We’re excited to unveil a sneak peek of the upcoming NeoLoad 2024.3 release, which will be generally available this November. One of the most anticipated features in this release is remote terminal emulation (RTE) support — a game-changer for teams responsible for the performance of mainframe and other legacy systems.

The report highlights platforms like Fivetran that are crucial for modernizing marketing data infrastructure in today’s fast-paced, budget-conscious market.

In this blog post, we'll talk about how to implement API product tiering, a powerful way to customize access, control usage, and monetize APIs. This model can help you scale efficiently while maintaining a smooth user experience. Read on to learn more! We'll be talking about how to implement API product tiering with Kong Konnect, an API lifecycle management platform designed from the ground up for the cloud-native era and delivered as a service.

Imagine being at the helm of a project, excited to launch an innovative software application, but then... the testing phase reveals critical flaws that could have been caught earlier. This experience is a stark reminder of how vital a cohesive test plan can be. Join me as we explore how a visual test plan builder can transform your approach to crafting robust test plans, ensuring quality at every step of the way!

Keep users informed and engaged with Ably's expanded push notification support. We're thrilled to announce that Ably Pub/Sub now supports web push notifications, in addition to our existing support for iOS and Android devices. With just a few lines of code, developers can easily integrate web push into their applications, providing a seamless and unified experience across all major platforms.

The problem with test data is that it can become stale very quickly. This is either through its use from testing or from the fact that it is naturally aging in the test environments. This is not just an issue for performance testing, although the volumes of data sometimes required for performance testing do make it harder. This also affects functional testing as well as batch testing and business acceptance testing amongst others.

Organizations generate vast amounts of data daily during various business operations. For example, whenever a customer checks out out at a retail outlet, data such as the customer identifier, retail outlet identifier, time of check out, list of purchased items, and the total sales value can be captured in the Point of Sales (PoS) system. Similarly, field sales staff may record possible sales opportunities in spreadsheets.

Many vendors have started calling their platforms “low-code” or “no-code.” Competitors often pit the terms against each other. But what do low-code and no-code really mean? And what's the difference between the two? Both platforms offer improvements over traditional high-code approaches. The biggest differences are the target user groups.

In recent years, machine learning operations (MLOps) have become the standard practice for developing, deploying, and managing machine learning models. MLOps standardizes processes and workflows for faster, scalable, and risk-free model deployment, centralizing model management, automating CI/CD for deployment, providing continuous monitoring, and ensuring governance and release best practices.