2019 Performance Testing Trends Part Two

Last week, we published part one of an article on the performance testing trends we see impacting us in 2019. In this week’s post, we’re going to dive into the remaining trends:

  • Increased use of AI and APM to fully automate test processes
  • Continued support for what Gartner refers to as the bimodal enterprise 
  • A broader approach to testing Enterprise Resource Planning applications such as SAP

Increased use of AI and APM to Fully Automate Test Processes

The volume of performance tests that need to be conducted on any given day has grown significantly. CI/CD has reduced the time it takes for the code to get from development to production. Shorter release cycles provide businesses with the competitive advantage needed to satisfy market demand. However, they can also burden a company’s test infrastructure, particularly when it comes to performance testing. The code needs to be tested. There’s no way around this. But, the demand has grown beyond manual testing. It’s also expanded beyond the capabilities of automation processes that use simple procedural scripting. More is needed.

Artificial Intelligence (AI) and Application Performance Monitoring (APM) technologies provide the path forward to allow companies to bridge the gap between the speed of software releases and the need to ensure quality code. The emerging trend among forward-thinking companies is to take automated testing to the next level by applying AI to respond to events and information generated by APM tools. In other words, APM emits information, and AI conducts performance testing based on that information.

For example, take this scenario: AI detects patterns in high network latency among nodes in a distributed application. AI takes this latency information and binds the node to the application(s) running on the node. AI goes one step further by inspecting the nodes’ system logs to correlate request activity to network latency. This information is used by AI to run a series of performance tests that profile code activity on the identified applications to determine existing and likely points of failure. This is all done automatically with no human interaction.

The trend to use AI and APM tools to identify potential problems and conduct testing without human assistance are going to stay on an upward trajectory as the tools become more mainstream, easier to use.

Continued Support for the Bimodal Enterprise

A few years back in response to a sea of change brought forth by continued technology advancement, Gartner coined the term Bimodal IT. The concept’s design was to articulate how enterprises needed to strike a balance between new gen technology investment without impacting the legacy environment. From a software development standpoint, bimodal enables the opportunity to choose between Agile and waterfall.

The fact is that while some companies use Agile, more still follow the waterfall development, leaving the rest to support a combination. Companies need to be realistic in their approach to testing, planning their test strategies accordingly.

Support for testing in the bimodal enterprise can get expensive, particularly as it relates to tooling. But, companies can control these costs with accurate planning. It’s true that the waterfall method does have hard boundaries between the different phases and personnel associated with the release process. Many test practices found in Agile can be applied as a waterfall. Well encapsulated testing methods, such as unit testing, can be implemented in both Agile and waterfall environments in an agnostic manner. And, making extensive use of automated testing can be done in a bimodal enterprise.

The trick for supporting a bimodal enterprise is to identify the common aspects of the Agile and waterfall approaches and then share a standard set of tools and techniques that apply to both. Resource sharing in a bimodal enterprise saves time and money. It also makes the transformation from waterfall to Agile an easier road to follow when required.

A Broader Approach to Testing Enterprise Resource Planning Applications such as SAP

Enterprise Resource Planning (ERP) software has gone from being large, monolithic applications to a collection of components that can be implemented on a mix and match basis. Nowhere is this more evident than with the industry-leading ERP, SAP. SAP started on the mainframe with its R2 product. Then it migrated to commodity client-server environments with R3. Both R2 and R3 were big, expensive and monolithic. Today the current version is SAP ERP Central Component (ECC). In the ECC model, there are a core set of components central to SAP that can be extended by installing additional components on an as-needed basis. While SAP has always had the notion of packages to be added, the overall architecture has become more encapsulated as is typical of a component-based approach.

As ERPs go component-based, so too have companies in terms of performance testing. ERP performance testing has become broader, but also more focused. Instead of having a single, standard suite of performance tests, companies are having to tailor their approach to performance testing based on the component configuration of the given ERP. Each component must be approached as a testing scenario in itself. The work of test designers is to come up with performance tests that are geared to the particular component scenario.

For some companies, a component-based strategy can represent a new way of conducting business. Given the current trend, they will need to adapt. Fortunately, they will not be going into unknown territory. The expertise and resources required to make the transition are readily available. It’s just a question of having the willingness as well as taking the time and energy required to adjust.

Putting it All Together

If nothing else, we think 2019 will be an exciting year in performance testing. As the costs of using AI and APM tools decrease, and as the technologies involved get more straightforward to use, we’re going to see them increase as performance testing mainstays. We’re also going to see an embrace for Agile and waterfall processes in the Software Development Lifecycle. Companies cannot afford to abandon profitable investments made in the past for the sole reason of adopting something new. Costs must justify the benefits. The ERP landscape will also be a hub for performance testing activity. ERPs are still essential to the enterprise, particularly large-scale manufacturing, finance, and retail outfits. As ERPs become more componentized, performance testing practices will become broader to accommodate the architectural shift.

The 2019 performance testing trends are going to continue to transform the way IT departments conduct business. Forward-thinking companies will do well to embrace these trends to save money, increase efficiency, but most importantly to meet the growing demands of customers for the innovative software they need to run their business and make a profit.

Learn More about Performance Testing

Discover more load testing and performance testing content on the Neotys Resources pages, or download the latest version of NeoLoad and start testing today.

 

Bob Reselman 
Bob Reselman is a nationally-known software developer, system architect, test engineer, technical writer/journalist, and industry analyst. He has held positions as Principal Consultant with the transnational consulting firm, Capgemini and Platform Architect (Consumer) for the computer manufacturer, Gateway. Also, he was CTO for the international trade finance exchange, ITFex.
Bob’s authored four computer programming books and has penned dozens of test engineering/software development industry articles. He lives in Los Angeles and can be found on LinkedIn here, or Twitter at @reselbob. Bob is always interested in talking about testing and software performance and happily responds to emails (tbob@xndev.com).

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