Many Comet implementations like Caplin provide server scalable solutions.
Following is one of the statistics from Caplin site:
A single instance of Caplin liberator can support up to 100,000 clients each receiving 1 message per second with an average latency of less than 7ms.
How does this to compare to HTML5 websockets on any webserver? Can anyone point me to any HTML 5 websockets statistics?
Disclosure - I work for Caplin.
There is a bit of misinformation on this page so I'd like to try and make it clearer..
I think we could split up the methods we are talking about into three camps..
Comet HTTP polling - including long polling
Comet HTTP streaming - server to client messages use a single persistent socket with no HTTP header overhead after initial setup
Comet WebSocket - single bidirectional socket
I see them all as Comet, since Comet is just a paradigm, but since WebSocket came along some people want to treat it like it is different or replaces Comet - but it is just another technique - and unless you are happy only supporting the latest browsers then you can't just rely on WebSocket.
As far as performance is concerned, most benchmarks concentrate on server to client messages - numbers of users, numbers of messages per second, and the latency of those messages. For this scenario there is no fundamental difference between HTTP Streaming and WebSocket - both are writing messages down an open socket with little or no header or overhead.
Long polling can give good latency if the frequency of messages is low. However, if you have two messages (server to client) in quick succession then the second one will not arrive at the client until a new request is made after the first message is received.
I think someone touched on HTTP KeepAlive. This can obviously improve Long polling - you still have the overhead of the roundtrip and headers, but not always the socket creation.
Where WebSocket should improve upon HTTP Streaming in scenarios where there are more client to server messages. Relating these scenarios to the real world creates slightly more arbitrary setups, compared to the simple to understand 'send lots of messages to lots of clients' which everyone can understand. For example, in a trading application, creating a scenario where you include users executing trades (ie client to server messages) is easy, but the results a bit less meaningful than the basic server to client scenarios. Traders are not trying to do 100 trades/sec - so you end up with results like '10000 users receiving 100 messages/sec while also sending a client message once every 5 minutes'. The more interesting part for the client to server message is the latency, since the number of messages required is usually insignificant compared to the server to client messages.
Another point someone made above, about 64k clients, You do not need to do anything clever to support more than 64k sockets on a server - other than configuring the number file descriptors etc. If you were trying to do 64k connection from a single client machine, that is totally different as they need a port number for each one - on the server end it is fine though, that is the listen end, and you can go above 64k sockets fine.
In theory, WebSockets can scale much better than HTTP but there are some caveats and some ways to address those caveats too.
The complexity of the handshake header processing of HTTP vs WebSockets is about the same. The HTTP (and initial WebSocket) handshake can easily be over 1K of data (due to cookies, etc). The important difference is that the HTTP handshake happens again every message. Once a WebSocket connection is established, the overhead per message is only 2-14 bytes.
The excellent Jetty benchmark links posted in #David Titarenco's answer (1, 2) show that WebSockets can easily achieve more than an order of magnitude better latency when compared to Comet.
See this answer for more information on scaling of WebSockets vs HTTP.
Caveats:
WebSocket connections are long-lived unlike HTTP connections which are short-lived. This significantly reduces the overhead (no socket creation and management for every request/response), but it does mean that to scale a server above 64k separate simultaneous client hosts you will need to use tricks like multiple IP addresses on the same server.
Due to security concerns with web intermediaries, browser to server WebSocket messages have all payload data XOR masked. This adds some CPU utilization to the server to decode the messages. However, XOR is one of the most efficient operations in most CPU architectures and there is often hardware assist available. Server to browser messages are not masked and since many uses of WebSockets don't require large amounts of data sent from browser to server, this isn't a big issue.
It's hard to know how that compares to anything because we don't know how big the (average) payload size is. Under the hood (as in how the server is implemented), HTTP streaming and websockets are virtually identical - apart from the initial handshake which is more complicated when done with HTTP obviously.
If you wrote your own websocket server in C (ala Caplin), you could probably reach those numbers without too much difficulty. Most websocket implementations are done through existing server packages (like Jetty) so the comparison wouldn't really be fair.
Some benchmarks:
http://webtide.intalio.com/2011/09/cometd-2-4-0-websocket-benchmarks/
http://webtide.intalio.com/2011/08/prelim-cometd-websocket-benchmarks/
However, if you look at C event lib benchmarks, like libev and libevent, the numbers look significantly sexier:
http://libev.schmorp.de/bench.html
Ignoring any form of polling, which as explained elsewhere, can introduce latency when the update rate is high, the three most common techniques for JavaScript streaming are:
WebSocket
Comet XHR/XDR streaming
Comet Forever IFrame
WebSocket is by far the cleanest solution, but there are still issues in terms of browser and network infrastructure not supporting it. The sooner it can be relied upon the better.
XHR/XDR & Forever IFrame are both fine for pushing data to clients from the server, but require various hacks to be made to work consistently across all browsers. In my experience these Comet approaches are always slightly slower than WebSockets not least because there is a lot more client side JavaScript code required to make it work - from the server's perspective, however, sending data over the wire happens at the same speed.
Here are some more WebSocket benchmark graphs, this time for our product my-Channels Nirvana.
Skip past the multicast and binary data graphs down to the last graph on the page (JavaScript High Update Rate)
In summary - The results show Nirvana WebSocket delivering 50 events/sec to 2,500k users with 800 microsecond latency. At 5,000 users (total of 250k events/sec streamed) the latency is 2 milliseconds.
Related
I'm looking for a way to implement basic Publish / Subscribe between applications written in different languages, to exchange events with JSON payloads.
WebSocket seems like the obvious choice for the transport, but you need an (arguably small) layer on top to implement some of the plumbing:
aggreeing on messages representing the pubsub domain "subscribe to a topic", "publish a message"
aggreeing on messages for the infra ("heartbeat", "authentication")
I was expecting to find an obvious standard for this, but there does not seem to be any.
WAMP is often refered to, but in my (short) experience, the implementations of server / clients libraries are not great
STOMP is often refered to, but in my (even shorter) experience, it's even worse
Phoenix Channels are nice, but they're restricted to Phoenix/Elixir world, and not standard (so the messages can be changed at any phoenix version without notice.)
So, is everyone using MQTT/WS (which require another broker components, rather than simple servers ?) Or gRPC ?
Is everyone just re-implementing it from scratch ? (It's one of those things that seems easy enough to do oneselves, but I guess you just end up with an half-baked, poorly-specified, broken version of the thing I'm looking for...)
Or is there something fundamentally broken with the idea of serving streams of data from a server over WS ?
There are two primary classes of WebSocket libraries; those that implement the protocol and leave the rest to the developer, and those that build on top of the protocol with various additional features commonly required by realtime messaging applications, such as restoring lost connections, pub/sub, and channels, authentication, authorization, etc.
The latter variety often requires that their own libraries be used on the client-side, rather than just using the raw WebSocket API provided by the browser. As such, it becomes crucial to make sure you’re happy with how they work and what they’re offering. You may find yourself locked into your chosen solution’s way of doing things once it has been integrated into your architecture, and any issues with reliability, performance, and extensibility may come back to bite you.
ws, faye-websockets, socket.io, μWebSockets and SocketCluster are some good open-source options.
The number of concurrent connections a server can handle is rarely the bottleneck when it comes to server load. Most decent WebSocket servers can support thousands of concurrent connections, but what’s the workload required to process and respond to messages once the WebSocket server process has handled receipt of the actual data?
Typically there will be all kinds of potential concerns, such as reading and writing to and from a database, integration with a game server, allocation and management of resources for each client, and so forth.
As soon as one machine is unable to cope with the workload, you’ll need to start adding additional servers, which means now you’ll need to start thinking about load-balancing, synchronization of messages among clients connected to different servers, generalized access to client state irrespective of connection lifespan or the specific server that the client is connected to – the list goes on and on.
There’s a lot involved when implementing support for the WebSocket protocol, not just in terms of client and server implementation details, but also with respect to support for other transports to ensure robust support for different client environments, as well as broader concerns, such as authentication and authorization, guaranteed message delivery, reliable message ordering, historical message retention, and so forth. A data stream network such as Ably Realtime would be a good option to use in such cases if you'd rather avoid re-inventing the wheel.
There's a nice piece on WebSockets, Pub/Sub, and all issues related to scaling that I'd recommend reading.
Full disclosure: I'm a Developer Advocate for Ably but I hope this genuinely answers your question.
When writing a web crawler/scraper, what algorithms and techniques are available to throttle requests and avoid DoS'ing the server/getting banned? This comes up often when reading about web scraping (for example, here), but always as something like "I should have implemented throttling, but didn't" :)
My Google-fu may be weak, as I found mostly discussions on how to throttle requests server-side, and others (like this question) are specific about some library.
The most generic, cross-language way is to sleep between requests. Something like 10 seconds sleep should mimic how fast a real human goes through web pages. To avoid robot identifying algorithms some people sleep a random amount of time: sleep(ten_seconds + rand()).
You can make it fancier by keeping track of different sleep timeouts for each domain so that you can fetch something from another server while waiting for the sleep timeout.
The second method is to actually try to reduce the bandwidth for your request. You may need to write your own http client with this feature to do it. Or on linux you can use the network stack to do it for you - google qdisc.
You can of course combine both methods.
Note that reducing bandwidth is not very friendly to sites with lots of small resources. That's because you're increasing the amount of time you're connected for each resource hence occupying one network socket and probably one web server thread while you're at it.
On the other hand not reducing bandwidth is not very friendly to sites with lots of large resources like mp3 files or videos. That's because you're saturating their network - switches, routers, ISP connection - by downloading as fast as they can serve.
A smart implementation will download small files at full speed, sleeping between downloads, but reduce bandwidth for large files.
Some time ago I read about some work done to cut down on the web client to web server chatter by combining client requests or server responses to help reduce latency.
Basically the web client would merge its requests into one larger request and/or the server could combine its responses to the webclient into one larger response.
The idea being to reduce chatter and latency in real time.
I am either searching for the wrong thing or just dreaming but my search attempts are coming up empty.
I ask as a developer because I would prefer to enable such a technology rather then having to manually code it myself. We have an app that has the potential to be very chatty.
Search terms I tried are: Request Merging/Combining, Response Merging/Combining, Write Combining for Web, and many others...
Note: I am NOT taking about merging static JS/CSS or even Image files (sprites) at compile time.
A persistent connection enables a client to send multiple requests over the socket. Other possibilities include pipelining and/or WebSocket.
We're playing around with WebRTC and trying to understand its benefits.
One reason Skype can serve hundreds of millions of people is because of its decentralized, peer-to-peer architecture, which keeps server costs down.
Does WebRTC allow people to build a video chat application similar to Skype in that the architecture can be decentralized (i.e., video streams are not routed from a broadcaster through a central server to listeners but rather routed directly from broadcaster to listener)?
Or, put another way, does WebRTC allow someone to essentially replicate the benefits of a P2P architecture similar to Skype's?
Or do you still need something similar to Skype's P2P architecture?
Yes, that's basically what WebRTC does. Calls using the getPeerConnection() API don't send voice/video data through a centralized server, but rather use firewall traversal protocols like ICE, STUN and TURN to allow a direct, peer-to-peer connection. However, the initial call setup still requires a server (most likely something running a WebSocket implementation, but it could be anything that you can figure out how to get JavaScript to talk to), so that the two clients can figure out that they're both online, signal that they want to connect, and then figure out how to do it (this is where the ICE/STUN/TURN bit comes in).
However, there's more to Skype's P2P architecture than just passing voice/video data back and forth. The majority of Skype's IP isn't in the codecs or protocols (much of which they licensed from Global IP Solutions, which Google purchased two years ago and then open-sourced, and which forms of the basis of Chrome's WebRTC implementation). Skype's real IP is all in the piece of WebRTC which still depends on a server: figuring out which people are online, and where they are, and how to get a hold of them, and doing that in a massively decentralized fashion. (See here for some rough details.) I think that you could probably use the DataStream portion of the getPeerConnection() API to do that sort of thing, if you were really, really smart - but it would be complicated, and would most likely stomp on a few Skype patents. Unless you want to be really, really huge, you'd probably just want to run your own centralized presence and location servers and handle all that stuff through standard WebSockets.
I should note that Skype's network architecture has changed since it was created; it no longer (from what I hear) uses random users as supernodes to relay data from client 1 to client 2; it didn't scale well and caused rampant variability in results (and annoyed people who had non-firewalled connections and bandwidth).
You definitely can build something SKype-like with WebRTC - and more. :-)
I am curious if anyone has any information about the scalability of HTML WebSockets. For everything I've read it appears that every client will maintain an open line of communication with the server. I'm just wondering how that scales and how many open WebSocket connections a server can handle. Maybe leaving those connections open isn't a problem in reality, but it feels like it is.
In most ways WebSockets will probably scale better than AJAX/HTML requests. However, that doesn't mean WebSockets is a replacement for all uses of AJAX/HTML.
Each TCP connection in itself consumes very little in terms server resources. Often setting up the connection can be expensive but maintaining an idle connection it is almost free. The first limitation that is usually encountered is the maximum number of file descriptors (sockets consume file descriptors) that can be open simultaneously. This often defaults to 1024 but can easily be configured higher.
Ever tried configuring a web server to support tens of thousands of simultaneous AJAX clients? Change those clients into WebSockets clients and it just might be feasible.
HTTP connections, while they don't create open files or consume port numbers for a long period, are more expensive in just about every other way:
Each HTTP connection carries a lot of baggage that isn't used most of the time: cookies, content type, conetent length, user-agent, server id, date, last-modified, etc. Once a WebSockets connection is established, only the data required by the application needs to be sent back and forth.
Typically, HTTP servers are configured to log the start and completion of every HTTP request taking up disk and CPU time. It will become standard to log the start and completion of WebSockets data, but while the WebSockets connection doing duplex transfer there won't be any additional logging overhead (except by the application/service if it is designed to do so).
Typically, interactive applications that use AJAX either continuously poll or use some sort of long-poll mechanism. WebSockets is a much cleaner (and lower resource) way of doing a more event'd model where the server and client notify each other when they have something to report over the existing connection.
Most of the popular web servers in production have a pool of processes (or threads) for handling HTTP requests. As pressure increases the size of the pool will be increased because each process/thread handles one HTTP request at a time. Each additional process/thread uses more memory and creating new processes/threads is quite a bit more expensive than creating new socket connections (which those process/threads still have to do). Most of the popular WebSockets server frameworks are going the event'd route which tends to scale and perform better.
The primary benefit of WebSockets will be lower latency connections for interactive web applications. It will scale better and consume less server resources than HTTP AJAX/long-poll (assuming the application/server is designed properly), but IMO lower latency is the primary benefit of WebSockets because it will enable new classes of web applications that are not possible with the current overhead and latency of AJAX/long-poll.
Once the WebSockets standard becomes more finalized and has broader support, it will make sense to use it for most new interactive web applications that need to communicate frequently with the server. For existing interactive web applications it will really depend on how well the current AJAX/long-poll model is working. The effort to convert will be non-trivial so in many cases the cost just won't be worth the benefit.
Update:
Useful link: 600k concurrent websocket connections on AWS using Node.js
Just a clarification: the number of client connections that a server can support has nothing to do with ports in this scenario, since the server is [typically] only listening for WS/WSS connections on one single port. I think what the other commenters meant to refer to were file descriptors. You can set the maximum number of file descriptors quite high, but then you have to watch out for socket buffer sizes adding up for each open TCP/IP socket. Here's some additional info: https://serverfault.com/questions/48717/practical-maximum-open-file-descriptors-ulimit-n-for-a-high-volume-system
As for decreased latency via WS vs. HTTP, it's true since there's no more parsing of HTTP headers beyond the initial WS handshake. Plus, as more and more packets are successfully sent, the TCP congestion window widens, effectively reducing the RTT.
Any modern single server is able to server thousands of clients at once. Its HTTP server software has just to be is Event-Driven (IOCP) oriented (we are not in the old Apache one connection = one thread/process equation any more). Even the HTTP server built in Windows (http.sys) is IOCP oriented and very efficient (running in kernel mode). From this point of view, there won't be a lot of difference at scaling between WebSockets and regular HTTP connection. One TCP/IP connection uses a little resource (much less than a thread), and modern OS are optimized for handling a lot of concurrent connections: WebSockets and HTTP are just OSI 7 application layer protocols, inheriting from this TCP/IP specifications.
But, from experiment, I've seen two main problems with WebSockets:
They do not support CDN;
They have potential security issues.
So I would recommend the following, for any project:
Use WebSockets for client notifications only (with a fallback mechanism to long-polling - there are plenty of libraries around);
Use RESTful / JSON for all other data, using a CDN or proxies for cache.
In practice, full WebSockets applications do not scale well. Just use WebSockets for what they were designed to: push notifications from the server to the client.
About the potential problems of using WebSockets:
1. Consider using a CDN
Today (almost 4 years later), web scaling involves using Content Delivery Network (CDN) front ends, not only for static content (html,css,js) but also your (JSON) application data.
Of course, you won't put all your data on your CDN cache, but in practice, a lot of common content won't change often. I suspect that 80% of your REST resources may be cached... Even a one minute (or 30 seconds) CDN expiration timeout may be enough to give your central server a new live, and enhance the application responsiveness a lot, since CDN can be geographically tuned...
To my knowledge, there is no WebSockets support in CDN yet, and I suspect it would never be. WebSockets are statefull, whereas HTTP is stateless, so is much easily cached. In fact, to make WebSockets CDN-friendly, you may need to switch to a stateless RESTful approach... which would not be WebSockets any more.
2. Security issues
WebSockets have potential security issues, especially about DOS attacks. For illustration about new security vulnerabilities , see this set of slides and this webkit ticket.
WebSockets avoid any chance of packet inspection at OSI 7 application layer level, which comes to be pretty standard nowadays, in any business security. In fact, WebSockets makes the transmission obfuscated, so may be a major breach of security leak.
Think of it this way: what is cheaper, keeping an open connection, or opening a new connection for every request (with the negotiation overhead of doing so, remember it's TCP.)
Of course it depends on the application, but for long-term realtime connections (e.g. an AJAX chat) it's far better to keep the connection open.
The max number of connections will be capped by the max number of free ports for the sockets.
No it does not scale, gives tremendous work to intermediate routes switches. Then on the server side the page faults (you have to keep all those descriptors) are reaching high values, and the time to bring a resource into the work area increases. These are mostly JAVA written servers and it might be faster to hold on those gazilions of sockets then to destroy/create one.
When you run such a server on a machine any other process can't move anymore.