If you don't like managing all of this stuff there's a turn-key solution: The Azure SignalR Service. When SignalR uses Long Polling or Server Sent Events that limit is quickly reached.Įven WebSockets a limit of about 50 connections. Each client will have a HTTP connection limit of about 6 connections at the same time. Sticky sessions, Redis cache and we didn't even talk about connection limits. You can install Redis yourself or use the Azure Redis service.Īpart from Redis there is also community build support for other data stores, but the beauty of Redis is that it doesn't even store the data. Now in the configure services method in the startup class type AddRedis behind AddSignalR with as a parameter the redis connection string. Solving this is so easy it doesn't even need a screen shot. It in fact uses the built-in pub/sub functionality in Redis to synchronize client information across the different servers. SignalR supports redis out of the box as we will see later. This can be done with a database but a faster alternative would be to use a redis cache. To solve this the servers need a way to share data. But server 1 doesn't know about users that are connected to hubs in other servers. Now when the user on server 1 changes the document a message has to be sent to the others. The other might end up at another server. Let's say a user is working on a web document using Office 365 and she invites others to join her. Syncing Clients Between Instancesīut there's another problem. Else your application will use Server Sent Events at best. When using an on-premise server with IIS install the ARR Affinity module.Īnd while you're at it, make sure WebSockets is also turned on. Since SignalR could use non-websocket transports you should turn this on on all servers where your application is on. The IIS and Azure web apps version of sticky sessions is called Application Request Routing Affinity or ARR Affinity. On subsequent requests the load balancer then reads the cookie and assigns the request to the same server. As part of the response of the first request the load balancer sets a cookie in the browser indicating the server that was used. There are several implementations of this but most of the time it works as follows. We can solve this problem by using sticky sessions. The connection will then immediately be restored by the EventSource in the browser. With server sent events the same problem can occur because the http connection could get dropped. When a polling request comes in the load balancer assigns the request to a different server. Server 1 is getting the request to prepare order 1 and it starts processing it. Let's say your app is scaled out to different servers. A server that might have no knowledge about the messages that were sent earlier to the client and about the context of the message. Each message is a different request and each time a request is made it can turn up at a different server. But when using polling or long polling there might be a problem. Once the web socket is established it is like a tunnel between one server and the browser. When using web sockets there is no problem. The load balancer can pick a different server in sequence or have some other logic going on to pick one. A mechanism called a load balancer will then pick a server on each incoming request. When the app runs in the cloud scaling out is a matter of setting the number of servers you want to run. Scaling out means running the app on multiple servers. When you deploy your app to production at some point you'll want to scale out.
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