The main fundamental question of every business today: Are you on the right side of AI? Many businesses and investors are facing the big question: will they get AI-fied and die slowly or will they be propelled by AI and grow faster? Kong API tools and the Konnect API platform will bring our customers on to the right side of AI. Every platform shift from mainframes onward has created demand for more APIs.

We're excited to announce the release of Kong Gateway 3.8, a significant update that marks a major milestone in the evolution of our API management platform. This release is packed with enhancements designed to boost performance, fortify security, and provide greater flexibility and ease of use for our customers.

Choosing a QA automation partner is not just a question of technicality but it’s strategy. So CTOs and VPs must meet general criteria like compatibility of the partner’s service with current development pipelines, scalability of the partner’s automation solutions, and the partner’s experience in managing complex test cases. Furthermore, knowing their view toward the integration and delivery (CI/CD) pipeline can significantly boost.

Understanding and monitoring the performance and health of applications and systems is critical. This is where observability comes into play. Observability is about gaining a comprehensive understanding of a system's internal state by analyzing the data it generates within the context of real-time events and actions across the infrastructure.

Software testability measures how simple it is to test both the system as a whole and each individual component. In modern discussions about testing, the focus often shifts solely to the tests themselves, overlooking the socio-technical environment in which the application or project operates. Ensuring your application is testable means making it straightforward and reliable to test, so that when issues arise, we can be confident they are real issues and not artifacts of poor testability.

Local preview environments are transforming how developers test and validate code changes before merging them into the main codebase. Acting as temporary cloud environments, they provide a production-like setting where new features and bug fixes can be tested in isolation, catching issues early and streamlining the development code review process. These environments are crucial for enhancing development velocity, especially in CI/CD workflows used by DevOps engineers and QA teams.

Like most organizations today, you’re probably looking to optimize your business model through increased technology adoption. The more successful digital transformation projects look at changing business trends and seek to incorporate those trends within their own specific environment. Similarly, as API technology grows, promising new functionalities and integrations, enterprises should aim to embrace the utility of APIs within their wider technology strategy.

Organizations are harnessing the power of AI to revolutionize products and services across industries. But AI-powered solutions have been getting more sophisticated. We need to redesign and amend our approach to understanding how customers experience these solutions. Unlike traditional products, AI solutions are dynamic, continuously learning and adapting. Traditional metrics may fall short of capturing the nuances of how users interact with AI.

It sounds counterintuitive—using a technology that has trust issues to create more trustworthy data. But smart engineers can put generative AI to work to improve the quality of their data, allowing them to build more accurate and trustworthy AI-powered applications.