Author Archives: 1202Performance

How does Citrix Improve Response Times

I was asked the other day how does Citrix improve response times. The simple answer is that it cuts down on the number of times the user has to wait for information to be transfered across the network. For example the diagram below shows an application on a client PC communicating with the DB. In this case it is Oracle forms 6i and this can take between 20-60 network hops to get the data needed to display a screen.

chattynetworkapplication

If you are on the same LAN as the DB then you may not notice the delay but it you access across a WAN then the time to cross the WAN all adds up to a slow response time.

With Citrix the citrix server is placed in the datacentre close to the DB. The client then makes one request to the citrix server, the citrix server makes all the requests to the DB and then when the screen is complete send a picture of the screen back to the user. As can be seen in the diagram below.

chattynetworkapplicationcitrixperformance

As the citrix server and DB are closely located then the network hops needed to get the data to build the screen happen quickly and the user has to suffer the delay across the WAN only once. Where applications cross the WAN many times and the delay from the users to the server is high then Citrix is likely to help improve performance. However, you need to also consider the bandwidth of the pipe between the client and the server.

To do this you can create a performance model. The following presentation contain I performance model I built for determining when to deploy citrix to various locations as part of a large upgrade project. In that project the application made 7 trips across the network to generate the display for the user. Pages 12-21 provide the model and some results.

You can download the presentation here.

Seven Stages of Performance Testing Denial

As you may know, many of the ancient religions have such doctrines as “the 5 pillars of wisdom” or the “4 noble truths” that lead humble pilgrims to true enlightenment. Although I am not suggesting we start a new Performance Test religion that perhaps worships the god “Mercury”, I have noticed that there are the 7 levels of denial that developers/system architects/managers (aka pilgrims) seem to have to go through before they realise or admit that they have performance problems (i.e.  true enlightenment).

Like following a religion, this is a personal journey and a unique path is followed by each pilgrim, with no two making the same realisations or decisions at the same point in the project lifecycle, some having to repeat parts of the journey several times (as I am writing this, Mike is explaining again to another set of pilgrims how LoadRunner works).
 
My Experience suggests there are 7 levels of denial, as follows:

1) The load test tool must be wrong – you may be using the industrial standard performance test tool costing £100K, but the quick test the pilgrims did with the free tool downloaded from the internet was better. When you ask whether HTTP 500 status messages were trapped or if the data returned was validated the pilgrims look confused. So, take a deep breath, explain the benefits of a proper tool and move on.
 
2) The performance scripts or workload model must be wrong – you have only been a performance tester for 5 years and worked on countless projects, so its nice to be told you are stupid. Take a deep breath, walk them through the code and enjoy their look of surprise as they suddenly realise what correlation is.
 
3) The system is not finished so doesn’t need to be tested – pilgrims can believe that the last 5% of functionality will increase performance so that a poorly performing system will obviously get better in a minute.. Explain politely how adding new code won’t magically improve the performance of the old.
 
4) It’s not our system, it’s the network etc- blaming the supplier of the components is a common area of denial. To correct this misconception, feign a look of surprise and then arrange a test to show that the offending component runs super fast.

5) We JUST need to configure parameter X – the pilgrim often has the belief that the correct setting of a single magic parameter will solve any problem. What is annoying is the condescending tone often in which the pilgrim states that this is surely the problem and that you the tester must be a complete donkey for not setting this. Of course you smile politely, say lets give it a go and, when nothing changes be dutifully diplomatic. Often you will iterate on “number 5” as several pilgrims in the development team search for the “silver bullet” (or is it “Rocking horse pooh”). An obvious attraction to pilgrims of this approach is that the solution is “only a test cycle away”. Many a manager pilgrim has followed this route.
 
6) Throw hardware at the problem – although this does often have an effect, adding an extra processor to a DB server that is crippled by too many stored procedures doing table scans is as useful as a chocolate tea pot. Take another breath, particularly when you are told the lead time to order the components and re-install the software. Just stay alert because the pilgrim will be very happy believing they are solving the problem and can relax while they await the new hardware.
 
7) We JUST need to tune a small part of the system – there is often a hope that only a small store procedure or code element, once tuned, will yield the magical performance improvement or that all the performance problems can be found in one part of the architecture. At last the pilgrims are getting somewhere on their journey allowing you to progress too – some measurements at least have to be taken to identify the bad boy item. You can smile now; the journey’s nearly over..

Journey’s End – Wow! we do have a performance problem – at last your bunch of pilgrims have made the journey to true enlightenment. Like any religious journey it is full of self-doubt and distractions along the way, but at last you can finally start to solve the problem. Just hope now that a new project manager doesn’t get involved and you have to start at step 1 again.

Some projects have less potential areas for deviating from the true path, and some have more, but each pilgrim has to find his own way. Your job is to guide and educate!

Performance Test Best Practise

An old colleague asked if there are any standards identifying best practise in performance testing. I could not think of any but it started me thinking about what is best practise. Here are my thoughts on some areas of best practise in Performance Testing. They are NOT in any order of importance and the list is NOT exhaustive.

1.) Have a defined process and constantly refine it.
Before you start you should have a process defined and you should make sure you review this process to add improvements. The process needs to be flexible in order to accomodate different types of projects, from benchmarking a core application through to making sure an e-commerce site can handle the Christmas rush.

2.) Define the Goals up front.
This seems obvious, but you need to understand why are you testing and what the performance goals of the system under test are. (Note I use the word goals not requirements). Here, the move to ITIL may help where service design packages developed early on should include the performance requirements.

3.) Let Risk guide you.
The performance risk and consequences of failure should guide the type and amount of performance testing you do. Don’t just test what is easy to test.

4.) Don’t be afraid to say no.
If you are given responsibility for signing off on the performance of the system, you are the expert. If, subsequently, you are not given enough time or the correct tools then be prepared to say that you cannot test the system adequately. Remember that the caveats you place in your final report may never make it into the summary presented to the management board!

5.) Get the workload right.
If you don’t test the system with the correct workload it won’t matter if everything else is perfect – the results will be wrong. This means you need to understand user behaviours and their frequency. Don’t forget to include error scenarios as well.

6.) Develop Quality Scripts.
Make sure your scripts emulate user behaviour as much as possible and remember that users make mistakes, leave processes early and have comfort breaks! Also, make sure your script check what is returned to the user is what is expected.

7.) Select an appropriate test environment.
Is best practise using a production-sized test environment? Not sure, but make sure your test environment is sized and up to the job involved. Make sure you can collect the necessary data about the performance of that environment during the load test.

8.) Run your performance tests for long enough and often enough.
Make sure your tests are repeatable and that the results they produce are statistically valid.

9.) Participation.
Get all the people that need to be involved in the performance test working togther. Unless you are superhuman and multi-skilled you will need DBAs, administrators, developers, Project Managers, etc., to assist in the test. Remember, for the best results get these stakeholders involved in the process early on.

10.) Remember, people want results not data.
Don’t just present the canned report from the performance test tool; you need to analyse the results and present the key facts of the load test. And remember that different people will want different results from the load test – a manager will want to know if it passed whereas the DBA will want to know if the SGA is sized correctly, for example.

Small vs Large Scale Performance Test Environments

I have just added to the website a presentation that looks at sizing and extrapolation techniques for people considering building a small scale performance test environment instead of a large full scale performance test environment. In the paper several approaches are considered.
Factoring – This is where the architecture is easily scaled and therefore the performance test can be undertaken on a subset of the hardware.

Dimensioning – The architecture has known bottlenecks that drive the performance such as a central DB. The performance test environment must contain the bottleneck component but other components may not need to be representative of a full sized environment.

Modelling – This examines the use of modelling to take results from a small scale environment and predict the results for a larger scale environment.

Flipping – This looks at creating test environment that can be have the correct amount of resources allocated to them for a “full scale” performance test for example during off hours and then revert to a smaller scale performance test environment at other times.

Full Scale – Finally the advantages and disadvantages of a full scale performance test environment are discussed.

Finally the caveat for these techniques is that for any testing on a small scale performance test environment does not guarantee that all performance problems will be discovered due to application/scalability constrains that may only appear in the full sized environment!

You can download the presentation from here.