Take Twitter for example, they say twitter.com as a client of their own API. Could this be one of the reason why Twitter is quite 'slow'?
Reference: http://engineering.twitter.com/2010/09/tech-behind-new-twittercom.html
Would you recommend using your own API for you main website/app?
If using own API is OK, what are the ways to avoid performance issues?
Regarding using your own API: It's about trade offs. In the twitter example by using their own API they were able to "allocate more resources to the API team." That benefit for them outweighed a performance hit. There are other benefits not mentioned either, Like, being the first to vet your api and having a single unified entry point into the system. There are drawbacks as well that are mentioned in the link you posted.
For your application you should look at the architectural qualities you want to achieve and balance that with the constraints you are given and make your own choice. If ultra high performance is at the top of the list then craft your solution to meet that goal.
Regarding performance when using your own API: Again it depends. In the twitter case they knew they would be accessing the API in JavaScript. So the physical jumps are Browser --> Server --> DB. There is no way to get around these hops if you are doing client-server development. In the link you posted they talked about going directly to the DB. Yes that would be faster, but I'm not sure how to do that from a javascript client. I suppose if they had used websockets to a custom API then that would have been faster, but at what development cost.
Summary So it's not that they are using their own API that was the performance hit, it was that they wanted the client to be an HTTP hop away.
Please note that none of these comments talk about what the server --> db calls look like or their caching strategy, or any of the other dozen things which could be a bottleneck
Related
I'm looking the best more efficient way to implement (or use an already setup) rate limiter that would protect all my rest api url. the protection I'm looking at is a "call per second per user limiter"
I had a look on the net and what comes out was the use of either "Redis" or Guava RateLimiter.
To be honest I have never used Redis and I'am really not familiar with it. But by looking on its docs it seems that it has a quite robust rate limiter system.
I have also had a look at Guava's RateLimiter. And it looks a bit easier to use (don't need a redis installation etc...)
So I would like some suggestion of what would be "in my case" the best solution? Is using Redis "too much"?
Have any of you already tried RateLimter? Is this a good solution? Is it scaleable?
PS: I am also open to other solutions than the 2 I aforementioned if you think there are better choices.
Thank you!
If you are trying to limit access to your Spring-based REST api you should use token-bucket algorithm.
There is bucket4j-spring-boot-starter project which uses bucket4j library to rate-limit access to the REST api. You can configure it via application properties file. There is an option to limit the access based on IP address or username.
If you are using Netflix Zuul you could use Spring Cloud Zuul RateLimit which uses different storage options: Consul, Redis, Spring Data and Bucket4j.
Guava’s RateLimiter blocks the current thread so if there’s a burst of asynchronous calls against the throttled service lots of threads will be blocked and might result exhaust of free threads.
Perhaps Spring-based library Kite meets your needs. Kite's "rate-limiting throttle" rejects requests after the principal reaches a configurable limit on the number of requests in some time period. The rate limiter uses Spring Security to determine the principal involved.
But Kite is still a single-JVM approach. If you do need a cluster-aware approach Redis is a way to go.
there is no hard rule, it totally depends on your specific situation. provided that "I have never used Redis", I would recommend guava RateLimiter. compare to redis, a completely new nosql system for you, guava RateLimiter is much easier to get started with. by adding a few lines of code, you are enable to distribute permits at a configurable rate. what left to do is to adapt it to fit your need, like providing rate limit on a per user basis.
I am working with geocoder gem and like to process more number of requests from an IP. By default Google API provides only 2500 requests per day.
Please share your thoughts on how I can do more requests than the limit?
As stated before: Using only Google API the only way around the limitation is to pay for it. Or in a more shady way make the requests form more than one IP/API-Key which i would not recommend.
But to stay on the save side i would suggest mixing the services up since there a few more Geocoding APIs out there - for free.
With the right gem mixing them is also not a big issue:
http://www.rubygeocoder.com/
Supports a couple of them with a nice interface. You would pretty much only have to add some rate-limiting counters making sure you stay within the limits of each provider.
Or go the heavy way of implementing your own geocoding. With for example your own running Openstreetmaps database. The Database can be downloaded here: http://wiki.openstreetmap.org/wiki/Planet.osm#Worldwide_data
Which is the best way depends on what your actual requirements are and what ressources you have available.
When we do single page application, the webserver basically does only one things, it gives some data when the client asks them (using JSON format for example). So any server side language (php, ror) or tool (apache, ningx) can do it.
But is there a language/tool that works better with this sorts of single page applications that generates lot of small requests that need low latency and sometimes permanent connection (for realtime and push things)?
SocketStream seems like it matches your requirements quite well: "A phenomenally fast real-time web framework for Node.js ... dedicated to creating single-page real time websites."
SocketStream uses WebSockets to get lowest latency for the real-time portion. There are several examples on the site to build from.
If you want a lot of small requests in realtime by pushing data - you should take a look at socket type connections.
Check out Node.js with Socket.io.
If you really want to optimize for speed, you could try implementing a custom HTTP server that just fits your needs, for example with the help of Netty.
It's blazingly fast and has examples for HTTP and WebSocket servers included.
Also, taking a look at GWAN may be worthwile (though I have not tried that one yet).
http://en.wikipedia.org/wiki/Nginx could be appropriate
I'm working on the design of a web app which will be using AJAX to communicate with a server on an embedded device. But for one feature, the client will need to get very frequent updates (>10 per second), as close to real time as possible, for an extended period of time. Meanwhile typical AJAX requests will need to be handled from time to time.
Some considerations unique to this project:
This data will be very small, probably no more than a single numeric value.
There will only be 1 client connected to the server at a time, so scaling is not an issue.
The client and server will reside on the same local network, so the connection will be fast and reliable.
The app will be designed for Android devices, so we can take advantage of any platform-specific browser features.
The backend will most likely be implemented in Python using WSGI on Apache or lighttpd, but that is still open for discussion.
I'm looking into Comet techniques including XHL long polling and hidden iframe but I'm pretty new to web development and I don't know what kind of performance we can expect. The server shouldn't have any problem preparing the data, it's just a matter of pushing it out to the client as quickly as possible. Is 10 updates per second an unreasonable expectation for any of the Comet techniques, or even regular AJAX polling? Or is there another method you would suggest?
I realize this is ultimately going to take some prototyping, but if someone can give me a ball-park estimate or better yet specific technologies (client and server side) that would provide the best performance in this case, that would be a great help.
You may want to consider WebSockets. That way you wouldn't have to poll, you would receive data directly from your server. I'm not sure what server implementations are available at this point since it's still a pretty new technology, but I found a blog post about a library for WebSockets on Android:
http://anismiles.wordpress.com/2011/02/03/websocket-support-in-android%E2%80%99s-phonegap-apps/
For a Python back end, you might want to look into Twisted. I would also recommend the WebSocket approach, but failing that, and since you seem to be focused on a browser client, I would default to HTTP Streaming rather than polling or long-polls. This jQuery Plugin implements an http streaming Ajax client and claims specifically to support Twisted.
I am not sure if this would be helpful at all but you may want to try Comet style ajax
http://ajaxian.com/archives/comet-a-new-approach-to-ajax-applications
I'm starting to step into unfamiliar territory with regards to performance improvement and our RIA (Rich Internet Application) built with GWT. For those unfamiliar with GWT, essentially when deployed it's just pure JavaScript. We're interfacing with the server side using a REST-style XML web service via XMLHttpRequest.
Our XML is un-marshalled into JavaScript objects and used within the application to represent the data model behind the interface. When changes occur, the model is updated and marshalled back to XML and sent back to the server.
I've learned the number one rule of performance (in terms of user experience) is to make as few requests as possible. Obviously this brings up the possibility of caching. Caching is great for static data but things get tricky in a multi-user system where data on the server may be changing. Also, use of "Last-Modified" and "If-Modified-Since" requests don't quite do enough since we'd like to avoid unnecessary requests altogether.
I'm trying to figure out if caching data in the browser is even right for us before researching the approaches. I hope someone has tread this path before. I'm looking for similar approaches, lessons learned, things to avoid, etc.
I'm happy to provide more specific info if needed...
For GWT, if performance matters that much to you, you get better performance by sending all the data you need in a single request, instead of querying multiple small data. I would recommend against client-side data caching as there are lots of issues like keeping the data in sync with the database.
Besides, you already have a good advantage with GWT over traditional html apps. Unless you are dealing with special data (eg: does not become stale too quickly - implies mostly-read queries) I found out that there is no special need for caching. You are better off doing a service-layer caching, since most of the time should come of server-side processing.
If you can provide more details about the nature of the app, maybe some different conclusions can be taken.