5 Key DevOps and Software Testing Predictions for 2019

 In Blog, AI and Machine Learning in Test Automation, Agile & DevOps Testing

testing predictions

2018 was an exciting year from an innovation perspective, from a DevOps maturing standpoint, and from the planting of roots around AI and ML in various use cases in the DevOps landscape.

With that in place, organizations are still struggling to increase the degree of their digital test automation for both desktop web apps, responsive and progressive, as well as mobile native apps. The maturity of agile and DevOps processes together with stable continuous testing are among the key challenges’ teams are facing.

In 2019, there will be few significant advancements in the software industry that will enhance the overall maturity in DevOps and Continuous Testing.

  • The role of the DevOps tester
  • DevOps adoption will see (even) more growth
  • ML and AI will permeate into both dev and test tasks
  • Digital transformation and UX will grow with AR/VR/5G and IoT technologies
  • Focus on non-functional testing activities within the DevOps Pipeline

The role of the DevOps tester will continue to grow

Currently, the industry is divided into 3 types of personas that are involved in the testing processes. The software developer who focuses on unit testing and build acceptance testing, the test automation engineer who is focused on test coding of functional and non-functional test development, and lastly, the business tester, who is focused on the user stories from a manual standpoint. In 2019, the main impact will be on the software developers and the business testers. These personas will aim to enhance their overall test productivity by shrinking to the minimum possible time it takes to author and execute their tests. To accomplish that, these teams will embrace smart testing tools that are powered by machine-learning and artificial intelligence capabilities. Among the features these personas will benefit from will be codeless test authoring, smart test data analysis, self-healing of test code while the app is dynamically changing, and more.

To succeed in the above, these individuals need to explore the existing tools and try to match their capabilities with the most urgent and tedious tasks that are on their tables. Starting small and growing the adoption of these tools will be a key to success. From recent research among many others, it seems like DevOps teams are already focusing on the above objective (see following image), so 2019 will be a great year to validate whether this will be the groundbreaking trend of the year in DevOps.

testing predictions

Fig 1: Use of Bots Interest as Part of Test Activities (Source: QATestlab)

DevOps adoption will see (even) more growth

DevOps is here for a while and is the focus of most software engineering management across industry verticals. In 2019, to drive more agility, and expedite delivery of value to customers, DevOps teams will embrace various tools and technologies that will boost their productivity even further. Among the changes we will see are:

  1. Higher focus and investment in the automation of the entire DevOps pipeline activities from coding through production.
  2. More cloud and SaaS-based services that include lab environments, service virtualization, big-data management, and more.
  3. Maximizing software architecture around micro-services development.
  4. Business analytics visibility at any stage of the software development lifecycle to ensure business-focused feature delivery.
  5. ML and AI solutions in various use cases will help deliver and measure software quality

testing predictions

ML and AI will permeate into both dev and test tasks

As mentioned above, and as a key supporter of the entire DevOps pipeline tasks, ML and AI tools will come to the rescue among various use cases that the above-mentioned 3 personas require.

  1. Reliable and stable test automation authoring to facilitate trust between dev and testers. Tools that enable codeless testing with self-healing object management will see higher adoption within DevOps teams.
  2. Optimization of test suites across the entire DevOps pipeline through identification of flaky, redundant, and duplicate cases.
  3. Slicing and dicing test data to help decision-makers validate their software quality on-demand. Understand functional areas quality fast, identify RCAs (root cause analysis) of defects fast, present quality dashboards including visibility into the CI (continuous integration), logs visibility and analytics, traceability between tests and requirements, and more.

testing predictions

Digital transformation and UX will grow with AR/VR/5G and IoT technologies

Continuous testing in the digital era has never been more complicated, and 2019 will take this a step further as we start learning more about advanced AR/VR capabilities in the mobile and web landscape, and the rollout of 5G networks that will aim to boost end-user experiences.

Technology gaps between mobile and web will shrink even more with the rise of progressive web apps (PWAs).

testing predictions

To keep pace with the innovations, DevOps teams will need to re-think schedule, existing software delivery processes, and existing architecture and find ways to accommodate these changes within the already tight delivery schedules they face today. Automation here will be the key, and enabling it through the right tools, test environments, labs, and others will serve as a key to success.

Focus on non-functional testing activities within the DevOps pipeline

While teams struggle to automate their DevOps pipeline and include as many tests as possible from the unit, acceptance, and functional testing, in 2019, the expectations will grow as more compliance with non-functional standards like accessibility and security become mandatory.

The above-mentioned new technologies do not come free, and to support the new 5G network, AI/ML, AR and VR, IOT and others, teams will need to spend more time on developing test cases to cover the innovative features. By end of 2019, all websites need to comply with the strict accessibility requirements and to make this less painful and impactful on the overall pipeline, these tests will need to be automated as much as possible. Security and cyber attacks are always in the news, but the risks are only going up as the digitalization matures, hence, teams will invest more time and resources into baking security testing, code scanning etc. during 2019. Overall reliability, UX, and performance testing of apps will also become an integral part of the DevOps pipeline and part of the CI testing.

testing predictions

Bottom Line

As we wrap 2018, it is obvious that the future of DevOps and continuous testing holds both exciting innovations and challenges. Being able as a team to enter 2019 as prepared as possible for both, will help drive faster value to customers, with greater quality and greater productivity.

Happy New Year,

Eran Kinsbruner

Author, Lead Software Evangelist.


Selenium Testing eBook

SaaS enterprise