DevOps Next Virtual Conference
Join us Wednesday, September 30 for DevOps Next, a free, half-day event packed with sessions on AI & ML in continuous testing, code quality, and DevOps productivity.
Registration Now Open!
DevOps Next is a half-day virtual event by and for DevOps industry experts — examining the challenges of DevOps today, and how evolving smart technologies can improve tomorrow’s testing, coding, and DevOps productivity.
Attendees can select from sessions across 3 tracks, connect with presenters via live chat, and participate in important discussions with peers.
The event is free but requires advanced registration. Register today!
Already registered? Enter the event here.
Tracks & Sessions
An introduction to AI/ML in software testing tools.
- The New Categories of Software Defects in the Era of AI and ML
- Classification of Advanced AI and ML Testing Tools
- Advancing the State of The Art in AI and Testing
The New Categories of Software Defects in the Era of AI and ML
When AI and ML are tested alongside traditional features of an app, the defects are of a different nature. AI/ML creates a new set of defect classification that will invade the DevOps space, and this session addresses these new and modern types of defects, including data-related, stochastic, and interpretability defects.
Classification of Advanced AI and ML Testing Tools
AI and ML solutions, whether commercial or open source, typically address unique use case or challenges. Learn about the categorization of testing tools with advanced AI/ML and get examples and existing tools for each of the use cases.
Advancing the State of The Art in AI and Testing
In this session, we’ll explore some of the latest advancements in AI for software testing. Our goal is to bring you to the bleeding edge of where AI and ML technologies are being applied to difficult software testing problems in the real world today. AI is no longer just doing functional testing, it’s testing user interface designs, video stream quality, gameplay, and more.
Practices and use cases in continuous testing leveraging AI and ML.
- Leveraging AI and ML in Test Management Systems
- The Rise and Benefits of Robotic Process Automation(RPA)
- Cognitive Engineering – Shifting Right with Gated.AI Testing
Leveraging AI and ML in Test Management Systems
AI and ML can be utilized to improve test management and quality, and the impact of changes from design into production. Learn about the various stages of software development life cycle from planning and design, through coding and testing, and shows how AI and ML can benefit these stages from within a test management system.
The Rise and Benefits of Robotic Process Automation(RPA)
Many companies are implementing RPA to automate high-frequency transactional processes that are better handled by bots. There is great opportunity in leveraging RPA to embed bots into handling regulatory requests, and much to be considered from a measurement perspective before adopting RPA on an enterprise scale, which will be covered in this session.
Cognitive Engineering – Shifting Right with Gated.AI Testing
The approaches and techniques that worked yesterday may not be optimum for the next generation of enterprise AI platforms. This session will cover how to prove Artificial Intelligence (AI) platforms by leveraging Cognitive, Reliability, and Chaos Engineering heuristics.
DevOps & Code
Maturing code quality and DevOps teams productivity using AI and ML.
- Automated Code Reviews with AI and ML
- Moving to Modern DevOps with Fuzzing and ML
- How Does AIOps Benefit DevOps Pipeline and Software Quality?
Automated Code Reviews with AI and ML
One of the biggest problems with code reviews is that they often derail developer productivity. Learn about the essentials of code reviews, where they are today, and where they can be using AI/ML technologies. With machine learning technology, code quality can be improved, and developers can focus on invention, rather than remediation.
Moving to Modern DevOps with Fuzzing and ML
Software fuzzing has long been a trusted method for finding vulnerabilities that are difficult to discover using traditional methods. The application of AI and ML to this field has already begun to bear very promising results. Learn the various methods of fuzzing through examples, documentation, and other related data that can guide practitioners on where to start and which tools are ready to be applied today.
How Does AIOps Benefit DevOps Pipeline and Software Quality?
The market has made great advancements in addressing inefficiencies in automated production and operation environment management. When armed with advanced abilities that make an AIOps portfolio valuable, IT managers can impact the entire software delivery cycle. Attend this session for a current and futuristic overview of AIOPs, its benefits, and where it’s heading in the future.