Ideas for scaling chat in AWS?

Question

I'm trying to come up with the best solution for scaling a chat service in AWS. I've come up with a couple potential solutions:

1. Redis Pub/Sub - When a user establishes a connection to a server that server subscribes to that user's ID. When someone sends a message to that user, a server will perform a publish to the channel with the user's id. The server the user is connected to will receive the message and push it down to the appropriate client.

2. SQS - I've thought of creating a queue for each user. The server the user is connected to will poll (or use SQS long-polling) that queue. When a new message is discovered, it will be pushed to the user from the server.

3. SNS - I really liked this solution until I discovered the 100 topic limit. I would need to create a topic for each user, which would only support 100 users.

Are their any other ways chat could be scaled using AWS? Is the SQS approach viable? How long does it take AWS to add a message to a queue?

Answer 1

the way i would implement such a thing (if not using some framework) is the following:

have a webserver (on ec2) which accepts the msgs from the user. use Autoscalling group on this webserver. the webserver can update any DB on amazon RDS which can scale easily.

if you are using your own db, you might consider to decouple the db from the webserver using the sqs (by sending all requests the same queue), and then u can have a consumer which consume the queue. this consumer can also be placed behind an autoscalling group, so that if the queue is larger than X msgs, it will scale (u can set it up with alarms)

sqs normally updates pretty fast i.e less than one second. (from the moment u sent it, to the moment it appears on the on the queue), and rarely more than that.

Answer 2

Building a chat service isn't as easy as you would think.

I've built full XMPP servers, clients, and SDK's and can attest to some of the subtle and difficult problems that arise. A prototype where users see each other and chat is easy. A full features system with account creation, security, discovery, presence, offline delivery, and friend lists is much more of a challenge. To then scale that across an arbitrary number of servers is especially difficult.

PubSub is a feature offered by Chat Services (see XEP-60) rather than a traditional means of building a chat service. I can see the allure, but PubSub can have drawbacks.

Some questions for you: 1. Are you doing this over the Web? Are users going to be connecting and long-poling or do you have a Web Sockets solution?

2. How many users? How many connections per user? Ratio of writes to reads?

3. Your idea for using SQS that way is interesting, but probably won't scale. It's not unusual to have 50k or more users on a chat server. If you're polling each SQS Queue for each user you're not going to get anywhere near that. You would be better off having a queue for each server, and the server polls only that queue. Then it's on you to figure out what server a user is on and put the message into the right queue.

I suspect you'll want to go something like:

1. A big RDS database on the backend.
2. A bunch of front-end servers handling the client connections.
3. Some middle tier Java / C# code tracking everything and routing messages to the right place.

To get an idea of the complexity of building a chat server read the XMPP RFC's: RFC 3920 RFC 3921

Answer 3

SQS/ SNS might not fit your chatty requirement. we have observed some latency in SQS which might not be suitable for a chat application. Also SQS does not guarantee FIFO. i have worked with Redis on AWS. It is quite easy and stable if it is configured taking all the best practices in mind.

Answer 4

Since a new AWS IoT service started to support WebSockets, Keepalive and Pub/Sub couple months ago, you may easily build elastic chat on it. AWS IoT is a managed service with lots of SDKs for different languages including JavaScript that was build to handle monster loads (billions of messages) with zero administration.

You can read more about update here:

https://aws.amazon.com/ru/about-aws/whats-new/2016/01/aws-iot-now-supports-websockets-custom-keepalive-intervals-and-enhanced-console/

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Edit:

Last SQS update (2016/11): you can now use Amazon Simple Queue Service (SQS) for applications that require messages to be processed in a strict sequence and exactly once using First-in, First-out (FIFO) queues. FIFO queues are designed to ensure that the order in which messages are sent and received is strictly preserved and that each message is processed exactly once.

Source: https://aws.amazon.com/about-aws/whats-new/2016/11/amazon-sqs-introduces-fifo-queues-with-exactly-once-processing-and-lower-prices-for-standard-queues/

Now on, implementing SQS + SNS looks like a good idea too.

Answer 5

I've thought about building a chat server using SNS, but instead of doing one topic per user, as you describe, doing one topic for the entire chat system and having each server subscribe to the topic - where each server is running some sort of long polling or web sockets chat system. Then, when an event occurs, the data is sent in the payload of the SNS notification. The server can then use this payload to determine what clients in its queue should receive the response, leaving any unrelated clients untouched. I actually built a small prototype for this, but haven't done a ton of testing to see if it's robust enough for a large number of users.

Answer 6

HI realtime chat doesn't work well with SNS. It's designed for email/SMS or service 1 or a few seconds latency is acceptable. In realtime chat, 1 or a few seconds are not acceptable.

check this link

Latency (i.e. “Realtime”) for PubNub vs SNS

Amazon SNS provides no latency guarantees, and the vast majority of latencies are measured over 1 second, and often many seconds slower. Again, this is somewhat irrelevant; Amazon SNS is designed for server-to-server (or email/SMS) notifications, where a latency of many seconds is often acceptable and expected.

Because PubNub delivers data via an existing, established open network socket, latencies are under 0.25 seconds from publish to subscribe in the 95% percentile of the subscribed devices. Most humans perceive something as “realtime” if the event is perceived within 0.6 – 0.7 seconds.