Posts tagged Performance
HP Aims to Redefine Apps Performance Testing with Cloud Platform
Feb 7th
When mobile users feel they don’t like how their apps perform after the first trial, some 75% of them won’t launch the app again. That’s the metric cited by engineers and marketers at HP Software, who note that this first wave of mobile apps brought forth by the iPhone has resulted in a glut of programs that make even the best performing mobile hardware into a pocket full of silicon cement.
This morning, HP begins a repurposing of the performance testing tools for Web sites that it gained through the Mercury Interactive acquisition of 2006, for the mobile apps era. It’s unveiling what it calls “LoadRunner-in-the-Cloud,” complete with hyphens. It will act as an off-premise testing platform for mobile apps that are deployed as services, simulating the activity generated by thousands of users simultaneously to gauge the resilience of servers and resources. This way, you might not have to disappoint three-fourths of them to learn how well your service holds up.
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“The application architecture itself is the performance bottleneck nine out of ten times,” says Matt Morgan, HP Software’s global senior director of solutions marketing, in an interview with RWW. “By monitoring these services and knowing how long a transaction spends waiting for a data retrieval or a logic process, or some other storage function to occur, you can pinpoint the modules inside the service that have the most potential to slow an application under load. You can find out which services are not scaling.”
When applications are deployed on PaaS platforms such as Heroku and Windows Azure, Morgan says, a great deal of the complexity of how the software interfaces with the hardware is abstracted into obscurity. The architectural concept that I dubbed composite applications in 1991 has expanded to a seemingly unmanageable number of tiers. With the shift to mobile architecture, much of the burden of providing performance has shifted off of the front-end client, and onto the server. And in-between those two tiers are any number of platforms. “So this idea that the software is a composition, gets even more complicated,” he remarks.
“We correlate the front-end story to the back-end problem. And if you think about just the complexities of performance monitoring, if you don’t do correlation, you can end up with an enormous collection of logs and metrics that don’t actually mean anything to the tester,” he continues. “The tester really cares about, how many users can the system support, and what will these users experience when they do concurrently hit their system?”
Mobile apps typically break at some point, and Morgan notes, they don’t bend very much before they do. Maybe an app performs well with 300 simultaneous users, and then fails completely at 325. So LoadRunner-in-the-Cloud (hereafter LRC) finds the breaking point, which is typically somewhere. Once that’s done, it relies upon feedback provided by a vast network of back-end monitors, probing such factors as SQL queries, server metrics, and diagnoses of the method calls being invoked inside the service. “By correlating how much time it takes for a transaction to hit these things, you can actually attain a pretty clear picture, and start to show that the areas of your application that are causing problems have a distinct performance impact.”
The protocol HP uses for emulating user activity in AJAX Web applications, called TruClient, is explained in this video. TruClient has been extended for LoadRunner-in-the-Cloud.
Identifying your app by how and where it breaks
The result is a kind of “stress footprint” that characterizes the resilience state of your mobile app. The space in which this footprint appears is the scenario, which is LRC’s term for a repeatable test. Each test helps establish a firm baseline, which is then replicated identically for different problem sets – different numbers of users. This way you’re testing how the same code scales up, including with each increment – LRC adds test users on an incremental scale, not logarithmic. “You’re trying to determine, if the exact same actions take place on the server, do things improve with the change?” says the HP senior director. “Scenarios allow you to digitize that load, creating a one-click re-execution capability, which is very important in an iterative world. You run your load test, you identify your problem, you make your change, and you go back to your scenario and run the exact same test.”
Overlaying the results gives you your best metric as to performance, which in a cloud-based scenario is indeed capable of improving with incrementally added users.
Results from previous load tests, including with earlier builds of your apps, are recorded as snapshots. New test results can be overlaid atop these earlier ones, in order to determine what code changes made the biggest impact. “We give you the capability to leverage that information inside of an operational monitoring solution, but if you wanted to monitor a Web or mobile app going forward for functionality, and you want to have visibility to the way it should run, you can use the metrics from LoadRunner to compare against what it’s actually doing in production. That gives you the snapshot of the lab world, where everything works, to the production world where everything’s real.”
LoadRunner-in-the-Cloud is being offered now to HP partners in the U.S. and Canada, and will be rolled out through OEM partners on their own timetables. Pricing will be determined by the party making the sale.
No, no, not that Lode Runner! Somebody get our graphics department off the Apple II and replace this!
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[Case Study] Lessons in High Performance Computing with Open Source
Feb 2nd
Providing adequate software and tools for researchers has always been of great importance to organizations, but has often come at a great cost. In an era of constantly evolving technology and rapidly dwindling budgets, my IT team has had to work with a large pool of researchers to provide cost-effective solutions that meet the ever-growing demand for innovation and computing power.
I am an Information Technologist for the Department of Statistics and Probability at Michigan State University. The Department is home to award-winning faculty with a wide variety of expertise in fundamental and interdisciplinary research, and over 100 graduate students from all over the world. Keeping the faculty and students ahead of their research is a constantly evolving challenge for my team and I.
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Evolution of Statistical Software
Erik Segur is an Information Technologist for the Department of Statistics and Probability at Michigan State University.
For many years, most statistical analysis in our department was done in Matlab, S-Plus, SPSS or SAS. Even with a Higher Educational discount, most of the software required yearly renewal fees that quickly devoured our IT budget. Things started to change when the R language, which was first developed in 1993, began to gain traction in statistics communities in the early 2000s. R is an open source programming language and software environment that is used for statistical computing and data analysis. Several years ago, we began the transition at Michigan State to R; today, it is used for the majority of the research in the department–as well as being a central focus of our statistics curriculum. By switching to the free, open source version of R, our department has been able to cut thousands of dollars each year in software costs and have focused more on fueling and expanding research.
Lesson #1: The Shortcomings of Open Source
As more people began to use R and the analysis became increasingly complex, researchers began to face a large problem: time. Research was taking several months to complete in terms of processing jobs. Often, there is a need to run the calculations several times to ensure accuracy; waiting three months for one to complete was simply not feasible. It was taking R this long to process the jobs because the iterations were computed in serial, one right after another, using only one processor core at a time.
Bo Cowgill from Google once said “The best thing about R is that it was developed by statisticians. The worst thing about R …is that it was developed by statisticians.”
Until the spring of 2010, R was a 32-bit application and could only access a limited amount of memory. The maximum amount of memory that could be accessed by R was only 3GB. When dealing with large datasets researchers were quickly running out of memory as well as discovering they needed a solution to deal with large data efficiently.
Bo Cowgill from Google once said “The best thing about R is that it was developed by statisticians. The worst thing about R …is that it was developed by statisticians.” Even though R was–and still is–constantly evolving, the department needed a solution that could keep up with hardware technology and compute calculations in an efficient, scalable manner.
Lesson #2: Find Commercial Enhancements for Open Source
Our search for a more effective version of R ultimately brought us to a product called Revolution R Enterprise by Revolution Analytics, which provides commercial support and software for open source R. It takes advantage of multiple processor cores by using optimized assembly code and efficient multi-threaded algorithms that use all of the processor cores simultaneously. Although this addressed a lot of the issues of open source R, professors were only using Revolution R on their desktops. The next question was, how we could combine the power of our servers to dramatically decrease our computation times?
Lesson #3: Expanding to Infinity and Beyond
Open Source R is a memory-bound language. This means that all of the data, matrices, lists etc. need to be stored in memory. Issues quickly arose when data sets became several gigabytes large and were too big to fit into memory. This required implementing parallel external memory algorithms and data structures to handle the data. These challenges were tackled by Revolution Analytics as they developed the R language for a High Performance Computing (HPC) environment.
There are often great pieces of software created through open source, but they generally lack key features needed for an enterprise environment. Combined with commercial backing and expertise, these projects can be further developed and expanded to meet the needs of large-scale enterprise environments.
In 2010, Revolution Analytics offered Revolution R Enterprise free for academic users and shifted the focus of their enterprise software to big data, large scale multiprocessor computing and multi-core functionality. Revolution Analytics was going to tackle everything the department needed. The evolution was complete: open source R went from an inefficient single core program to a HPC environment.
Once the department could schedule R jobs in an HPC environment, the demand began to drastically increase. The HPC cluster is now scheduling more than four times the amount of jobs that were scheduled in previous semesters, from 200 jobs over a year ago to over 800 jobs this past semester. Jobs that were taking over three months to complete on open source R were completed in less than a few days with Revolution R. Computational jobs are now run multiple times with significantly higher levels of accuracy than ever before.
Conclusion
There are often great pieces of software created through open source, but they generally lack key features needed for an enterprise environment. Combined with commercial backing and expertise, these projects can be further developed and expanded to meet the needs of large-scale enterprise environments. IT departments can provide enhanced solutions to their users that adapt to the expanding world of cloud and High Performance Computing environments–all while minimizing the impact on a shrinking budget.
Photo courtesy of Shutterstock.
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AdWords Performance Grader Tool Touts More Accurate PPC Data Reports
Jan 30th
WordStream has updated their AdWords Performance Grader, released in August, 2011. Peer report data is now more accurate, as the tool has analyzed almost half a billion in annualized PPC spend, about 1.5 percent of Google’s total ad revenue.
View full post on Search Engine Watch – Latest
Google AdMob: A Performance Marketer’s Opinion
Jan 24th
Unless your products are extremely broad appeal or you’re selling mobile download bale goods (e.g., apps, books, music or video), let me save you some time, frustration and money: there is no apparent way to leverage AdMob for performance marketing.
View full post on Search Engine Watch – Latest
topseos.com Ranks ResultFirst as Best Pay For Performance SEO Company for … – Press Media Wire
Jan 14th
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topseos.com Ranks ResultFirst as Best Pay For Performance SEO Company for …
Press Media Wire The independent authority on Search vendors, topseos.com, has named the best pay for performance SEO companies in the online marketing industry for the month of January 2012. ResultFirst has been named the best SEO service which offers services on a … |
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SEO India Services Company, SEO Corporation Launches Performance Based SEO Plan – SBWire (press release)
Jan 3rd
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SEO India Services Company, SEO Corporation Launches Performance Based SEO Plan
SBWire (press release) SEO India News: SEO Services Company in India which provides Search Engine Marketing Services to companies across the Globe announced Performance based SEO Services. In the Performance based SEO India Services you don't need to pay a single penny to … |
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Market Target, San Diego Leading SEO Consulting Team Offers Performance Based … – San Francisco Chronicle (press release)
Dec 21st
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Market Target, San Diego Leading SEO Consulting Team Offers Performance Based …
San Francisco Chronicle (press release) Market Target, an SEO in San Diego and Phoenix SEO services company announced today a new pay for performance pricing model. Market Target's San Diego SEO Consulting team has helped an unprecedented number of its clients successfully reach the first … |
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Market Target, San Diego Leading SEO Consulting Team Offers Performance Based … – Promotion World (press release)
Dec 21st
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Market Target, San Diego Leading SEO Consulting Team Offers Performance Based …
Promotion World (press release) San Diego, California (PRWEB) December 21, 2011 – Market Target, an SEO in San Diego and Phoenix SEOservices company announced today a new pay for performance pricing model. Market Target's San Diego SEO Consulting team has helped an unprecedented … |
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Market Target, San Diego Leading SEO Consulting Team Offers Performance Based … – PR Web (press release)
Dec 21st
 PR Web (press release) |
Market Target, San Diego Leading SEO Consulting Team Offers Performance Based …
PR Web (press release) Market Target, an SEO in San Diego and Phoenix SEO services company announced today a new pay for performance pricing model. Market Target's San Diego SEO Consulting team has helped an unprecedented number of its clients successfully reach the first … |
View full post on SEO – Google News
Galaxy Nexus A Step Up For Android HTML5 Performance
Dec 14th
When it comes to HTML5 implementation, Android has historically lagged behind most of the other major mobile platforms. iOS is considered the crown jewel of HTML5 performance and even Windows Phone has faired better than Android. That may all be about to change.
In Sencha’s latest HTML5 benchmark, the Samsung Galaxy Nexus running Android 4.0.1 Ice Cream Sandwich was put through the paces. The newest flagship Android device acquitted itself well. As Sencha puts it; “The Galaxy Nexus is a big step forward for developers looking to leverage HTML5 on Android.” See the details below.
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What does good HTML5 need? A good browser, of course. The native Android browser has been historically subpar. Sencha finds that the Ice Cream Sandwich browser is a big step forward for Android. It is not iOS 5 quality, but it is better than what came before. It supports most of the HMTL5 specifications and renders well.
When Sencha does its HTML5 benchmarks, it runs a series of tests including JavaScript performance, HTML5/CSS3, rendering performance and accuracy. Sencha uses Acid3 for rendering performance, Modernizr for browser optimization, SunSpider for JavaScript benchmarks along with Sencha-specific tools Animator and Touch Kitchen Sink.
The Galaxy Nexus scores a perfect 100 on the Acid3 test. Yet, Sencha found that rendering was not completely perfect, with some imperfections such as a red/pink box in the top right of the rendering that shows ICS has almost-but-not-quite perfect rendering. The Modernizr test, which is used to see the nuts and bolts of the inside of the browser, faired well. Font-face, geo-location and CSS3 were all fully supported. Animations, relections, 2D/3D transformations and transitions were all found to be supported. This means that ICS finally brings the ability to build rich user interfaces to Android.
Web Workers and Web Sockets are missing from Android 4.0 as well as weak supprt for Input Types and WebGL. It boils down to the fact that Ice Cream Sandwich does not support a variety of APIs that iOS 5 does. See the list below.
In terms of performance, the SunSpider Javascript tests were what Sencha expected with a smartphone running a dual-core ARM processor. The Galaxy Nexus does well though does not outperform other platforms like the iPad 2, BlackBerry PlayBook or Kindle Fire.
The Nexus held up well when put through the paces of the Sencha Animator, meaning most games built with CSS3 should run perfectly. Other tests such as Canvas rendering and pinch/zoom qualities also performed better than expected, far above other Android builds.
HTML5 audio and video, some of the trickier implementations of HTML5, is fully supported by Ice Cream Sandwich. Sencha said that the Galaxy Nexus was the first phone to run the html5video.org test video inline, something that iOS 5 does not do.
The final test is the Kitchen Sink test. As you might expect, this is a experiment that throws everything possible at an HTML5 app (including, as they say, the kitchen sink) to see how it performs. As expected with such a major upgrade, Ice Cream Sandwich handles the Kitchen Sink better than any other Android build. It was not perfect. Not many platforms escape the Kitchen Sink unscathed. But it was still a decent performance. Rounded corners look smooth, multi-touch is supported and scrolling is improved. White-screen flashes in the rendering were still seen and page transitions often causes the browser to “blink.”
To what does it all boil down? Android is finally an acceptable HTML5 platform. The hiccups, crashes and poor rendering seen with previous builds have mostly been eliminated. “Although still behind the current HTML5 gold standard of iOS5, Android 4.0 is night and day compared to previous versions,” Sencha reports.
For developers working to create an HTML5 mobile Web app ecosystem for the largest mobile platform in the world, that is welcome news to ring in the new year.
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