Enterprise Resource Planning (ERP) systems are designed to streamline business operations by centralizing data across an organization. However, extracting and utilizing this data can be a complex and time-consuming process. One solution to this problem is the use of APIs (Application Programming Interfaces), which allow you to get data out of ERP systems and other software applications.

There are several ways to handle load spikes on a service. However, these methods are not cost-effective: you either pay for resources you don't use, or you risk not having enough resources to handle the load. Fortunately, there is a third way: horizontal autoscaling. Horizontal autoscaling is the process of dynamically adjusting the number of instances of a service based on the current load. This way, you only pay for the resources you use, and you can handle load spikes without any manual intervention.

Unlocking the power of AI within SAP for your team requires overcoming a significant hurdle: data accessibility. SAP data’s complexity, spread across various modules, creates silos of information that your team might struggle to understand and utilize effectively. Inaccessible or misaligned SAP data will hinder your AI system’s ability to learn and deliver valuable results specific to your organization.

Have you ever come across a website that made you scroll over it again just to see the motions and transitions and made you GASP, thinking how hard it must be to create these amazing animations, One such animation I saw on keploy website, the parallax effect which made me go through there Developer section twice!

We've just rolled out new trigger controls and enhanced YAML syntax so you can initiate your builds with unmatched precision.

"The whole is more than the sum of its parts." Aristotle is credited with this quote, and it's true in the world of data. Legacy systems typically approached their role in a limited manner. Each system was intended to be used by a certain user set and handle well-defined processes and associated data. The result was a disintegrated environment with data being difficult to obtain, and frequently out of date. The parts couldn't easily cooperate to make a whole.

At some point, anyone who has enjoyed using a computer has wondered if they could build their own app. But software development becomes intimidating fast if you’re not a programmer. Fortunately, there is a wide range of no-code platforms available today. Even in the enterprise, there’s demand for no-code development. As APIs have become one of the most important components of the modern application ecosystem, several no-code API solutions are now available.

Despite the transformative potential of AI, a large number of finance teams are hesitating, waiting for this emerging technology to mature before investing. According to a recent Gartner report, a staggering 61% of finance organizations haven’t yet adopted AI. Finance has always been considered risk averse, so it is perhaps unsurprising to see that AI adoption in finance significantly lags other departments.

When you’re ready to make the transition from manual testing to test automation, it’s natural to consider hiring. A QA engineer — who has the technical skills to write and maintain automated tests in an open-source framework — can take the burden of end-to-end test management off of your development team, allowing them to ship more code, faster. But hiring a good QA engineer is — often prohibitively — expensive.