By annie shum | October 22, 2009
Annie Shum [email protected]
Invariably, the underlying questions at the heart of every technology or business initiative are less about technology but, as Clive Thompson of Wired Magazine observed, more about the people (generally referred to as the users and consumers in the IT industry). For example, “How does this technology/initiative impact the lives and productivity of people?” or “What happens to the uses/consumers when they are offered new power or a new vehicle of empowerment?” Remarkably, very often the answers to these questions will directly as well as indirectly influence whether the technology/initiative will succeed or fail; whether its impact will be lasting or fleeting ; and whether it will be a strategic game-changer (and transform society) or a tactical short-term opportunity.
One can approach some of the Cloud-friendly applications, e.g. large scale QA and load stress testing in the Cloud, either from a tactical or from a strategic perspective. As aforementioned, the answer to the question “What happens to the uses/consumers when they are offered new power or a new vehicle of empowerment?” can influence whether a new technology initiative will be a strategic or tactical. In other words, think about the bacon-and-eggs analogy where the chicken is involved but the pig is committed. Look for new business models and innovation opportunities by leveraging Cloud Computing that go beyond addressing tactical issues (in particular, trading CapEx for OpEx). One example would be to explore transformative business possibilities stemming from Cloud Computing’s flexible, service-based delivery and deployment options.
Approaching Large-scale QA and Load Stress Testing in the Cloud from a Tactical Perspective
Nowadays, an enterprise organization is constantly under pressure to demonstrate ROI of IT projects. Moreover, they must be able to do this quickly and repeatedly. So as they plan for the transition to the Cloud, it is only prudent that they start small and focus on a target area that can readily showcase the Cloud potential. One of the oft-touted low hanging fruit of Cloud Computing is large scale QA (usability and functionality) testing and application load stress testing in the Cloud. Traditionally, one of the top barriers and major obstacles to conducting comprehensive, iterative and massively parallel QA test cases is the lack of adequate computing resources. Not only is the shortfall due to budget constraint but also staff scheduling conflicts and the long lead time to procure new hardware/software. This can cause significant product release delays, particularly problematic with new application development under Scrum. An iterative incremental development/management framework commonly used with Agile software development, Scrum requires rapid successive releases in chunks, generally referred to as splints. Advanced Agile users leverage this chunking technique as an affordable experimentation vehicle that can lead to innovations. However, the downside is the rapid accumulation of new testing needs.
By providing virtually unlimited computing resources on-demand and without up-front CapEx or long-term commitment, QA/load stress and scalability testing in the Cloud is a good starting point. Especially, the flexibility and on-demand elasticity of Cloud Computing meet the iterative requirements of Agile on an on-going basis. More than likely it will turn out to be one of the least risky but quick ROI pilot Cloud projects for enterprise IT. Case in point, Franz Inc, opted for the Cloud solution when confronted with the dilemma of either abandoning their critical software product testing plan across dozens of machines and databases or procuring new hardware and software that would have been cost-prohibitive. Staging the stress testing study in Amazon’s S3, Franz completed its mission within a few days. Instead of the $100K capital expense for new hardware as well as additional soft costs (such as IT staff and other maintenance costs), the cost of the Amazon’s Cloud services was under $200 and without the penalty of delays in acquisition and configuration.
Approaching Large-scale QA and Load Stress Testing in the Cloud from a Strategic Perspective
While Franz Inc. leverages the granular utility payment model, the avoidance of upfront CapEx and long-term commitment for a one-off project, other entrepreneurs have decided to harness the power of on-demand QA testing in the Cloud as a new business model. Several companies, e.g. SOASTA, LoadStorm and Browsermob are now offering “Testing as a Service” also known as “Reliability as a Service” to enable businesses to test the real-world performance of their Web applications based on a utility-based, on-demand Cloud deployment model. Compared to traditional on-premises enterprise testing tool such as LoadRunner, the Cloud offerings promise to reduce complexity without any software download and up-front licensing cost. In addition, unlike conventional outsourcing models, enterprise IT can retain control of their testing scenarios. This is important because comprehensive QA testing typically requires an iterative process of test-analyze-fix-test cycle that spans weeks if not months.
Notably, all three organizations built their service offerings on Amazon EC2 infrastructure. LoadStorm launched in January 2009 and Browsermob (open source) currently in beta, each enable users to run iterative and parallel load tests directly from its Website. SOASTA, more established than the aforementioned two startups, recently showcases the viability of “Testing as a Service” business model by spawning 650 EC2 Servers to simulate load from two different availability zones to stress test a music-sharing website QTRAX. As reported by Amazon, after a 3-month iterative process of test-analyze-fix-test cycle, QTRAX can now serve 10M hits/hour and handle 500K concurrent users.
The bottom line is there are effectively two different perspectives: tactical (“involved”) versus the strategic (“committed”) and both can be successful. Moreover, the consideration of tactical versus strategic is not a discrete binary choice but a granularity spectrum that accommodates amalgamations of short term and long-term thinking. Every business must decide the best course to meet its goals.
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