Welcome!

Java IoT Authors: Liz McMillan, Elizabeth White, Yeshim Deniz, Zakia Bouachraoui, Pat Romanski

Related Topics: Mobile IoT, Java IoT, Microservices Expo, Containers Expo Blog, Agile Computing

Mobile IoT: Article

Mobile Performance Testing: Demystified

A look at how to approach performance / load testing extranet mobile applications

How does the approach to performance / load testing extranet mobile applications change from testing other RIAs? In some ways, not much. Yes, the user activity for every mobile application will be unique, but the same goes for every web application. Different technology stacks, different deployments, different load patterns, different types of users profiles, and different content delivery… All make each web application, in its own right, unique. The approach to methodical performance testing for capacity planning and identifying scalability issues remains the same.

The mobile application could be a web site accessed via a URL or it could be a native mobile application loaded onto your device. The list of mobile devices keeps growing, but currently the most popular are Tablets, PDA’s, Droids, Blackberry, iPhone, iPad, Smartphones, etc. Supporting testing from these devices is important, but what’s even more important in your mobile load testing strategy is to generate traffic that represents the way users are actually going to access this mobile application. Whether it’s an ecommerce application being accessed via a Safari browser or an installed mobile app which makes webservice calls out to a feed, the load testing tool must generate the correct type of user connections and generate realistic load. This is the exact same challenge with testing non-mobile web applications as well.

Mobile applications are being developed and deployed rapidly, using a variety of cutting edge protocols and behaviors. The load tool must support the latest technologies in order to effectively address mobile apps. You need the ability to record a script either straight from the mobile device, from an emulator, or from a mobile browser. Handling behaviors such as asynchronous behaviors of PUSH technology becomes a requirement in many mobile applications. As important as the design of a performance test case scenario, now the load generation piece must either mimic the unique characteristics of mobile devices or have the ability to generate the load straight from the device. For example: headers, number of connection threads, etc. All these characteristics are important elements to emulate when conducting web and mobile performance testing.

What’s different about mobile? Mobile applications are being built using network efficiencies which aim in relying less on the intermittent characteristics of mobile networks. It is the variable network conditions that cause delays in response times which in turn affect the duration that ports or sockets are kept open — an environmental resource usage that is frequently seen with mobile applications. It’s because of this variable network connectivity that the user experience isn’t always an absolute known: the speed of the network depends on your device, your network plan (WIFI, 3G, 4G, ATT, etc), your geographic location, network connectivity, the network usage vs. bandwidth, and so on. Your load tool needs to have the option of emulating these bandwidth speeds to more accurately capture response times. Developers concentrate on what can be controlled: building efficient mobile apps which require less network overhead. There are many techniques to reduce the network traffic, all of which contribute to making responses less dependent on the network. “Conservation” is the approach of reducing network roundtrips by decreasing embedded requests, using local storage on the device for caching static files, enabling transfer compression, avoiding redirects, minimizing data content size, reducing number and length of cookies, removing lint from code (white spaces and comments), organizing the delivery for incremental rendering, aggregating requests and using PUSH behaviors. Creating lighter-weight mobile applications allows the overall end user experience to be less dependent on the device network vulnerabilities.

In the end however, the approach to load testing an extranet mobile application remains the same. You have goals: number of concurrent users, expected response times, load patterns etc. Using the right load tool, you can emulate this activity. You then identify capacity and saturation points and alleviate these bottlenecks in order to scale to a higher workload. You already know the drill for doing this and if you don’t, please refer to 11 Tips to Becoming a Better Performance Engineer. It sounds simple, but mobile performance testing is an interesting and vast topic so check back in for future posts on the subject from some of my colleagues.

More Stories By Rebecca Clinard

Rebecca Clinard is a Senior Performance Engineer at Neotys, a provider of load testing software for Web applications. Previously, she worked as a web application performance engineer for Bowstreet, Fidelity Investments, Bottomline Technologies and Timberland companies, industries spanning retail, financial services, insurance and manufacturing. Her expertise lies in creating realistic load tests and performance tuning multi-tier deployments. She has been orchestrating and conducting performance tests since 2001. Clinard graduated from University of New Hampshire with a BS and also holds a UNIX Certificate from Worcester Polytechnic Institute.

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...