Systems | Development | Analytics | API | Testing

Continuous Integration (CI) is the process of automatically building and testing your code on every source control commit. Continuous Delivery (CD) takes this further and automatically deploys the code to production on every commit. Used together these techniques allow code to be built, tested, and deployed automatically through a robust CI/CD pipeline. CHAPTERS.

Dive into the testing world with our latest video as we debunk the myth of a strict timeline for transitioning from manual to automation testing. Learn why individual strengths, coupled with years of product testing experience, are pivotal in deciding the testing approach.

In this enlightening session, Shraddha Misri demystifies the Agile process by delving into the dynamic worlds of Scrum and Kanban. As businesses strive for agility in today's fast-paced environment, understanding these frameworks becomes paramount. Shraddha provides valuable insights into the principles and practices of both Scrum and Kanban, offering a comprehensive guide for teams seeking to enhance their agility.

This week we have added new generative AI real-time connectors for Amazon Bedrock to Qlik Analytics, as well as new Amazon Bedrock connector blocks for App Automation.

Amazon Bedrock is the name of the Amazon service that offers a single API to access foundation models provided by companies such as AI21, Amazon Titan, Anthropic and Cohere, from which you can build generative AI into your Qlik applications without writing any code. With generative AI, organizations can broaden insight and context while adding a variety of new and exciting capabilities directly in analytics apps, load scripts, and through app automations. The analytics connector constructs questions and our unique associative engine passes only relevant data related to those selections, in real-time, allowing users to get contextually relevant responses while minimizing cost and complexity. Automation connectors offer the ability for developers to send questions and receive responses and data sets as part of automation workflows.

In this insightful presentation, Ajay Balamurugadas explores the notion that today's testers often find themselves entangled in a continuous loop of myths, rules, and expectations, restricting their freedom. Ajay, a skilled tester and storyteller, narrates the journey of a tester's freedom struggles and how reinventing one's approach can lead to overcoming challenges.

In this candid talk, testing expert James Bach takes on the prevailing notion that ChatGPT and similar tools have disrupted the landscape of 'manual testing.' Contrary to the hype, James argues that these tools are not only practically but also conceptually incapable of effective testing. Join him as he dissects the reasons behind the misconceptions surrounding ChatGPT's testing capabilities.

In this insightful presentation, Federico Toledo challenges the traditional distinction between functional and non-functional testing, urging testers to prioritize essential aspects that contribute significantly to the overall quality of an application. Federico highlights the misconception that non-functional aspects are separate from functionality, emphasizing that issues related to security, performance, or accessibility can profoundly impact an application's functionality.

In this compelling talk, Vikas Mittal addresses a common challenge faced by testing leadership—articulating the business value of testing when seeking additional funding. Testers often encounter questions about how testing contributes to business outcomes and key performance indicators (KPIs), a query that might seem more straightforward for developers. While developers can directly link their work to revenue, cost reduction, or operational efficiency, the value of testing is sometimes perceived through the lens of quality, leading to questions about the necessity of a testing team.

In today's rapidly evolving digital landscape, Large Language Models (LLMs) and Generative AI are emerging as transformative tools for enterprises. These innovations are not only changing how we interact with data but are also reshaping the very fabric of business operations. Unlike other public LLMs, what happens in your organization stays in your organization. But with great power comes great responsibility—and the need for in-depth understanding.