We collect the latest Development, Anaytics, API & Testing news from around the globe and deliver it direct to your inbox. One email per week, no spam.
Learn how to quickly build an ephemeral CI test environment using GitHub Actions and proxymock. This video shows you how to insert meaningful tests without depending on flaky mocks or virtualized services.
Regulated industries – from healthcare to finance – face a dual challenge: delivering high-quality software at speed while maintaining strict compliance with industry regulations. The stakes are high, with non-compliance leading to massive fines, reputational damage, loss of customer trust and operational disruptions. The good news? Compliance doesn’t have to be a bottleneck. With the right tools, it can become a seamless part of your development process.
In coding land, it’s really important to ensure that your app behaves as it should, isn’t it? One of the ways people do this is by doing something called assertion testing. Assertion testing is about creating checkpoints in the form of assertions. They’re small tests that verify everything’s going as expected while the program’s executing its task.
API is the backbone of many software architecture. However, it is also one of the major points of technical conflict. When a major code update happens, it is really important to check on these APIs to ensure that those code modifications did not inadvertently break existing functionality. This is why API regression testing should be considered in your regression test planning.
The latest version of Kong Mesh brings an improved provisioning experience and streamlined management of policies — plus user interface enhancements to elevate your experience deploying and managing Kong Mesh. Built on top of Kuma, Kong Mesh is a service mesh designed to provide security, observability, and traffic control across modern, distributed applications.
Get a sneak peek at how SmartBear API Hub is evolving API design with AI-augmented workflows. In this demo, we explore our new AI-powered API design capability, which lets you describe APIs in plain English and instantly generate OpenAPI-compliant designs — complete with resource definitions, error schemas, and support for your organizational standards.
Massive data sets can overwhelm native Pandas, causing memory issues and slow performance. Pandas on Snowflake eliminates these constraints by running Python code directly in Snowflake, with no rewrites needed. This demo shows how to transform and visualize large data sets using the familiar Pandas API with Snowflake’s distributed compute. Boost your data workflows and maintain security and governance, all while staying within the Pandas ecosystem.
Keeping your API documentation accurate and up-to-date can be effortless with automation. Automatic API documentation updates use tools like Swagger and Postman to sync documentation with API changes in real time, saving time and reducing errors.
Modernization is an ongoing journey—not just about migrating from legacy systems, but about continuously evolving, adapting, and pushing the boundaries of what’s possible. In today’s fast-moving landscape, AI is transforming how we build, integrate, and manage software, making modernization a necessity rather than a choice.