What can be the various performance testing scenarios to be considered for a website with huge traffic? Is there any way to identify the elements of the code which are adversely affecting the site performance?
Please provide something similar to checklist of generalised scenarios to be tested to ensure proper performance testing.
It would be good to start with some load testing tools like JMeter or PushToTest and start running it against your web application. JMeter simulates HTTP traffic and loads the server that way. You can do that as well as load test AJAX parts of your application with PushToTest because it can use Selenium Scripts.
If you don't have the resources (computers to run load tests) you can always use a service like BrowserMob to run the scripts against a web accessible server.
It sounds like you need more of a test plan than a suggestion of tools to use. In performance testing, it is best to look at the users of the application -
How many will use the application on a light day? How many will use the app on a heavy day?
What type of users make up your user population?
What transactions will each of these user types perform?
Using this information, you can identify the major transactions and come up with different user levels (e.g. 10, 25, 50, 100) and percentages of user types (30% user A, 50% user B, ...) to test these transactions with. Time each of these transactions for each test you execute and examine how the transaction times change as compared to your user levels.
After gathering some metrics, since you should be able to narrow transactions to individual pieces of code, you will be able to know where to focus your code improvements. If you still need to narrow things down further, finer tests within each transaction can be created to provide more granular results.
Concurrency will kill you here, as you need to test your maximum projected concurrent users + wiggling room hitting the database, website, and any other web service simultaneously. It really depends on the technologies you're using, but if you have a large interaction of different web technologies, you may want to check out Neoload. I've had nothing but success with this web stress tool, and the support is top notch if you need to emulate specific, complicated behavior (such as mocking AMF traffic, or using responses from web pages to dictate request behavior.)
If you have a DB layer then this should be the initial focus of your attention, once the system is stable (i.e. no memory leaks or other resource issues). If the DB is not the bottle neck (or not relevant) then you need to correlate CPU/Memory/Disk IO and Network traffic with the increasing load and increasing response times. This gives you an idea of capacity and correlation (but not cause) to resource usage.
To find the cause of a given issue with resources you need to establish a Six Sigma style project where you define the problem and perform root case analysis in order to pin point the piece of code (or resource configuration) that is the bottleneck. Once you have done this a couple of times in your environment, you will notice patterns of workload, resource usage and counter measures (solutions) that will guide you in your future performance testing 'projects'.
To choose correct performance scenarios you need to go through the next basic checklist:
High priority scenarios from the business logic perspective. For example: login/order transactions, etc.
Mostly used scenarios by end users. Here you may need information from monitoring tools like NewRelic, etc.
Search / filtering functionality (if applicable) - Scenarios which involve different user roles/permissions
Performance test is a comparison test either with the previous release of the same application or with the existing players in the market.
Case 1- Existing application
1)Carry out the test for the same scenarios as covered before to get a clear picture on the response of the application before and after the upgrade.
2)If you need to dig deeper you can get back to the database team to understand which functionalities are getting more requests. Also ask them on the total number of requests on an average on any particular day so that you can take a call on what user load and time duration to be given for the test.
Case 2- New Application
1) Look for existing market players and design your test as per the critical functions of the rival product (for e.g. Gmail might support many functions what what is being used often is launch ->login ->compose mail -> inbox ->outbox).
2) Any time you can get back to your clients on what they suppose to be business critical scenarios or scenarios that will be used more often..
Related
I have taken as an example for learning and gathered some information about tools, objectives,scenarios, but I need your inputs. Please assist me.
I am new to Performance testing and would like to test the following website www.volkswagen.co.nz
Can you tell me, what are need to be tested? What are the scenarios and activities for each scenario? What metrics do I need to add? Which is the best and free tool for testing it? How to test if it is deployed in cloud like AWS?
Please let me know, Thanks in advance.
Performance testing needs,
Identify critical/heavy/important scenario in your webapp (irrespective of deployment cloud/standalone)
Identify service level agreements in terms of response times, throughput, latency etc.
Identify workload model i.e. how much user load application is expecting. this should be as fine grained as possible (avg users per transaction/workflow at a point of time)
Identify tools (JMeter is freeware and best but if you can afford paid then look at loadrunner, neoload etc.)
Record the script for workflows and parameterise and correlate.
generate test setup for load test and execute the load test.
monitor system utilization, collect metrics like response time, throughput, error rate, latency etc.
This all comes in load testing. For more you can read http://www.guru99.com/performance-testing.html
I am new to Performance testing and would like to test the following website www.volkswagen.co.nz
That is a recipe for disaster. No one new should be allowed to work on their own without a full period of training and internship with a master in the field. This is true of stone masons, electricians, plumbers, barbers, accountants, engineers and physicians. And it is most certainly true of performance testers/engineers.
There are dozens of foundation skills you need to master before you touch any tool, open source or otherwise. Until you show mastery of those items along with tool mechanics for your tool you should not be allowed to test any website, particularly a production website. And, if you don't work for this company what you are engaging in is a denial of service attack and could leave you with exposed legal liability.
I strongly agree with James on this one.
Do not touched the site if:
it's not yours
not sure what you are doing
the owner gave you explicit (and sounds like irresponsible) permission
don't know or don't have the support to restore the environment into a working state
If you do work for the company then you need to have a test environment first, a playground where you can mess around and nobody would mind if you take it down.
Firstly get information from the business on which use cases needs to
be tested.
Get response times target for user actions and for environments utilisation.
Get response time targets for environments utilisation: define environment monitoring tactics.
Found a tool that can fit for purpose: Jmeter, Gattling,etc, lot's of free ones available.
Get a test environment, preferably similar scale to production
Create scripts to cover critical use cases
Comply scripts into scenarios
Create a reporting framework
Kick off monitoring
Kick off scenario
Collect and analyse results
Be mindful of the free editions of load testing tools: they tend to be easy to use at first but soon as you start to outgrow it it can cost a fortune and more often then not it's hard to port scripts/scenarios to another tool.
Anyone can point out the difference between virtual user and real user?
In the context of web load testing, there are a lot of differences. A virtual user is a simulation of human using a browser to perform some actions on a website. One company offers what they call "real browser users", but they, too, are simulations - just at a different layer (browser vs HTTP). I'm going to assume you are using "real users" to refer to humans.
Using humans to conduct a load test has a few advantages, but is fraught with difficulties. The primary advantage is that there are real humans using real browsers - which means that, if they are following the scripts precisely, there is virtually no difference between a simulation and real traffic. The list of difficulties, however, is long: First, it is expensive. The process does not scale well beyond a few dozen users in a limited number of locations. Humans may not follow the script precisely...and you may not be able to tell if they did. The test is likely not perfectly repeatable. It is difficult to collect, integrate and analyze metrics from real browsers. I could go on...
Testing tools which use virtual users to simulate real users do not have any of those disadvantages - as they are engineered for this task. However, depending on the tool, they may not perform a perfect simulation. Most load testing tools work at the HTTP layer - simulating the HTTP messages passed between the browser and server. If the simulation of these messages is perfect, then the server cannot tell the difference between real and simulated users...and thus the test results are more valid. The more complex the application is, particularly in the use of javascript/AJAX, the harder it is to make a perfect simulation. The capabilities of tools in this regard varies widely.
There is a small group of testing tools that actually run real browsers and simulate the user by pushing simulated mouse and keyboard events to the browser. These tools are more likely to simulate the HTTP messages perfectly, but they have their own set of problems. Most are limited to working with only a single browser (i.e. Firefox). It can be hard to get good metrics out of real browsers. This approach is far more scalable better than using humans, but not nearly as scalable as HTTP-layer simulation. For sites that need to test <10k users, though, the web-based solutions using this approach can provide the required capacity.
There is a difference.
Depends on your jmeter testing, if you are doing from a single box, your IO is limited. You cant imitate lets say 10K users with jmeter in single box. You can do small tests with one box. If you use multiple jmeter boxes that s another story.
Also, how about the cookies, do you store cookies while load testing your app? that does make a difference
A virtual user is an automatic emulation of a real users browser and http requests.
Thus the virtual users is designed to simulate a real user. It is also possible to configure virtual users to run through what we think a real users would do, but without all the delay between getting a page and submitting a new one.
This allows us to simulate a much higher load on our server.
The real key differences between virtual user simulations and real users is are the network between the server and thier device as well as the actual actions a real user performs on the website.
I use several loadtesting tools (Loadrunner, JMeter, NeoLoad) to performance test different applications. Im wondering if it is possible to monitor all layers of an application stack so for example. Say i have the following data chain.
Loadbalancer <-x-> Application Server <-x-> RMI <-x-> Java Application <-x-> MQ <-x-> Legacy application <-x-> Database
Where i have marked the x in the chain i am interested in monitoring, for example avg responsetimes.
Obviously we could simply create a wrapper on all endpoints which would gather the statistics for us and maybe we could import it into loadrunner or other loadtesting tools and sideline hem with the tools inbuilt performance statistics, but maybe there is tools/applications which already does this?
If not, how should we proceed, in order to gather this kind of statistics?
The standard for this was supposed to be Application Response Measurement (ARM). It was a cross language set of APIs that did just what you were looking for. The issue is that the products that implement this spec all tend to be big, expensive "enterprise" level monitoring tools. Think multi-week installs, consultants, more infrastructure and lots of buzzwords.
Still, if this is a mission critical app with a mission critical budget, this may be what you need. But you may be able to build your own that does just enough without too much effort. A quick search turns up at least one open source ARM implementation if you still want to use that API.
Another option is to simply to have transactions you can run against each tier of the system to check general responsiveness. For example you can have a static web page on the LB, a no-op tx on the app server, a "hello" servlet on the Java app, put a message directly on the queue, etc. During a performance / load test, these could be hit directly by the load testing tool or you could write a wrapper servlet / application call that does this as a single HTTP (RMI?) call. Running these a few times a minute won't add too much load to the system, but it should help you pinpoint which tier is slower. The nice thing about this approach is that it also works in production, just watch out for security issues.
For single user kind of test, where you know you have problem (e.g. this tx is "slow"), I have also had pretty good luck with network tracing. It's very tedious, but when you aren't sure what tier is slow, starting up a network trace on a few machines and running a single tx usually gives a good idea of what the system is doing.
I have handled this decomposition a number of ways in the past. The first is at a very low level using protocol analyzer dumped data to find the time points where a conversation leaves tier X and enters tier Y. The second method is through the use of log examination for the various tiers. Something that can make your examination quite usefule in this case is a common log server for all of your components (syslog, Rsyslog, etc....) and a nice log parsing tool, such as the freely available Microsoft Logparser. The third method utilization of the audit trail for an application stored in the database. You may find this when working on enterprise services bus style applications which have a consumer/producer model and a bus to pass information rather than a direct connection. The audit trails I have seen are typically stored in a database and allow the tracking of an individual transaction through the entire application infrastructure. Your Load balancer, as a network device, may be out of the hunt on this one.
Note, if you go the protocol analyzer or log route, then be sure and synchronize all of your source information devices to a common time server. Having one of your collectors (analyzer, app log) off on a time stamp basis can really be a hair pulling experience when you get into the analysis phase.
As to how you move from your collected data into LoadRunner, that part is very mechanical. The Analysis program supports an interface to import external datapoints. The format is very specific and is documented in both help and the online docs. This import process works very well, as I often have to use it for collection of statistics from hosts which I do not have direct monitoring access to, but which need to be included as a part of the monitored test infrastructure.
James Pulley
Moderator (YahooGroups LoadRunner, Advanced-Loadrunner; GoogleGroups lr-LoadRunner; Linkedin LoadRunner, LoadRunnerByTheHour; SQAForums LoadRunner, WinRunner)
We are creating a simple website but with heave user logins (about 25000 concurrent users). How can I calculate no. of instances required to support it?
Load testing and performance testing are really the only way you're going to figure out the performance metrics and instance requirements of your app. You'll need to define "concurrent users" - does that mean 25,000 concurrent transactions, or does that simply mean 25,000 active sessions? And if the latter, how frequently does a user visit web pages (e.g. think-time between pages)? Then, there's all the other moving parts: databases, Azure storage, external web services, intra-role communication, etc. All these steps in your processing pipeline could be a bottleneck.
Don't forget SLA: Assuming you CAN support 25,000 concurrent sessions (not transactions per second), what's an acceptable round-trip time? Two seconds? Five?
When thinking about instance count, you also need to consider VM size in your equation. Depending again on your processing pipeline, you might need a medium or large VM to support specific memory requirements, for instance. You might get completely different results when testing different VM sizes.
You need to have a way of performing empirical tests that are repeatable and remove edge-case errors (for instance: running tests a minimum of 3 times to get an average; and methodically ramping up load in a well-defined way and observing results while under that load for a set amount of time to allow for the chaotic behavior of adding load to stabilize). This empirical testing includes well-crafted test plans (e.g. what pages the users will hit for given usage scenarios, including possible form data). And you'll need the proper tools for monitoring the systems under test to determine when a given load creates a "knee in the curve" (meaning you've hit a bottleneck and your performance plummets).
Final thought: Be sure your load-generation tool is not the bottleneck during the test! You might want to look into using Microsoft's load-testing solution with Visual Studio, or a cloud-based load-test solution such as Loadstorm (disclaimer: Loadstorm interviewed me about load/performance testing last year, but I don't work for them in any capacity).
EDIT June 21, 2013 Announced at TechEd 2013, Team Foundation Service will offer cloud-based load-testing, with the Preview launching June 26, coincident with the //build conference. The announcement is here.
No one can answer this question without a lot more information... like what technology you're using to build the website, what happens on a page load, what backend storage is used (if any), etc. It could be that for each user who logs on, you compute a million digits of pi, or it could be that for each user you serve up static content from a cache.
The best advice I have is to test your application (either in the cloud or equivalent hardware) and see how it performs.
It all depends on the architecture design, persistence technology and number of read/write operations you are performing per second (average/peak).
I would recommend to look into CQRS-based architectures for this kind of application. It fits cloud computing environments and allows for elastic scaling.
I was recently at a Cloud Summit and there were a few case studies. The one that sticks in my mind is an exam app. it has a burst load of about 80000 users over 2 hours, for which they spin up about 300 instances.
Without knowing your load profile it's hard to add more value, just keep in mind concurrent and continuous are not the same thing. Remember the Stack overflow versus Digg debacle "http://twitter.com/#!/spolsky/status/27244766467"?
I have been tasked with looking for a performance testing solution for one of our Java applications running on a Weblogic server. The requirement is to record production requests (both GET and POST including POST data) and then run these requests in a performance test environment with a copy of the production database.
The reasons for using production requests instead of a test script are:
It is a large application with no existing test scripts so it would be a a large amount of work to write scripts to cover the entire application.
Some performance issues only appear when users do a number of actions in a particular order.
To test using actual user interaction with the system not an estimation at how the users may interact with the system. We all know that users will do things we have not thought of.
I want to be able to fix performance issues and rerun the requests against the fixed code before releasing to production.
I have looked at using JMeters Access Log Sampler with server access logs however the access logs do not contain POST data and the access log sampler only looks at the request URL so it cannot simulate users submitting form data.
I have also looked at using the JMeter HTTP Proxy Server however this can record the actions of only one user and requires the user to configure their browser to use the proxy. This same limitation exist with Tsung and The Grinder.
I have looked at using Wireshark and TCReplay but recording at the packet level is excessive and will not give any useful reports at a request level.
Is there a better way to analyze production performance considering I need to be able to test fixes before releasing to production?
That is going to be a hard ask. I work with Visual Studio Test Edition to load test my applications and we are only able to "estimate" the users activity on the site.
It is possible to look at the logs and gather information on the likelyhood of certain paths through your app. You can then look at the production database to look at the likely values entered in any post requests. From that you will have to make load tests that approach the useage patterns of your production site.
With any current tools I don't think it is possible to record and playback actual user interation.
It is possible to alter your web app so that is records and logs every request and post against session and datetime. This custom logging could be then used to generate load test requests against a test website. This would be some serious code change to your existing site and would likely have performance impacts.
That said, I have worked with web apps that do this level of logging and the ability to analyse the exact series of page posts/requests that caused an error is quite valuable to a developer.
So in summary: It is possible, but I have not heard of any off the shelf tools that do it.
Please check out this Whitepaper by Impetus Technologies on this page.. http://www.impetus.com/plabs/sandstorm.html
Honestly, I'm not sure the task you're being asked to do is even possible, let alone a good idea. Depending on how complex the application's backend is, and how perfect you can recreate the state (ie: all the way down to external SOA services or the time/clock), it may not be possible to make those GET and POST requests reproduce the same behavior.
That said, performance testing against production data is always great, but it usually requires application-specific knowledge that will stress said data. Simply repeating HTTP GETs and POSTs will almost certainly not yield useful results.
Good luck!
I would suggest the following to get the production requests and simulate the accurate workload:
1) Use coremetrics: CoreMetrics provides such solutions using which you can know the application usage patterns. This would help in coming up with an accurate workload model. This model can then be converted into test scripts and executed against a masked copy of production database. This will provide you accurate results about the application performance in realtime.
2) Another option would be creating a small utility using AOP (Aspect oriented apporach) so that it can trace all the requests and corresponding method traces. This would help in identifying the production usage pattern and in turn accurate simulation of workload. AOP frameworks such as AspectJ can be used. This would not require any changes in code. The instrumentation can be done on the fly. The other benefit would be that thi cna only be enabled for a specific time window and then it can be turned off.
Regards,
batterywalam