“AIOps” stands for “artificial intelligence in IT operations,” or using machine learning and data science to solve IT problems. AI can help with many IT functions, including detecting and remediating outages, monitoring availability and performance, and IT service management. Like with DevOps, a tester plays an important part with AIOps—they just have to determine what that is.
DevOps does speed up your processes and make them more efficient, but companies must focus on quality as well as speed. QA should not live outside the DevOps environment; it should be a fundamental part. If your DevOps ambitions have started with only the development and operations teams, it’s not too late to loop in testing. You must integrate QA into the lifecycle in order to truly achieve DevOps benefits.
Testers gather lots of metrics about defect count, test case execution classification, and test velocity—but this information doesn't necessarily answer questions around product quality or how much money test efforts have saved. Testers can better deliver business value by combining test automation with regression analysis, and using visual analytics tools to process the data and see what patterns emerge.
Continuous testing means all your tests are executing all the time, providing continuous feedback into the quality and health of your applications. In order to achieve continuous testing, you must first adopt the right test automation strategy. Understanding how to bring in all different types of test automation practices as efficiently as possible enables you to get started down the path of continuous testing.
The internet of things (IoT) continues to proliferate as connected smart devices become critical for individuals and businesses. Even with test automation, performing comprehensive testing can be quite a challenge.
Because enterprise applications are highly interconnected, development in stages puts a strain on the implementation and execution of automated testing. Service virtualization can be introduced to validate work in progress while reducing the dependencies on components and third-party technologies still under development.
Melissa Benua, director of engineering at mParticle, chats with TechWell community manager Owen Gotimer about the importance of whole team quality, how to get started using the test pyramid, and how developers can start writing testable code.
Jeremias Rößler, founder of ReTest, discusses his company’s open source re-check tool, how customer input was vital to the tool’s development, and shares insight on growing a start-up. Jeremias also provides resources for learning about AI that can guide you on how to apply AI into your testing strategy.
Melissa Benua, engineering manager at mParticle, discusses the role that containers play in test environments. She answers questions like: Why do you need containers? How is your team going to benefit from containers? What is the first step in getting started with containers? Melissa provides resources for learning how to make a container and on how containers will aid you in maintaining control over data and code.
Jason Arbon, CEO and founder of test.ai, discusses his goal to test all the world’s apps. Jason also provides insight on a frequent question he faces: When will AI replace my job? He believes that AI and machine learning have already started taking over some aspects of software testing, and that this transition will keep accelerating. Based on available data, Jason predicts which aspects of testing are going to be subsumed by AI, in what order, and in what time frame.
Most modern testing, especially in a DevOps model, uses a lot of telemetry to evaluate and monitor quality of experience for apps and services. In this interconnected world, there is power and risk in data. Ken Johnston will share his personal experiences dealing with US and European Union privacy regulations and the methods he and his team have implemented to mitigate the potential of significant penalties for the misuse of data. He will cover privacy-preserving techniques such as differential privacy and private enclave, what constitutes primary versus secondary uses of data, and how you should handle personally identifiable information (PII). You'll leave with a better understanding of how to keep data private and secured, as well as how to keep your team adhering to privacy best practices and regulations.
Serverless cloud applications are rapidly moving into the mainstream. In this model, teams focus on developing and deploying code on a known technology stack and runtime, with fixed interfaces for application, database, and network.