I wonder why the rendering time to load a certain page is different from time to time (i used one certain browser). I have a java script code in that page..so when the page load, there will be a java script alert coming up.
I'm intending to compare the rendering time of a page in one browser to another. But, when only in one browser the rendering time could be different form time to time..how might i campare to another browser?? It's just hard to compare the rendering time of those browser.
Any idea why this could happen?
Thanks a bunch :)
Are you testing under lab conditions, ie. are you sure that there are no other burdens on your system resources when rendering the page.
Most importantly, are there any other processes running in your browser, extensions, other tabs etc. etc.
It's also very important where you're loading the page from, if it's not a local server then you have a lot of variables to consider.
Also, as nnnnnn points out, is it load time, or rendering time?
In short, the following factors can heavily influence render time:
Caching rules
Server speed & server load
Cookies
Network (your internet connection, the server's connection speed, etc.)
First, I'd check the caching rules. Depending on those, your browser might be told to only save static elements for a short amount of time, resulting in longer loading times when it is told to reload those.
Secondly, compare server speeds at different times of day (there's online tools for this).
Also have a look on how 'busy' your server is. Especially shared servers can be quite slow from time to time.
Then, have a look at your code. If you're setting cookies, these might influence loading time depending on their size. The larger the cookies grow, the slower the site loading might become.
Related
I am new to jmeter and have a couple of doubt about web application performance testing.
Is it necessary to load all embedded resource in jmeter for performance testing ?
I have written a Jmeter script that exercise all REST apis. Is this enough to find the application performance at the server side ?
How Ramp up time affects the Performance test ?
For how much time the test needs to be executed, to get an accurate performance report ?
Load Generation configuration - Generating load from machines attached to application cluster / from different LAN ?
Kindly find my view on the questions below:
I believe that load test needs to be as much realistic as possible so representing real browser behavior is a must. Real browsers download embedded resources like scripts, images and styles, moreover, they use a concurrent thread pool of 2 - 8 threads to do this in parallel. So you need to configure JMeter similarly. However real browsers download these assets only once, on subsequent requests they return embedded resources from cache. So make sure that you configure JMeter to:
download embedded resources
use concurrent pool for it
add HTTP Cache Manager to your test plan
It should be enough from functional point of view as usually static content is being served separately. However see point 1, if you have possibility to simulate real user behavior - go for it
It is better to have reasonable ramp-up and ramp-down periods so the load could increment gradually so both server and load generator sides won't experience peak stress loads (unless it is your test case). See the bit on ramp-up from JMeter documentation
Ramp-up needs to be long enough to avoid too large a work-load at the start of a test, and short enough that the last threads start running before the first ones finish (unless one wants that to happen).
Start with Ramp-up = number of threads and adjust up or down as needed.
By default, the thread group is configured to loop once through its elements.
Usually peak load follows general Pareto principle, during "peak" periods application served 80% of requests during 1-2 hours time frame and remaining 20% of requests were more or less equally distributed between remaining 20 hours in a day. So it should be enough to test your application providing anticipated peak load for a couple of hours. Again if time allows I would recommend to go for Soak testing to see if there are any memory leaks and for Stress testing to determine application load boundaries and whether it recovers from stress load or not
Theoretically application shouldn't care regarding requests source (unless it uses different logic to handle requests from i.e. different geo regions). One thing is obvious: don't run load generator and application under test on the same machine. If one JMeter instance cannot create enough load to implement test scenario - go for distributed testing
I'd like to add some more perspective:
Question 1 & 2:
The Pareto principle can be applied here also - meaning, that it takes a lot of effort to properly simulate reality, downloading all resources used by a browser to render a page and to give the proper 'weights' to different URLs, simulating user behaviour accurately. This is where many load tests fail, because simulating reality accurately is very, very hard. As the previous response mentions, most static content is often served via CDNs or similar anyway, and what you really want to test is usually your own system's capability to handle traffic.
Considering the above, I would say that if you spend 20% of effort setting up a load test that tests your REST API, you will get 80% of the results you want. If you on the other hand go for a completely realistic test, you will spend another 80% of effort for only 20% more results. The effect of this is that in many cases it is better to go for the simpler test, that does not simulate reality accurately. It gives you the most return on your invested time.
Question 3: Agree fully with previous response here. Ramp up slowly, unless your specific use case sees very sudden traffic peaks (like if you're an online auction service or ticket sales or similar). Can also be a good idea to configure your test so it spends some time on a "plateau" after ramping up to peak load, and not just stopping the load test once you reach the peak.
Question 4: I would say you need to run the load test long enough to produce stable, statistically significant results. This can be 5 minutes or 5 hours depending on your scenario, but half an hour is probably a good minimum time to aim for in mostly all cases. The test duration should not be dependent on how long your site tends to experience peak load in real life though - not unless you're doing some kind of soak test.
Question 5: Traffic origin is sometimes worth thinking about, as different source locations lead to different network delay between (simulated) clients and server, which affects transaction rates. If you run a load test with 1,000 VUs on a system located in New York, and generate the traffic from Australia, you will not get a lot of transactions per second due to the high network delay. If you run the same test using a load generator in New York instead, your transaction rate will be a lot higher because the network delay is so much lower. Of course, you can always add more concurrent clients/VUs/connections and get the same transaction rate on a high-delay network link that you would on a low-delay link, but at the cost of forcing the server to keep a lot more (TCP) connection state, using more file descriptors and buffer memory. I.e. might not be a very realistic scenario.
I have an xpages 9.0.1 server running multiple online form type apps. The server runs fine and performance response is quite good. Pages load fast, users are happy.
Over time (yet to determine how long), the server performance degrades and ultimately grinds to an almost stop.
Each night I am scheduling -c "tel http restart" and it is getting me out of trouble.
I am not sure what page is causing the problem as the degrading happens over a couple of days.
Most of our xpages are SSJS, all of our java (of which there is not much) is appropriately recycled.
It does not seem to be effecting RAM memory - it bounces up a bit and down a bit but well with limits. There is no correlation with the increased response times to more memory used.
So where do I look and what tools can I use to isolate the problem. We are more Dev than Admin.
Cheers
Damien
There are profiling tools available that may help pinpoint which application is causing problems. From OpenNTF, XPages Toolbox is specifically for XPages and was contributed by Philippe Riand, who at the time was Chief Architect for XPages http://www.openntf.org/main.nsf/project.xsp?r=project/XPages%20Toolbox.
There are more heavy-duty, Java-specific tools like YourKit available.
Chapter 20 of Mastering XPages second edition specifically covers performance and there is also a lot of information in XPages Portable Command Guide about performance tuning.
If performance is degrading over time, it could be session timeout. By default, that's 30 minutes. You can extend it, but the danger then is that a browser cannot tell the server it's closing the session when the user closes the browser. So those sessions hang around. Equally if there are very long-running tasks, they would hang around until they complete and the session would then still be active until the timeout.
Are you recycling your SSJS?
If you go into the server tasks of Domino Admin what do you see the CPU usage of the HTTP task doing. Also what is the memory usage of your nHTTP task? You may want to watch that.
Have you gone into the console to see if you can see if there us anything that looks bad?
If you can't pinpoint a problem you may want to think of putting some of your pages on a different server to determine if which app if not all is causing this.
Are you using scoped variables that are session or application scope? Application scope variables stay alive so if you are creating those and have some sort of issue where you end up creating a bunch that can affect memory.
Also there is a server and application setting for when the XPages stay in memory. The suggested setting to Keep only the current page in memory and save the others to disk. This is in the XSP properties.
First - a little bit about my background: I have been programming for some time (10 years at this point) and am fairly competent when it comes to coding ideas up. I started working on web-application programming just over a year ago, and thankfully discovered nodeJS, which made web-app creation feel a lot more like traditional programming. Now, I have a node.js app that I've been developing for some time that is now running in production on the web. My main confusion stems from the fact that I am very new to the world of the web development, and don't really know what's important and what isn't when it comes to monitoring my application.
I am using a Joyent SmartMachine, and looking at the analytics options that they provide is a little overwhelming. There are so many different options and configurations, and I have no clue what purpose each analytic really serves. For the questions below, I'd appreciate any answer, whether it's specific to Joyent's Cloud Analytics or completely general.
QUESTION ONE
Right now, my main concern is to figure out how my application is utilizing the server that I have it running on. I want to know if my application has the right amount of resources allocated to it. Does the number of requests that it receives make the server it's on overkill, or does it warrant extra resources? What analytics are important to look at for a NodeJS app for that purpose? (using both MongoDB and Redis on separate servers if that makes a difference)
QUESTION TWO
What other statistics are generally really important to look at when managing a server that's in production? I'm used to programs that run once to do something specific (e.g. a raytracer that finishes running once it has computed an image), as opposed to web-apps which are continuously running and interacting with many clients. I'm sure there are many things that are obvious to long-time server administrators that aren't to newbies like me.
QUESTION THREE
What's important to look at when dealing with NodeJS specifically? What are statistics/analytics that become particularly critical when dealing with the single-threaded event loop of NodeJS versus more standard server systems?
I have other questions about how databases play into the equation, but I think this is enough for now...
We have been running node.js in production nearly an year starting from 0.4 and currenty 0.8 series. Web app is express 2 and 3 based with mongo, redis and memcached.
Few facts.
node can not handle large v8 heap, when it grows over 200mb you will start seeing increased cpu usage
node always seem to leak memory, or at least grow large heap size without actually using it. I suspect memory fragmentation, as v8 profiling or valgrind shows no leaks in js space nor resident heap. Early 0.8 was awful in this respect, rss could be 1GB with 50MB heap.
hanging requests are hard to track. We wrote our middleware to monitor these especially as our app is long poll based
My suggestions.
use multiple instances per machine, at least 1 per cpu. Balance with haproxy, nginx or such with session affinity
write midleware to report hanged connections, ie ones that code never responded or latency was over threshold
restart instances often, at least weekly
write poller that prints out memory stats with process module one per minute
Use supervisord and fabric for easy process management
Monitor cpu, reported memory stats and restart on threshold
Whichever the type of web app, NodeJS or otherwise, load testing will answer whether your application has the right amount of server resources. A good website I recently found for this is Load Impact.
The real question to answer is WHEN does the load time begin to increase as the number of concurrent users increase? A tipping point is reached when you get to a certain number of concurrent users, after which the server performance will start to degrade. So load test according to how many users you expect to reach your website in the near future.
How can you estimate the amount of users you expect?
Installing Google Analytics or another analytics package on your pages is a must! This way you will be able to see how many daily users are visiting your website, and what is the growth of your visits from month-to-month which can help in predicting future expected visits and therefore expected load on your server.
Even if I know the number of users, how can I estimate actual load?
The answer is in the F12 Development Tools available in all browsers. Open up your website in any browser and push F12 (or for Opera Ctrl+Shift+I), which should open up the browser's development tools. On Firefox make sure you have Firebug installed, on Chrome and Internet Explorer it should work out of the box. Go to the Net or Network tab and then refresh your page. This will show you the number of HTTP requests, bandwidth usage per page load!
So the formula to work out daily server load is simple:
Number of HTTP requests per page load X the average number of pages load per user per day X Expected number of concurrent users = Total HTTP Requests to Server per Day
And...
Number of MBs transferred per page load X the average number of pages load per user per day X Expected number of concurrent users = Total Bandwidth Required per Day
I've always found it easier to calculate these figures on a daily basis and then extrapolate it to weeks and months.
Node.js is single threaded so you should definitely start a process for every cpu your machine has. Cluster is by far the best way to do this and has the added benefit of being able to restart died workers and to detect unresponsive workers.
You also want to do load testing until your requests start timing out or exceed what you consider a reasonable response time. This will give you a good idea of the upper limit your server can handle. Blitz is one of the many options to have a look at.
I have never used Joyent's statistics, but NodeFly and their node-nodefly-gcinfo is a great tools to monitor node processes.
I'm working with a JSF2 webapp. When I'm navigating between different pages they normally load fast; less than 100 ms. Sometimes though, for no apparent reason, it takes several seconds.
I've been trying to find some common denominator for when this occurs, but it happens regardless of page and regardless if I have visited the page several times before. Also, after a page has been slow to load, the next time I load it, it will load fast again for some time.
It all seems to happen randomly.
I have tried to find out what part of the application that takes time to carry out its task. I've timed more or less everything I can think of and it's not database calls, the logic in my classes or anything like that. Instead, looking at the "network" graph of chrome, it seems to be the initial call to the page that is the time thief.
Looking at the "network" diagram of Chrome, it shows that the latency for the first call is several seconds on those occasions.
Had this been due to my own bad code, I could at least have timed it and found out where I had made mistakes. Seeing that this seems to happen before my own code is even reached, I have no idea about how to solve this problem.
This may not be the actual reason to the problem, but I noticed that my internet connection was going up and down, which seems to affect the application even though I'm running a local server.
If I have made a request to the application and the internet connection goes down, the requested page won't load and as soon as the connection is back, the page loads.
I didn't think that this would affect the application at all, as the server is local and I can inactivate the internet connection and still access the application.
What solutions do you have in place for handling bandwidth billing for your vhosts on a shared environment in apache? If you are using log parsing, does your solution scale well when the logs become very very large? Anyone using any sort of module out there for this?
There exist certain modules for Apache 1.x and 2.x that will allow you to set a maximum on the transfer amount, most of them keep track using the scoreboard file that Apache generates (when mod_status is enabled with ExtendedStatus on). The one I still have bookmarked from when I was looking for one is mod_curb, however it is not complete and at the current moment in time looks to only work on a server-wide scale and not for individual virtual hosts.
Apache modules can be set to be outbound filters, so you could write a costume module that would sit at the end of the chain, and add up all the outgoing packets, using the data that APR provides you can then add it to a counter for that specific domain/sub-domain. After that you have a choice of what to do with the data.
For specific examples, take a look at mod_deflate that Apache provides, to see how it sits at the end of the chain and compresses everything but the headers the server sends out. This should give you a good start.
As for log based processing, it becomes slower the more logs exist. This is just the nature of the beast. When we were using a log based solution we had a custom perl script that ran every 15 minutes. Eventually it would take longer than 15 minutes to parse, and since we had proper locking after a while multiple of these log processing perl scripts were now running, all waiting on each other. We ended up re-writing it with a simple call to tail -F, which then let perl parse each and every request as it came in, while not entirely efficient, it worked. The upside of that was that we were now able to update traffic statistics in near realtime so that clients were updated sooner rather than later if they went over their limits.
You could go the poor man's route, and use Webalizer or Awstats. Both of these will give you an idea of traffic based off of access logs, and can be done on a per virtual host basis. In the case of Awstats, I know once you start doing 10GB+ of traffic daily, it starts to consume resources. You can always nice it, but then you'll get your data next week, rather than when you actually need it. In the past with Webalizer I've had to use some hackery to get it to handle large access logs, by chunking up the logs to smaller pieces that it could manage. It didn't provide as many useful metrics from what I've done with it, but I've also never needed to save a server from it :)
If virtual host does not have own IP, there is no easier way than logfile parsing. Just use mod_logio to calculate actual bytes transferred. mod_logio handles broken connections, compressed data etc. correctly. You should be able to parse logs realtime using piped logs. Use BufferedLogs to scale further (just check that parser handles lines broken when buffered correctly). Parser should save data periodically (like every minute) somewhere, just avoid locking issues as parsing must not slow down httpd. If httpd connections is spending time in L-state at server-status, you are too slow. After you have numbers, you can sum then further and then save data to billing system.
If you save billing logs as file too you can correct and doublecheck realtime traffic calculations. If you boot httpd you can end up missing some lines. But generally losing couple hundred requests is acceptable as it less than seconds worth on a high volume site.
There is modules that try to handle and limit bandwidth, like mod_cband and mod_bw. But they don't work when you have same vhost on multiple machines. I guess they would work ok on smaller scale.
If you have IP per vhost you could try IP based methods like feeding firewall logs to traffic calculator. Simple way is to use iptables.
Although we use IIS rather than apache we do use log file analysis for bandwidth billing (and bandwidth profiling / analysis). We use a custom application to load data collected in the log files in one hour increments, and act upon any required notifications or bandwidth overuse.
The log file loader runs as a low priority process, so as not to interupt operation of the server. Even on high usage servers with a large number of sites, processing takes less than 15 minutes, so we don't see scalability as a problem with this methodology.
There may be better ways of doing this, but this is perfectly adequate for what we need. I look forward to viewing the other responses.
It can be easily achieved with mod_cband. We've rewritten the module to fix a few bugs, provide true redundancy on restarts and incorporate FTP and Mail statistics.
http://www.howtoforge.com/mod_cband_apache2_bandwidth_quota_throttling
Well mod_cband would be great, except for when i'm using it, the max_connections (the overall, total value for every client combined), decides to crawl upwards until it hits the max value i've set. when it does reach the highest value, it just stays there and leaves all my clients receiving a constant "503 Service Temporarily Unavailable" error.
for example, i set "CbandSpeed 1000Mbps 500 1200", and the server connections crawls up to 1200 in about 8 hrs, then stays there. at this point, i count the total number of connections under Remote Clients in the mod_cband status window, and i see around 50. i've also used ps aux and i see around the same amount (~50) open http processes, which is normal, except for the fact that nobody can access the site at all because of the 503 errors.
Any ideas what could be wrong, or can this be fixed?