms p90
LinkedIn Realtime Performance >100K Persistent Connections/machine Dispatcher Publish QPS/machine 75ms E2E Publish Latency 5K
LINKEDIN ENGINEERING BLOG tiny.cc/ linkedinlatency Measurement System E2E Publish Latency
Why does this system scale? Horizontally Scalable System Frontend Dispatcher Frontend Frontend Frontend Dispatcher Dispatcher Dispatcher Distributed K/V Storage System
Active Status/Presence Online/Offline indicators LINKEDIN REALTIME TECHNOLOGY
LINKEDIN ENGINEERING BLOG tiny.cc/ linkedinpresence Active Status/Presence
Key takeaways
R E A LT I M E I N T E R A C T I O N S Enable dynamic instant experiences on your apps
E V E N T S O U R C E / S S E Built-in support in most server frameworks Readily available client libraries HTTP/1.1 200 OK - RESPONSE HEADERS - Content-Type: text/event-stream
P l a y F r a m e w o r k a n d A k k a A c t o r s Powerful frameworks to manage millions of connections State BehaviorMailbox
D i s t r i b u t e d S y s t e m s Start small and add simple layers to your architecture
S C A L I N G B A C K E N D S Y S T E M S When in doubt, add a machine!
R E A LT I M E I N T E R A C T I O N P L A T F O R M Can be built on any server/storage technology Horizontally scalable Frontend Dispatcher Key-
R E A LT I M E I N T E R A C T I O N P L A T F O R M You can do it for your app!
R E A LT I M E E N G I N E E R , L I N K E D I N @agupta03 t i n y . c c / c o d e m o t i o n 2 0 1 9

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