Systems | Development | Analytics | API | Testing

Insurance companies have long relied on data to assess risk, underwrite policies, and handle claims. However, as the volume of data grows, so does the need for sophisticated tools to turn that information into actionable insights. Simply having access to data is no longer enough. To succeed, insurers must be able to harness the power of their data—transforming it into a strategic asset that drives both operational efficiency and improved customer outcomes.

In the current software market, products are being introduced in the market at a very fast rate, with new versions being brought out almost every month, if not weekly. This is a good thing as it keeps the products evolving, but at the same time, it is not without its problems, and the most evident of these is the existence of problems and bugs.

Data lakes offer a unified data platform that can support analytics of all kinds.

Setting up a development environment can be challenging, especially for new developers or those adapting to new developer tools. A well-configured environment is crucial for efficient coding, testing, and debugging, enhancing productivity and minimizing errors. This guide will walk you through everything you need to know, from the basics to advanced customizations for different operating systems.

The main fundamental question of every business today: Are you on the right side of AI? Many businesses and investors are facing the big question: will they get AI-fied and die slowly or will they be propelled by AI and grow faster? Kong API tools and the Konnect API platform will bring our customers on to the right side of AI. Every platform shift from mainframes onward has created demand for more APIs.

Understanding and monitoring the performance and health of applications and systems is critical. This is where observability comes into play. Observability is about gaining a comprehensive understanding of a system's internal state by analyzing the data it generates within the context of real-time events and actions across the infrastructure.

When it comes to making HTTP requests in Node.js, developers are spoiled for choice: from the built-in and browser-familiar Fetch API to third-party libraries like Axios, Got, Superagent, Ky, and others. Navigating this diverse landscape can be a little daunting. This comprehensive guide aims to simplify your decision-making process by comparing the features and nuances of popular options, so you can select the ideal solution for your next project.

Rails partials have been around for years, but they can be clunky since they're just ERB snippets without a backing object structure. Recently, libraries like ViewComponent and Phlex have tried to improve the view layer by adding more semantic structure to the templates. These are great libraries and I personally reach for ViewComponent on almost every project I work on. That said, I still feel the humble Rails partial still works great for many use cases.

‍ ‍John McCarthy, an American computer scientist, stated this belief more than 40 years ago. Surely, his commitment to understanding the human mental process led him to ideate one of the most revolutionary ideas in computer science—artificial Intelligence (AI). Since then, AI has helped us develop software, utilize it to streamline our business offerings and maintain another essential aspect of digital ecosystems—quality assurance.

Software testability measures how simple it is to test both the system as a whole and each individual component. In modern discussions about testing, the focus often shifts solely to the tests themselves, overlooking the socio-technical environment in which the application or project operates. Ensuring your application is testable means making it straightforward and reliable to test, so that when issues arise, we can be confident they are real issues and not artifacts of poor testability.