The constant market fluctuation of today’s business environment spells constantly shifting business requirements and focus. In order to stay on top of those changes, software engineering and operations management introduced Agile methodologies to provide rapid feedback cycles and the chance to innovate while keeping up with changing requirements. While business requirements are relatively easy to take into consideration, system requirements and architectural complexity is not.
Agile + DevOps Virtual 2021 - Industry Technical Presentations
Get solutions to your top software development challenges by attending the Industry Technical Presentations (ITPs). Offered alongside the concurrent sessions in 1-hour time slots, these presentations give you the opportunity to learn first-hand how solution providers have implemented their products and services in the real world. These solution providers are often on the leading edge of new technologies, tools, and practices and offer conference attendees a window into their future.
Wednesday, June 9
AI isn’t the future of testing; it’s the present-day reality, with ever-increasing significance as organizations are propelling into the next normal. Intelligent technologies such as artificial intelligence (AI), machine learning (ML) and analytics are becoming important building blocks of intelligent platform solutions for software companies and IT organizations in 2021. The aim of such intelligent platforms is to provide people with sustainable support so that processes can be optimized and maintenance costs can be minimized.
How Process Understanding & Continuous Testing for Agile+DevOps Speed Delivery and Ensure Quality. Learn how engaging automation can empower your organization to move at the speed of change in CI/CD environments. Explore how closed-loop automation for process intelligence, testing, and RPA aligns with the CI/CD pipeline and creates a continuous feedback loop and reusable assets.
In this webcast, GitLab Developer Evangelist, Michael Friedrich goes over how to secure your CI pipeline using GitLab built-in security features. Catch potential errors and vulnerabilities in the codebase before they turn into bigger problems!
- How to secure your CI pipeline using GitLab
- Learn about FOSS & GitLab: http://bit.ly/2KegFjx
- Get in touch with Sales: http://bit.ly/2IygR7z
AI-driven test execution is helping organizations scale their software validation and verification efforts and keep pace with the speed of DevOps. However, this new level of test automation is not without additional infrastructure costs. AI testing bots tend to consume a significant amount of resources when using deep machine learning models to generate and execute test cases. And so a new problem has arisen: how do we scale AI-driven testing efficiently and reliably to support the needs of large enterprises?
Thursday, June 10
To embrace digital transformation and succeed in today’s world of online everything, businesses must have complete confidence that their digital applications will work flawlessly every single time they’re used - and that confidence must be shared by customers. Continuous testing can ensure digital confidence, but with testing volume increasing at every stage of the development lifecycle, you can’t let test infrastructure limits create bottlenecks and dips in productivity.
Many organizations have already embarked on their Agile Transformation journey, yet despite having agile methodologies in place they have still not matured their competencies to the desired level. Still, there are some unicorns who have managed to master the process and are now delivering value faster and more efficiently. Frameworks like DevOps and Scrum help organizations stay ahead of the curve by facilitating cultural transformation, adoption of a lean mindset, and increased automation.
Scaling Agile and DevOps practices is especially hard in large enterprises. In this session, we’ll walk through a use case that demonstrates how portfolio managers and enterprise architects can transform teams and entire organizations through agile and DevOps practices.
- DevOps as a Product Strategy closes the scaling gaps
- How we proved this strategy scales DevOps in large organisations
- DevOps scaling is an ongoing commitment"
In software development, the people are represented by two traditionally separate yet equally important teams: The development team, who creates software, and the operations team, who manages the production software. These are their stories.
Intelligent Orchestration enables teams to integrate application security analysis into their DevOps pipelines while maintaining team’s velocity, that automatically performs the right security tests at the right time with the right tools, with the right breadth and depth of analysis based on SDLC events, pre-defined policies, providing continuous metrics and feedback.