Welcome!

Silverlight Authors: Automic Blog, Michael Kopp, AppDynamics Blog, Kaazing Blog, Steven Mandel

Related Topics: Silverlight, Java IoT, Microservices Expo, Microsoft Cloud, Containers Expo Blog, @CloudExpo, @DevOpsSummit

Silverlight: Article

Combining Agile with Load and Performance Testing: What Am I in For?

Load and performance testing successfully in an Agile way can save an organization a lot in costly bug fixes

Agile software development isn't really a "new" trend anymore. I mean, the Agile Manifesto turns 13 years old next month and while that might be early adolescence in human years, it's downright ancient as far as trends in IT are concerned. However, one area that has yet to fully mature is the implementation of non-functional testing practices in a Continuous Testing sort of way that can keep pace with more Agile development teams. Load and performance testing definitely fall into that category. You might be a performance tester on a team that is just starting to do more iterative development or a more experienced Agile tester looking to add load and performance testing to your workflow; either way, you'll likely want to know what you're in for.

Agile development practices can help teams achieve faster time to market, adapt to changing requirements, provide a constant feedback loop, etc. The benefits of load and performance testing include determining how much load an application can handle before it crashes in production, when to add another server, when to reconfigure the network, where code needs to be optimized, etc.  What is less well known is the fact that the combination of the two practices can lead to additional benefits that go beyond just the sum of the benefits of each practice, i.e. 1+1=3.

Some of these benefits include:

Avoiding Late Performance Problem Discovery
When load and performance testing are pushed off until the end of a development cycle, there is often little to no time for developers to make changes. This can cause teams to push back release dates and delay getting features out the door that customers need. Alternatively, if the issues are minor, teams may decide to proceed and launch the application into production while accepting the heightened risks.  If the performance problems are more fundamental, they could even require painful architectural changes that could take weeks or months to implement.

Making Changes Earlier When They Are Cheaper
By including load and performance testing in Continuous Integration testing processes, organizations can catch performance issues early before they get much more costly to fix. Developers can instantly know that the new feature in the latest build has caused the application to no longer meet Service Level Agreements (SLAs). They can fix the problem then and there before it becomes exponentially more expensive. This is especially true on Agile teams when discovering a performance problem weeks later could mean that it actually occurred several builds ago which makes the task of pinpointing the root cause a nightmare.

Guaranteeing Users Get New Features, Not New Performance Issues
In some Agile organizations, changes are happening incredibly fast. It's possible for a new feature or some new functionality to get checked into source control, run through a Continuous Integration build, pass all of the automated tests, and get deployed to the production server in a matter of minutes. But if that code wasn't optimized to handle the number of simultaneous users seen at the worst peak times, it could cause the whole system to crash. Integrating load testing into the process before these changes are deployed to production can ensure that your users get all the goodies they want without the bad user experiences. This can save your company thousand or even millions in lost revenue from users switching to competitors' apps or bashing your brand because of the problems they experienced with your app.

In the same way that combining Agile with load testing can provide unique benefits, it can also present your teams with unique challenges they may not have experienced in the past.

Shorter Development Cycles Require More Tests in Less Time
Load and performance testing are usually pushed off until the end of a development cycle. With Agile, development, cycles are much shorter, and load & performance testing can get pushed off until the last day of a sprint or sometimes it's done every other sprint. This can often result in code being released without being adequately tested or user stories slipping to the next release once they have been tested. Conceptually the solution is to do the testing earlier in the development cycle, but that's easier said than done with many teams lacking the resources and tools to make it happen.

"Working" Code Does Not Always Perform Well
So much focus for developers on Agile teams is put on delivering "working" code, but is code really "working" if it fails when the application is under load? Should user stories and tasks really be marked as "done" if the code associated with them causes the application to crash with 100 users? What about 1,000? 100,000? The pressure to get code out the door is high, but so is the cost of having an application crash in production.

Developers Need Feedback NOW
Agile developers need to know more than just the fact that their code is causing performance issues: they need to know when their code started causing problems and what story they were working on when the issue started. It's a huge pain for developers to be forced to go back and fix code for a story they worked on weeks or months ago. It also means they can't spend time working on getting new features out the door. Detecting performance issues early in the cycle so you can deliver important feedback to developers quickly is crucial to saving costs.

Automating the Handoff from Dev to Ops Can Feel Risky
While DevOps and Continuous Deployment are still fairly young practices, the fear felt by operations teams that new changes in code will slow down or even crash the application when it is deployed in production has been around forever. Automating some of the testing in the Continuous Integration process can help to ease some of this fear, but without adequate performance testing included, the risk is still real. Ops teams know well the huge impact application downtime can have on the business.

As daunting as some of these challenges seem, don't lose sight of the benefits you'll receive. Load and performance testing successfully in an Agile way can save an organization a lot in costly bug fixes and could make a tester a hero to both development and operations teams alike.

Not quite sure how to get started? Stay tuned for my next blog on best practices for Agile load and performance testing.

More Stories By Tim Hinds

Tim Hinds is the Product Marketing Manager for NeoLoad at Neotys. He has a background in Agile software development, Scrum, Kanban, Continuous Integration, Continuous Delivery, and Continuous Testing practices.

Previously, Tim was Product Marketing Manager at AccuRev, a company acquired by Micro Focus, where he worked with software configuration management, issue tracking, Agile project management, continuous integration, workflow automation, and distributed version control systems.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


IoT & Smart Cities Stories
The deluge of IoT sensor data collected from connected devices and the powerful AI required to make that data actionable are giving rise to a hybrid ecosystem in which cloud, on-prem and edge processes become interweaved. Attendees will learn how emerging composable infrastructure solutions deliver the adaptive architecture needed to manage this new data reality. Machine learning algorithms can better anticipate data storms and automate resources to support surges, including fully scalable GPU-c...
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by ...
The explosion of new web/cloud/IoT-based applications and the data they generate are transforming our world right before our eyes. In this rush to adopt these new technologies, organizations are often ignoring fundamental questions concerning who owns the data and failing to ask for permission to conduct invasive surveillance of their customers. Organizations that are not transparent about how their systems gather data telemetry without offering shared data ownership risk product rejection, regu...
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...
Predicting the future has never been more challenging - not because of the lack of data but because of the flood of ungoverned and risk laden information. Microsoft states that 2.5 exabytes of data are created every day. Expectations and reliance on data are being pushed to the limits, as demands around hybrid options continue to grow.
Digital Transformation and Disruption, Amazon Style - What You Can Learn. Chris Kocher is a co-founder of Grey Heron, a management and strategic marketing consulting firm. He has 25+ years in both strategic and hands-on operating experience helping executives and investors build revenues and shareholder value. He has consulted with over 130 companies on innovating with new business models, product strategies and monetization. Chris has held management positions at HP and Symantec in addition to ...
Enterprises have taken advantage of IoT to achieve important revenue and cost advantages. What is less apparent is how incumbent enterprises operating at scale have, following success with IoT, built analytic, operations management and software development capabilities - ranging from autonomous vehicles to manageable robotics installations. They have embraced these capabilities as if they were Silicon Valley startups.
As IoT continues to increase momentum, so does the associated risk. Secure Device Lifecycle Management (DLM) is ranked as one of the most important technology areas of IoT. Driving this trend is the realization that secure support for IoT devices provides companies the ability to deliver high-quality, reliable, secure offerings faster, create new revenue streams, and reduce support costs, all while building a competitive advantage in their markets. In this session, we will use customer use cases...