Artificial intelligence (AI) is rapidly transforming the business world, and Application testing is no exception. AI-powered testing tools can help businesses to automate tasks, improve accuracy, and reduce costs. One of the most important benefits of using AI for Application testing is that it can help automate repetitive tasks. This can free up testers to focus on more complex and strategic tasks. For example, AI can automate creating test cases, executing test cases, and analyzing test results.

Imagine having the keys to a vault where every piece of data about your business is stored—not just any vault, but one that you built, control, and customize according to your precise specifications! This is the empowering reality of self-hosted analytics. It's like being the captain of your ship, navigating through the vast ocean of digital information with the confidence that comes from knowing every inch of your vessel.

In my previous post, we discussed how to take advantage of VPA to implement automatic vertical scaling for our Konnect Data Planes. In this post, we'll focus on HPA for horizontal Kubernetes Pods autoscaling.

At Honeybadger, we use Ahoy for first-party analytics in Rails. Ahoy is excellent for developers because it lives in your Rails application alongside your other data and code. Want to answer a specific question about your product or website visitors? It's just one ActiveRecord query away: Ahoy also works with Chartkick and Groupdate to visualize your data.

Today, we are excited to share insights into the strategic vision, product highlights, and the roadmap that will shape the future of data integration, analytics, AI, and machine learning. Click here to check out the webinar on-demand.

In today's dynamic software development landscape, efficient and scalable test management is crucial for ensuring the quality and reliability of software products. Jira, a popular project management tool, offers a robust solution for test management through its integration with Zephyr Scale. In this blog post, we’ll explore the high-level importance of reusability features in test management and how they contribute to scaling your testing efforts.

Collective (adj): done by people acting as a group. Collective (noun) a cooperative enterprise. What do these definitions tell us about collective testing? In its most basic form, it is a practice where individuals come together to test products, software, or ideas. Beyond that, collective testing is a powerful tool that not only improves the quality of what’s being tested but also fosters a sense of community and shared purpose.

Effective quality management in the life sciences industry is essential for ensuring patient safety, regulatory compliance, and the delivery of high-quality, efficacious treatments and medical devices. And good quality management is about more than just checking a regulatory box. Ensuring the safety and efficacy of your products can prove challenging, but the right technology can help.

Kong Ingress Controller 3.1 provides brand-new capabilities for keeping your secrets secure. We’ve introduced new KongVault and KongLicense CRDs, and added a way to keep sensitive information in your cluster when using KIC in Konnect. Finally, there’s a quality-of-life improvement that allows you to use a Kubernetes secret to populate a single field in a KongPlugin configuration.

How much time does your company spend manually preparing file data? Imagine a world where managing COBRA eligibility data is as simple as a few clicks, where files in myriad formats seamlessly transform into a standardized, compliant structure without hours of manual labor. For companies and consultancies managing employee benefits, standardizing and processing data files is a critical, yet challenging task.