It’s an interesting time for the application space. The pressures being put on enterprise development teams have accelerated to a point unseen in the past. The technologies and architectures patterns that are designed to help teams become more agile today are putting a level of complexity into the equation. New software service areas, not the least of which is IoT, are multiplying and need reliable testing. Customers have become more demanding, expecting new capabilities to be delivered, in some cases, on a weekly basis. All of these phenomenon can lead to chaos and confusion in the test lab.

Kelly Emo, director of product, solutions and technical marketing for application testing at HPE Software, sees three specific challenges that enterprise development teams face. She calls these pressures “seismic shifts.”

“First, is the complexity within software. On the architecture side, I’m seeing development teams move beyond APIs and services-oriented architecture (SOAs) into cloud-native, containerization, microservices, all designed to increase development agility, but the pressure it puts on the teams that are managing and testing the software is large,” she says.

The second shift is that the digital value software delivers in new service areas must be tested. “Think about where digital value is landing. It’s not just on your laptop, your computer, phone, or your watch. It’s moving to ‘things.’ Test labs need to be built to test these environments in an ongoing way and ensure functional performance and security,” Emo points out.

Rapid delivery is the third seismic shift Emo sees. She cautions, “When delivering new capabilities at a cadence of weekly, or even daily, methodologies like Agile and Lean help, but the whole ‘Develop, Test, Deliver’ pipeline has to evolve, and the testing methods must support that transformation. You can’t just spray and pray, then roll it back if there’s an issue.”

Transforming to meet customer needs
HPE has gone through an evolution in the last six months. It has had its own transition to DevOps, Lean, and Agile practices. The first major change is that the company is delivering new capabilities to SaaS customers every six weeks and on-premises customers every three months as opposed to one major upgrade every six months. HP’s mobile testing suite now provides support for MQTT, one of the peer-to-peer sensor messaging protocols for IoT. To encourage testers to use what they have, HPE is also embracing the open-source movement and has opened up its products so the actual automations can be built with Appium or Selenium.

Flagship tools for Continuous Testing
ALM Octane, HPE UFT Pro (previously LeanUFT), StormRunner Load, and Service Virtualization all work in a continuous integration pattern for integrated continuous testing in Agile and DevOps environments, with a CI engine like Jenkins and/or TeamCity.

Think of ALM Octane as your management layer that gives you the visibility into what is going on in terms of the application being managed and tested in your pipeline. It’s a cloud-based application life-cycle management offering that uses common toolsets and frameworks, such as Jenkins, GIT, and Gherkin. It’s geared towards making customers’ DevOps processes more efficient.

HPE UFT Pro is a functional test automation engine. It works with both HP scripts and Selenium. It’s built specifically for continuous testing and continuous integration. It supports the most common AUT technologies, and integrates with standard IDEs on multiple platforms to increase DevOps and Agile teams productivity.

HPE StormRunner Load is a SaaS-delivered cloud load and performance testing engine. It can be triggered as part of the CI process. It uses both on-premises and cloud virtual users so when it’s needed, it’s capable of mega-scaling up to a couple million users for a Black Friday type test, saving you the cost of those user licenses.

HPE Service Virtualization is the key, behind-the-scenes element that keeps the continuous integration pipeline running, since many of today’s applications are now compositions. It calls an API that may be out in the cloud or from a legacy system that you may not be able to access as a tester. Service Virtualization virtualizes that behavior and keeps your testing moving forward.

On the horizon
Building analytics into testing products is an emerging necessity. With all the data that test tools can provide, teams need to understand which data is important to their organization. Having a test tool that gives a comprehensive picture of how an application is used on a production network delivers significant value and informs what test cases need to be run. HPE is building predictive and analytic layers into its products, applying big data algorithms, machine learning and AI to help teams focus on where their issues are. Emo reveals, “We’ve been working with these technologies for a couple of years. There’s a lot of power in them but incorporating them so we get good data in and good data out isn’t an easy thing to accomplish. We want to design tools that will give people the ability to say, ‘Yes, this is my area of risk, and where I want to focus additional test resources.’ It’s very powerful.”

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