Systems | Development | Analytics | API | Testing

In the process of developing software, designing and performing testing is a critical aspect of ensuring high software reliability, improving software quality, and deploying strong fit and function. The shift-right testing approach moves testing to later in your production cycle as a way of doing this with more accurate user data and post-production testing practices. Also known as “testing in production,” with shift-right, you test software after it has been deployed.

Today — alongside the announcement of Kong Insomnia 10.2 — we're excited to introduce two new Kong Insomnia enterprise capabilities that will improve user management at scale across every organization. These new features are available to use for every existing enterprise customer, and they complement existing advanced user management capabilities like EE SSO and SCIM. Let’s take a look at each of the new capabilities.

Kong Insomnia 10.2 is now generally available with some exciting new features and improvements! As usual, we strongly recommend upgrading to this latest version and to always use the most recent release of Insomnia.

You’ve probably heard of generative AI, which uses deep learning models to simulate human decision-making by processing large amounts of data, and then responding with pertinent new content. Since the arrival of ChatGPT in 2022, generative AI has come a long way — but now there’s another technology on the scene that could further revolutionize the capabilities of AI. Read on to learn more about agentic AI and how it could transform the business landscape.

In the world of software development, terms like "staging" and "production" get thrown around a lot. But what do they mean? Why do we need them?

More than 80% of developers and business leaders say AI investments have already created the opportunity for new products or services, according to Kong’s 2024 API Impact Report. Clearly, AI has proven its value and place in the enterprise, but with new innovations come new potential vulnerabilities. But as organizations push forward into and navigate the rising risk of AI-enhanced threats and the adoption of AI tools and large language models (LLMs), what have tech leaders experienced?

Imagine a user waiting several seconds for an app to load due to slow API responses. Frustration builds, user retention plummets, and scaling becomes a nightmare. API performance is a critical determinant of user experience and system reliability. Fast APIs ensure seamless interactions and support scalability. Among the strategies to enhance API speed, caching stands out as a powerful, cost-efficient approach.