Clustering TCP servers, so can send data to all clients - python

Important note:
I've asked this question already on ServerFault: https://serverfault.com/questions/349065/clustering-tcp-servers-so-can-send-data-to-all-clients, but I'd also like a programmers perspective on the problem.
I'm developing a real-time mobile app by setting up a TCP connection between the app and server backend. Each user can send messages to all other users.
(I'm making the TCP server in Python with Twisted, am creating my own 'protocol' for communication between the app/backend and hosting it on Amazon Web Services.)
Currently I'm trying to make the backend scalable (and reliable). As far as I can tell, the system could cope with more users by upgrading to a bigger server (which could become rather limiting), or by adding new servers in a cluster configuration - i.e. having several servers sitting behind a load balancer, probably with 1 database they all access.
I have sketched out the rough architecture of this:
However what if the Red user sends a message to all other connected users? Red's server has a TCP connection with Red, but not with Green.
I can think of a one way to deal with this problem:
Each server could have an open TCP (or SSL) connection with each other server. When one server wants to send a message to all users it simply passes this along it's connection to the other servers. A record could be kept in the database of which servers are online (and their IP address), and one of the servers could be a boss - i.e. decides if others are up and running, if not it could remove them from the database (if a server was up and lost it's connection to the boss it could check the database and see if it had been removed, and restart if it had - else it could assume the boss was down.)
Clearly this needs refinement but shows the general principle.
Alternatively I'm not sure if this is possible (- definitely seems like wishful thinking on my part):
Perhaps users could just connect to a box or router, and all servers could message all users through it?
If you know how to cluster TCP servers effectively, or a design pattern that provides a solution, or have any comments at all, then I would be very grateful. Thank you :-)

You need to decide (or if you already did this - to share these decisions with us) reliability requirements for your system: should all messages be sent to all users in any case (e.g. one or more servers crashed), can you tolerate sending the same message twice to the same user on server crash? Your system complexity depends directly on these decisions.
The simplest version is when a message is not delivered to all users on server crash. All your servers keep TCP connection to each other. One of them receives a message from a user and sends it to all other connected users (to this server) and to all other connected servers. Other servers send this message to all their users. To scale the system you just run additional server which connects to all existing servers.

Have a look how it is handled with IRC servers. They essentially can do this already. Everbody can send to everybody else, on all servers. Or just to single users, also on another server. And to groups, called "channels". It works best by routing amongst the servers.
It's not that hard, if you can make sure the servers know each other and can talk to each other.
On a side note: At 9/11, the most reliable internet news source was the IRC network. All the www sites were down because of bandwidth; it took them ages to even get a plain-text web page back up. During this time, IRC networks were able to provide near real-time, moderated news channels across the atlantic. You maybe could no longer log into a server on the other side, but at least the servers were able to keep up a server-to-server connection across.

An obvious choice is to use the DB as a clearinghouse for messages. You have to store incoming messages somewhere anyway, lest they be lost if a server suddenly crashes. Put incoming messages into the central database and have notification processes on the TCP servers grab the messages and send them to the correct users.

TCP server cannot be clustered, the snapshot you put here is a classic HTTP server example.
Since the device will send TCP connection to server, say, pure socket, there will be noway of establishing a load-balancing server.

Related

Telnet server: is it good practice to keep connections open?

I'm working in a NetHack clone that is supposed to be playing through Telnet, like many NetHack servers. As I've said, this is a clone, so it's being written from scratch, on Python.
I've set up my socket server reusing code from a SMTP server I wrote a while ago and all of suddenly my attention jumped to this particular line of code:
s.listen(15)
My server was designed to be able to connect to 15 simultaneous clients just in case the data exchange with any took too long, but ideally listen(1) or listen(2) would be enough. But this case is different.
As it happens with Alt.org when you telnet their NetHack servers, people connected to my server should be able to play my roguelike remotely, through a single telnet session, so I guess this connection should not be interrupted. Yet, I've read here that
[...] if you are really holding more than 128 queued connect requests you are
a) taking too long to process them or b) need a heavy-weight
distributed server or c) suffering a DDoS attack.
What is the better practice to carry out here? Should I keep every connection open until the connected user disconnects or is there any other way? Should I go for listen(128) (or whatever my system's socket.SOMAXCONN is) or is that a bad practice?
number in listen(number) request limits number of pending connect requests.
Connect request is pending from initial SYN request received by OS until you called accept socket method. So number does not limits open (established) connection number but it limits number of connections in SYN_RECV state.
It is bad idea not to answer on incoming connection because:
Client will retransmit SYN requests until answer SYN is received
Client can not distinguish situation when your server is not available and it just in queue.
Better idea is to answer on connection but send some message to client with rejection reason and then close connection.

Communicating over a local server in python

I am creating a colloabrative note-making app in python.
Here, one guy on computer running the app can create the server subseuqently the changes on the screen([color, pixel], where pixel=[x,y]) will be transmitted to others connected to the server.
I am using kivy for creating the app. My question is with respect to transmitting the data over the server.
I can create server using this:
import socket
ip_address=socket.gethostbyname(socket.gethostname())
execfile( "manage.py runserver "+ip_address+":8000" )
Now, how do others connect to the server and request the data(assuming the above code is correct). Also, how to send the data in django.
Well, Django is a framework that allows creating a site or API that is reachable through HTTP protocol. This has several consequences for you:
Server cannot send a message to client unless the client asks. HTTP is a "request-response" protocol. Client sends a request (for example, http://server.com/getUpdates?id=100500) and gets a response from server.
Creating clients that ask the server to give them updates all the time is a bad practice, probably leading to server DoS.
Although you can use WebSockets, using Django for such a task is really an overkill.
Summarizing, you need a reliable duplex channel for sending data in both directions. I'd start with TCP server, rather than HTTP. Fortunately, Python stdlib has a module you can start with - socketserver.
Additional reading
TCP
UDP (you will probably want this for broadcasting)
Berkeley sockets (a socket standard underlying socketserver module)
TCP vs. UDP
When deciding what protocol to use, following aspects should be considered:
TCP is reliable. Messages never disappear implicitly. If there was a network error, message will be resent. If there's no connection, explicit error will be raised. TCP uses several algorithms to fit into the network channel. It is an intelligent protocol.
UDP is unreliable. It possesses no feature TCP has. Packets can disappear, get reordered. But UDP messages are lightweight and in experienced hands they summon to life such systems as network action games and streaming video (lost and reordered messages aren't crucial here and TCP becomes too slow).
So I'd recommend to start with TCP. It's way more easier to get working fast and correct than UDP. Switch to UDP if you have some experience with TCP and there are a lot of people using you app and wanting to get the lowest latency possible.

Python client-server - tell if client offline

My basic problem is that I am looking for a way for multiple clients to connect to a server over the internet, and for the server to be able to tell if those clients are online or offline.
My current way of doing this is a python socket server, and python clients, which send the server a small message every 2 seconds. The server checks each client to see if it has received such a message in the last 5 seconds, and if not, the client is marked as offline.
However, I feel that is is probably not the best way of doing this, and even if it is, there might be a library that does this for me. I have looked for such a library but have come up empty handed.
Does anyone know of a better way of doing this, or a library which can automatically check the status of multiple connected clients?
Note: by "offline", I mean that the client could be powered off, network connection disconnected or program quit.
Assuming you are not after ping from server to client. I believe that your approach is fine. Very ofther server will not be able to hit client but it works otherway around. You may run out of resources if you have many connected clients.
Also over this established channel you can send other data/metrics and boom monitoring was born ;-) IF you send other data you will probably reliaze you don't need to send data every 2 secs but only if no other data was sent - boom FIX works this way ( and many other messaging protocol)
What you may like is something like kafka that will transport the messages for you there are other messaging protocols too.. and they scale better then if you just connect all client(assuming you have many of them)
Happy messaging
Good Morning i am working a same project and i want to post my approach.
When a client is connected to my server with client, address = sock.accept() we can take his ip with ip_client = address[0]. Assuming you have a list with the connected ips you can append the ip with connected_clients.append(ip_client)
finally you have a list with the connected ips
make a Thread or inside an infinitive loop write the following code
for connected in connected_clients:
response = os.system("ping -c 1 " + connected)
if response == True:
continue
else:
connected_clients.remove(connected)
don't forget to the input os command on the beginning and you have made a beckon of connected clients

Scaling a decoupled realtime server alongside a standard webserver

Say I have a typical web server that serves standard HTML pages to clients, and a websocket server running alongside it used for realtime updates (chat, notifications, etc.).
My general workflow is when something occurs on the main server that triggers the need for a realtime message, the main server sends that message to the realtime server (via a message queue) and the realtime server distributes it to any related connection.
My concern is, if I want to scale things up a bit, and add another realtime server, it seems my only options are:
Have the main server keep track of which realtime server the client
is connected to. When that client receives a notification/chat
message, the main server forwards that message along to only the
realtime server the client is connected to. The downside here is
code complexity, as the main server has to do some extra book
keeping.
Or instead have the main server simply pass that message
along to every realtime server; only the server the client is
connected to would actually do anything with it. This would result
in a number of wasted messages being passed around.
Am I missing another option here? I'm just trying to make sure I don't go too far down one of these paths and realize I'm doing things totally wrong.
If the scenario is
a) The main web server raises a message upon an action (let's say a record is inserted)
b ) He notifies the appropriate real-time server
you could decouple these two steps by using an intermediate pub/sub architecture that forwards the messages to the indended recipient.
An implementation would be
1) You have a redis pub-sub channel where upon a client connecting to a real-time socket, you start listening in that channel
2) When the main app wants to notify a user via the real-time server, it pushes to the channel a message, the real-time server get's it and forwards it to the intended user.
This way, you decouple the realtime notification from the main app and you don't have to keep track of where the user is.
The problem you are describing is the common "message backplane" used for example in SignalR, also related to the "fanout message exchange" in message architectures. When having a backplane or doing fanout, every message is forwarded to every message node server, so clients can connect to any server and get the message. This approach is a reasonable pain when you have to support both long polling and websockets. However, as you noticed, it is a waste of traffic and resources.
You need to use a message infrastructure with intelligent routing, like RabbitMQ. Take a look to topic and header exchange : https://www.rabbitmq.com/tutorials/amqp-concepts.html
How Topic Exchanges Route Messages
RabbitMQ for Windows: Exchange Types
There are tons of different queuing frameworks. Pick the one you like, but ensure you can have more exchange modes than just direct or fanout ;) At the end, a WebSocket is just and endpoint to connect to a message infrastructure. So if you want to scale out, it boils down to the backend you have :)
For just a few realtime servers, you could conceivably just keep a list of them in the main server and just go through them round-robin.
Another approach is to use a load balancer.
Basically, you'll have one dedicated node to receive the requests from the main server, and then have that load-balancer node take care of choosing which websocket/realtime server to forward the request to.
Of course, this just shifts the code complexity from the main server to a new component, but conceptually I think it's better and more decoupled.
Changed the answer because a reply indicated that the "main" and "realtime" servers are alraady load-balanced clusters and not individual hosts.
The central scalability question seems to be:
My general workflow is when something occurs on the main server that triggers the need for a realtime message, the main server sends that message to the realtime server (via a message queue) and the realtime server distributes it to any related connection.
Emphasis on the word "related". Assume you have 10 "main" servers and 50 "realtime" servers, and an event occurs on main server #5: which of the websockets would be considered related to this event?
Worst case is that any event on any "main" server would need to propagate to all websockets. That's a O(N^2) complexity, which counts as a severe scalability impairment.
This O(N^2) complexity can only be prevented if you can group the related connections in groups that don't grow with the cluster size or total nr. of connections. Grouping requires state memory to store to which group(s) does a connection belong.
Remember that there's 3 ways to store state:
global memory (memcached / redis / DB, ...)
sticky routing (load balancer configuration)
client memory (cookies, browser local storage, link/redirect URLs)
Where option 3 counts as the most scalable one because it omits a central state storage.
For passing the messages from "main" to the "realtime" servers, that traffic should by definition be much smaller than the traffic towards the clients. There's also efficient frameworks to push pub/sub traffic.

Which web servers are compatible with gevent and how do the two relate?

I'm looking to start a web project using Flask and its SocketIO plugin, which depends on gevent (something something greenlets), but I don't understand how gevent relates to the webserver. Does using gevent restrict my server choice at all? How does it relate to the different levels of web servers that we have in python (e.g. Nginx/Apache, Gunicorn)?
Thanks for the insight.
First, lets clarify what we are talking about:
gevent is a library to allow the programming of event loops easily. It is a way to immediately return responses without "blocking" the requester.
socket.io is a javascript library create clients that can maintain permanent connections to servers, which send events. Then, the library can react to these events.
greenlet think of this a thread. A way to launch multiple workers that do some tasks.
A highly simplified overview of the entire process follows:
Imagine you are creating a chat client.
You need a way to notify the user's screens when anyone types a message. For this to happen, you need someway to tell all the users when a new message is there to be displayed. That's what socket.io does. You can think of it like a radio that is tuned to a particular frequency. Whenever someone transmits on this frequency, the code does something. In the case of the chat program, it adds the message to the chat box window.
Of course, if you have a radio tuned to a frequency (your client), then you need a radio station/dj to transmit on this frequency. Here is where your flask code comes in. It will create "rooms" and then transmit messages. The clients listen for these messages.
You can also write the server-side ("radio station") code in socket.io using node, but that is out of scope here.
The problem here is that traditionally - a web server works like this:
A user types an address into a browser, and hits enter (or go).
The browser reads the web address, and then using the DNS system, finds the IP address of the server.
It creates a connection to the server, and then sends a request.
The webserver accepts the request.
It does some work, or launches some process (depending on the type of request).
It prepares (or receives) a response from the process.
It sends the response to the client.
It closes the connection.
Between 3 and 8, the client (the browser) is waiting for a response - it is blocked from doing anything else. So if there is a problem somewhere, like say, some server side script is taking too long to process the request, the browser stays stuck on the white page with the loading icon spinning. It can't do anything until the entire process completes. This is just how the web was designed to work.
This kind of 'blocking' architecture works well for 1-to-1 communication. However, for multiple people to keep updated, this blocking doesn't work.
The event libraries (gevent) help with this because they accept and will not block the client; they immediately send a response and when the process is complete.
Your application, however, still needs to notify the client. However, as the connection is closed - you don't have a way to contact the client back.
In order to notify the client and to make sure the client doesn't need to "refresh", a permanent connection should be open - that's what socket.io does. It opens a permanent connection, and is always listening for messages.
So work request comes in from one end - is accepted.
The work is executed and a response is generated by something else (it could be a the same program or another program).
Then, a notification is sent "hey, I'm done with your request - here is the response".
The person from step 1, listens for this message and then does something.
Underneath is all is WebSocket a new full-duplex protocol that enables all this radio/dj functionality.
Things common between WebSockets and HTTP:
Work on the same port (80)
WebSocket requests start off as HTTP requests for the handshake (an upgrade header), but then shift over to the WebSocket protocol - at which point the connection is handed off to a websocket-compatible server.
All your traditional web server has to do is listen for this handshake request, acknowledge it, and then pass the request on to a websocket-compatible server - just like any other normal proxy request.
For Apache, you can use mod_proxy_wstunnel
For nginx versions 1.3+ have websocket support built-in

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