i have a website what can be used by 50 users at the same time. Those users will be in the same room.
My problem is to know how much bandwith (in Mb/s) do I need to rent for that room so that they can access my website comfortably (speed up and down) ?
The average page size of my website is 1MB.
I searched for answers on the internet and all I got was bandwith used in a month (for servers).
Sorry if my question is "vague", I did my best to make it clear.
Thank you in advance for your answers.
Using https://gtmetrix.com/ you can test your websites speed, page size, and load times
There are several alternatives you just have to do the research
The more important issue you should focus on is why your page is 1Mb that should be your first priority to resolve and using tools like gtmetrix can help
I recommend load testing your site to figure that out. If you're at all familiar with JMeter, you can use it to create a script that simulates a user navigating your site, then run multiple instances of that user (in your case, 50) to see how the site holds up under load.
You can learn more about JMeter here:
https://jmeter.apache.org/
If you're not familiar with creating JMeter scripts, you can record and auto-generate basic scripts using the Blazemeter Chrome Extension, here.
For low-load testing (50 users is pretty low), you can upload your JMeter script to Blazemeter, and with a free tier Blazemeter account, you can perform some basic tests to see how your site holds up. If you go that route, I recommend focusing on avg. response time and hits/second in order to determine what your bandwidth need truly is under load.
For small app they are no problem.
But for apps with traffic you can hit limits easily.
Http protocol is req-res driven. Just because your backend is stuck with limit, you can't really wait to send respond back until rate limit allows you to resume making your api calls.
What do you do?
I can think of several scenarios:
Wait it out: while it sucks, but sometimes it's easy fix, as you don't need to do anything.
Queue it: this a lot of work oppose to making just api call. This requires that first you store it in database, then have background task go through database and do the task. Also user would be told "it is processing" not "it's done"
Use lot of apis: very hacky... and lot of trouble to manage. Say you are using amazon, now you would have to create, verify, validate like 10 accounts. Not even possible for where you need to verify with say domain name. Since amazon would know account abc already owns it.
To expand on what your queueing options are:
Unless you can design the problem of hitting this rate limit out of existence as #Hammerbot walks through, I would go with some implementation of queue. The solution can scale in complexity and robustness according to what loads you're facing and how many rate limited APIs you're dealing with.
Recommended
You use some library to take care of this for you. Node-rate-limiter looks promising. It still appears you would have to worry about how you handle your user interaction (make them wait, write to a db/cache-service and notify them later).
"Simplest case" - not recommended
You can implement a minimally functioning queue and back it with a database or cache. I've done this before and it was fine, initially. Just remember you'll run into needing to implement your own retry logic, will have to worry about things like queue starvation **. Basically, the caveats of rolling your own < insert thing whose implementation someone already worried about > should be taken into consideration.
**(e.g. your calls keep failing for some reason and all of a sudden your background process is endlessly retrying large numbers of failing queue work elements and your app runs out of memory).
Complex case:
You have a bunch of API calls that all get rate-limited and those calls are all made at volumes that make you start considering decoupling your architecture so that your user-facing app doesn't have to worry about handling this asynchronous background processing.
High-level architecture:
Your user-facing server pushes work units of different type onto different queues. Each of these queues corresponds to a differently rate-limited processing (e.g. 10 queries per hour, 1000 queries per day). You then have a "rate-limit service" that acts as a gate to consuming work units off the different queues. Horizontally distributed workers then only consume items from the queues if and only if the rate limit service says they can. The results of these workers could then be written to a database and you could have some background process to then notify your users of the result of the asynchronous work you had to perform.
Of course, in this case you're wading into a whole world of infrastructure concerns.
For further reading, you could use Lyft's rate-limiting service (which I think implements the token bucket algorithm to handle rate limiting). You could use Amazon's simple queueing service for the queues and Amazon lambda as the queue consumers.
There are two reasons why rate limits may cause you problems.
Chronic: (that is, a sustained situation). You are hitting rate limits because your sustained demand exceeds your allowance.
In this case, consider a local cache, so you don't ask for the same thing twice. Hopefully the API you are using has a reliable "last-modified" date so you can detect when your cache is stale. With this approach, your API calling is to refresh your cache, and you serve requests from your cache.
If that can't help, you need higher rate limits
Acute: your application makes bursts of calls that exceed the rate limit, but on average your demand is under the limit. So you have a short term problem. I have settled on a brute-force solution for this ("shoot first, ask permission later"). I burst until I hit the rate limit, then I use retry logic, which is easy as my preferred tool is python, which supports this easily. The returned error is trapped and retry handling takes over. I think every mature library would have something like this.
https://urllib3.readthedocs.io/en/latest/reference/urllib3.util.html
The default retry logic is to backoff in increasingly big steps of time.
This has a starvation risk, I think. That is, if there are multiple clients using the same API, they share the same rate limit as a pool. On your nth retry, your backoff may be so long that newer clients with shorter backoff times are stealing your slots ... by the time your long backoff time expires, the rate limit has already been consumed by a younger competitor, so you now retry even longer, making the problem worse,although at the limit, this just means the same as the chronic situation: the real problem is your total rate limit is insufficient, but you might not be sharing fairly among jobs due to starvation. An improvement is to provide a less naive algorithm, it's the same locking problem that you do in computer science (introducing randomisation is a big improvement). Once again, a mature library is aware of this and should help with built-in retry options.
I think that this depends on which API you want to call and for what data.
For example, Facebook limits their API call to 200 requests per hour and per user. So if your app grows, and you are using their OAuth implementation correctly, you shouldn't be limited here.
Now, what data do you need? Do you really need to make all these calls? Is the information you call somewhat storable on any of your server?
Let's imagine that you need to display an Instagram feed on a website. So at each visitor request, you reach Instagram to get the pictures you need. And when your app grows, you reach the API limit because you have more visitors than what the Instagram API allows. In this case, you should definitely store the data on your server once per hour, and let your users reach your database rather than Instagram's one.
Now let's say that you need specific information for every user at each request. Isn't it possible to let that user handle his connection to the API's? Either by implementing the OAuth 2 flow of the API or by asking the user their API informations (not very secure I think...)?
Finally, if you really can't change the way you are working now, I don't see any other options that the ones you listed here.
EDIT: And Finally, as #Eric Stein stated in his comment, some APIs allow you to rise your API limit by paying (a lot of SaaS do that), so if your app grows, you should afford to pay for those services (they are delivering value to you, it's fair to pay them back)
Wondering if this is at all possible. I'm working on a Chrome extension where, as users browse a particular site, certain elements on the page are saved to chrome.storage.local (or chrome.storage.sync). Those elements are then called again later on a different page. However, it would be useful to allow all users to save this data to 1 global variable/source, and all users be able to read from that variable/source. Do Chrome extensions have any method of accomplishing this?
The data in question isn't anything sensitive, it's not authentication info or anything. The reason I'm hoping to do this and not just save static variables or JSON objects within a content script is that the website I'm building this for changes fairly frequently, and I would rather that data not be completely static.
Thank you!
Not possible natively but there are lots of ways to do it for free (given you have few users and load and assuming you dont surpass their free quotas or rate limits) like a google appengine backend or a public google spreadsheet as sync. For the spreadsheet case, you can store as rows or put everything on a single cell. For appengine, the datastore has free quotas for read/write and free store quota (with limits and rate limits of course).
I was wondering how much do you win by putting all of your css scripts and stuff that needs to be downloaded in one file?
I know that you would win a lot by using sprites, but at some point it might actually hurt to do that.
For example my website uses a lot of small icons and most of the pages has different icons after combining all those icons together i might get over 500kb in total, but if i make one sprite per page it is reduced to almost 50kb/page so that's cool.
But what about scripts js/css how much would i win by making a script for each page which has just over ~100 lines? Or maybe i wouldn't win at all?
Question, basically i want to know how much does a single request cost to download a file and is it really bad to to have many script/image files with todays modern browsers and a high speed connections.
EDIT
Thank you all for your answers, it was hard to chose just one because every answer did answer my question, I chose to reward the one that in my opinion answered my question about request cost the most directly, I will not accept any answer as correct because everyone was.
Multiple requests means more latency, so that will often make a difference. Exactly how costly that is will depend on the size of the response, the performance of the server, where in the world it's hosted, whether it's been cached, etc... To get real measurements you should experiment with your real world examples.
I often use PageSpeed, and generally follow the documented best practices: https://developers.google.com/speed/docs/insights/about.
To try answering your final question directly: additional requests will cost more. It's not necessarily "really bad" to have many files, but it's generally a good idea to combine content into a single file when you can.
Your question isn't answerable in a real generic way.
There are a few reasons to combine scripts and stylesheets.
Browsers using HTTP/1.1 will open multiple connections, typically 2-4 for every host. Because almost every site has the actual HTML file and at least one other resource like a stylesheet, script or image, these connections are created right when you load the initial URL like index.html.
TCP connections are costly. That's why browsers open directly multiple connections ahead of time.
Connections are usually limited to a small number and each connection can only transfer one file at a time.
That said, you could split your files across multiple hosts (e.g. an additional static.example.com), which increases the number of hosts / connections and can speed up the download. On the other hand, this brings additional overhead, because of more connections and additional DNS lookups.
On the other hand, there are valid reasons to leave your files split.
The most important one is HTTP/2. HTTP/2 uses only a single connection and multiplexes all file downloads over that connection. There are multiple demos online that demonstrate this, e.g. http://www.http2demo.io/
If you leave your files split, they can also be cached separately. If you have just small parts changing, the browser could just reload the changed file and all others would be answered using 304 Not Modified. You should have appropriate caching headers in place of course.
That said, if you have the resources, you could serve all your files separately using HTTP/2 for clients that support it. If you have a lot of older clients, you could fallback to combined files for them when they make requests using HTTP/1.1.
Tricky question :)
Of course, the trivial answer is that more requests takes more time, but that is not necessarily this simple.
browsers open multiple http connections to the same host, see http://sgdev-blog.blogspot.hu/2014/01/maximum-concurrent-connection-to-same.html Because that, not using parallel download but rather downloading one huge file is considered as a performance bottleneck by http://www.sitepoint.com/seven-mistakes-that-make-websites-slow/
web servers shall use gzip content-encoding whenever possible. Therefore size of the text resources such as HTML, JS, CSS are quite compressed.
most of those assets are static content, therefore a standard web server shall use etag caching on them. It means that next time the download will be like 26 bytes, since the server tells "not changed" instead of sending the 32kbyte of JavaScript over again
Because of the etag cache, the whole web site shall be cacheable (I assume you're programming a game or something like that, not some old-school J2EE servlet page).
I would suggest making 2-4 big files and download that, if you really want to go for the big files
So to put it together:
if you have only static content, then it is all the same, because etag caching will shortcut any real download from the server, server returns 304 Not modified answer
if you have some generated dynamic content (such as servlet pages), keep the JS and CSS separate as they can be etag cached separately, and only the servlet page needs to be downloaded
check that your server supports gzip content encoding for compression, this helps a lot :)
if you have multiple dynamic content (such as mutliple dynamically changing images), it makes sense to have them represented as 2-4 separate images to utilize the parallel http connections for download (although I can hardly imagine this use case in the real life)
Please, ensure that you're not serving static content dynamically. I.e. try to load the image to a web browser, open the network traffic view, reload with F5 and see that you get 304 Not modified from the server, instead of 200 OK and real traffic.
The biggest performance optimization is that you don't pull anything from the server, and it comes out of the box if used properly :)
I think #DigitalDan has the best answer.
But the question belies the real one, how do I make my page load faster? Or at least , APPEAR to load faster...
I would add something about "above the fold": basically you want to inline as much as will allow your page to render the main visible content on the first round trip, as that is what is perceived as the fastest by the user, and make sure nothing else on the page blocks that...
Archibald explains it well:
https://www.youtube.com/watch?v=EVEiIlJSx_Y
How much you win if you use any of these types might vary based on your specific needs, but I will talk about my case: in my web application we don't combine all files, instead, have 2 types of files, common files, and per page files, where we have common files that needed globally for our application, and other files that is used for its case only, and here is why.
Above is a chart request analysis for my web application, what you need to consider is this
DNS Lookup happens only once as it cached after that, however, DNS name might be cached already, then.
On each request we have:
request start + initial connection + SSL negotiation+ time to first byte + content download
The main factor here which takes majority of request time in most cases is the content download size, so if I have multiple files that all of them needed to be used in all pages, I would combine them into one file so I can save the TCP stack time, on the other hand, if I have files needed to be used in specific pages, I would make it separate so I can save the content download time in other pages.
Actually very relevant question (topic) that many web developer face.
I would also add my answer among other contributors of this question.
Introduction before going to answer
High performance web sites depending on different factors, here is some consideration:
Website size
Content type of website (primary content Text, image, video or mixture)
Traffic on your website (How many people visiting your website average)
Web-host Location vs your primary visitor location (with in your country, region and world wide), it matters a lot if you have website for Europe and your host is in US.
Web-host server (hardware) technology, I prefer SSD disks.
How web-server (software) is setup and optimized
Is it dynamic or static web site
If dynamic, how your code and database is structured and designed
By defining your need you might be able to find the proper strategy.
Regarding your question in general
What regards your website. I recommend you to look at Steve Souders 14 recommendation in his Book High Performance Web Sites.
Steve Souders 14 advice:
Make fewer HTTP requests
Use a Content Delivery Network (CDN)
Add an Expires Header
Gzip Components
Put Style-sheets at the Top
Put Scripts at the Bottom
Avoid CSS Expressions
Make JavaScript and CSS External if possible
Reduce DNS Lookups
Minify JavaScript
Avoid Redirects
Remove Duplicates Scripts
Configure ETages
Make Ajax Cacheable
Regarding your question
So if we take js/css in consideration following will help a lot:
It is better to have different codes on different files.
Example: you might have page1, page2, page3 and page4.
Page1 and page2 uses js1 and js2
Page3 uses only js3
Page4 uses all js1, js2 and js3
So it will be a good idea to have JavaScript in 3 files. You are not interested in including every thing you have that you do not use.
CSS Sprites
CSS at top and JS at the end
Minifying JavaScript
Put your JavaScript and CSS in external files
CDN, in case you use jQuery for example do not download it to your website just use the recommended CDN address.
Conclusion
I am pretty sure there is more details to write. And not all advice are necessary to implement, but it is important to be aware of those. As I mentioned before, I suggest you reading this tiny book, it gives you more details. And finally there is no perfect final solution. You need to start some where, do your best and improved it. No thing is permanent.
Good luck.
the answer to your question is it really depends.
the ultimate goal of page load optimization is to make your users feel your page load is fast.
some suggestions:
do not merge common library js css files like jquery coz they might have already cached by brower when you visited other sites so u don't even need to download them;
merge resources, but at least separate first screen required resouces and the others coz the earlier user could see some meaningful stuff, the faster they feel about your page;
if several of your pages shared some resources, separate the merged files for shared resources and page specific resources so that when you visit the second page, the shared ones might have already been cached by browser, so the page load is faster;
user might be using a phone with slow or inconsistent speed 3g/4g network, so even 50k of data or 2 more requests does make them feel different a lot;
Is really bad to have a lot of 100-lines-files and is also really bad to have just one or two big files, though for each type css/js/markup.
Desktops have mostly high speed connection, and mobile has also high latency.
Taking all the theory about this topic, i think the best approach shall be more practical, less accurate and based upon actual connection speed and device types from a statistical point of view.
For example, i think this is the best way to go today:
1) put all the stuff needed to show the first page/functionality to the user, in one file, shall be under 100KB - this is absolutely a requirement.
2) after that, split or group the files in sizes so that the latency is no longer noticeable together with the download time.
To make it simple and concrete, if we assume: time to first byte is around ~200ms, the size of each file should be between ~120KB and ~200 KB, good for the most connections of today, averaged.
On some of our pages, we display some statistics like number of times that page has been viewed today, number of times it's been viewed the past week, etc. Additionally, we have an overall statistics page where we list the pages, in order, that have been viewed the most.
Today, we just insert these pageviews and event counts into our database as they happen. We also send them to Google Analytics via normal page tracking and their API. Ideally, instead of querying our database for these stats to display on our webpages, we just query Google Analytics' API. Google Analytics does a FAR better job figuring out who the real uniques are and avoids counting people who artificially inflate their pageview counts (we allow people to create pages on our site).
So the question is if it's possible to use Google Analytics' API for updating the statistics on our webpages? If I cache the results is it more feasible? Or just occasionally update our stats? I absolutely love Google Analytics for our site metrics, but maybe there's a better solution for this particular need?
So the question is if it's possible to use Google Analytics' API for updating the statistics on our webpages?
Yes, it is. But, the authentication process and xml return may slow things up. You can speed it up by limiting the rows/columns returned. Also, authentication for the way you want to display the data (if I understood you correctly) would require you to use the client authentication method. You send the username and password. Security is an issue.
I have done exactly what you described but had to put a loading graphic on the page for the stats.
If I cache the results is it more feasible? Or just occasionally update our stats?
Either one but caching seems like it would work especially since GA data is not real-time data anyway. You could make the api call and store (or process then store) the returned xml for display later.
I haven't done this but I think I might give it a go. Could even run as a scheduled job.
I absolutely love Google Analytics for our site metrics, but maybe there's a better solution for this particular need?
There are some third-party solutions (googling should root them out) but money and feasibility should be considered.