devops cycle
December 21, 2018

5 Key DevOps and Software Testing Predictions for 2019

Automation

AI, ML, DevOps, New Tech and New Challenges

2018 was an exciting year for DevOps innovation and growth.  It is also likely to be remembered as the year that artificial intelligence and machine learning finally took root in the DevOps consciousness.

Organizations are still struggling to increase the degree of their test automation for desktop web apps, whether responsive or progressive, as well as native mobile apps. Mastering agile and DevOps processes and implementing stable continuous testing strategies are amongst the top challenges teams are facing.

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

  • The growing importance of the DevOps tester
  • Increased DevOps adoption
  • ML and AI will become commonplace for both developers and testers
  • Digital transformation and UX will grow alongside 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 the business tester, who is focused on user stories from a manual standpoint. In 2019, the biggest impact will be seen by software developers and business testers. These personas will aim to enhance their overall test productivity by minimizing time it takes to author and execute their tests. To accomplish this, these teams will embrace smart testing tools that are powered by machine learning and artificial intelligence capabilities. Among the new features benefiting these personas will be codeless test authoring, smart test data analysis, self-healing of test code during dynamic app changes, and more.

To succeed, these individuals will need to explore existing tools and match their capabilities to the most urgent and tedious tasks. Starting small and gradually increasing adoption of these new tools will be a key. According to recent research, it appears that DevOps teams are already implementing this type of approach (see following image).  2019 will reveal whether this trend will continue in DevOps.

DevOps adoption will see (even) more growth

DevOps has been around for a while; most software engineering management teams are using this approach to development. In 2019, to become more agile and expedite delivery of value to customers, DevOps teams will embrace new tools and technologies that will boost their productivity even further. Among the changes we will see are:

  • Greater focus on and investment in the automation of all DevOps pipeline activities, from coding through production.
  • More cloud and SaaS-based services, including lab environments, service virtualization, big data management, and more.
  • Maximizing software architecture with microservices development.
  • Business analytics visibility at all stages of the software development lifecycle to ensure business-focused feature delivery.
  • ML and AI solutions in various use cases will help ensure - and measure -  software quality

ML and AI will become commonplace for both developers and testers

As a key supporter of all DevOps pipeline tasks, ML and AI tools will come to the rescue in various use cases that the previously mentioned 3 personas require.

  • Reliable and stable test automation authoring to facilitate trust between devs and testers. Tools that enable codeless testing with self-healing object management will see greater adoption within DevOps teams.
  • Optimization of testsuites across the entire DevOps pipeline with identification of flaky, redundant, and duplicate cases.

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), log visibility and analytics, traceability between tests and requirements, and more.

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

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

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

To keep pace with innovation, DevOps teams will need to rethink scheduling, existing software delivery processes and architectures to find ways to integrate these changes into the already tight delivery schedules they face today. Automation will be the key, and enabling it with the right tools, test environments, labs, etc., will be key to success.

Focus on non-functional testing activities within the DevOps pipeline

Even as teams currently struggle to automate their DevOps pipelines and include as many unit, acceptance, and functional tests as possible, in 2019, expectations will continue to grow as compliance with non-functional standards, such as accessibility and security, becomes mandatory.

The aforementioned new technologies do not come free, and to support new 5G networks, AI/ML, AR and VR, IoT, and others, teams will need to spend more time developing test cases to cover these innovative new technologies. By end of 2019, all websites need to comply with strict accessibility requirements; to make this less painful and more impactful on the overall pipeline, these tests will need to be automated as much as possible. Security and cyberattacks are always in the news;  risks only increase in lock step with digitalization; hence, teams will need to invest more time and resources into baking in 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 CI testing.

The Bottom Line

As 2018 draws to a close, it is clear that the future of DevOps and Continuous Testing holds both exciting innovations and a few daunting challenges. Being able, as a team, to begin 2019 as prepared as possible for both will help deliver more value to customers faster, with greater quality and greater productivity.

Happy New Year,

Eran Kinsbruner