ChatGPT has taken the world by storm. A simple interface is now being used by everyone and for everything. If you are in IT, I am sure not just your colleagues, but folks from your family that do not belong to the IT world are also talking about it. ChatGPT registered 13 million users per day in January. In comparison, it took Instagram and TikTok 2.5 years and 9 months, respectively, to reach 100 million users on their respective platforms.
The Internet of Things (IoT) is expanding at an unprecedented pace. As IoT solutions become more complex, the need for comprehensive and efficient IoT testing increases.
In today’s dynamic business environment, enterprises realize the importance of a quality-first approach to test automation. Prioritizing quality at speed over a faster release pipeline is essential for ensuring the success of an organization. However, implementing a successful quality-first approach requires an end-to-end collaboration, where quality becomes the responsibility of all the different personas involved in the software development life cycle (SDLC).
Almost every organization needs a top-notch monitoring system to make sure everything is in place and operating at its best, given the developments in the cloud and changing software development life cycle (SDLC) processes. Observability is one of the significant areas that can guarantee your system’s health and ensures that the performance is visible and monitored properly.
Data has always been an important part of any business. A company’s data is its most valuable asset as it contains information about the procurement of resources to the customer relationship. With the rise of Big Data, more companies are trying to collect and store all information about their customers, products, employees, and other aspects of their operations to better understand them.
The performance and resilience of an application are used to measure the speed and scale of an organization. This is one of the key reasons businesses opt to modernize legacy applications using cloud-native technologies and platforms. According to a Gartner report, more than 95% of new digital efforts would be built on cloud-native platforms by 2025, up from less than 40% in 2021.
Imagine releasing a product or application with poor quality. The application is unfeasible to use and navigate from one menu to another. By the time we realize that the features are not generating value for intended customers, it may be too late to make any modifications, and it will be exorbitant to fix them. In such situations, Dogfooding testing helps prioritize features.
Data governance and management is a term that has become more commonplace in recent years. However, many organizations are still struggling with how to implement effective data governance and management strategies. This lack of focus is becoming more and more apparent as the importance of data management continues to grow. Here are the four key pillars that will help you successfully implement your data governance strategy.
