Kong Ingress Controller (KIC) 3.2 is here, and it’s an incredible release. It contains features related to graph theory, features that mean you’ll never need a database again, and a whole host of quality-of-life fixes.

In today's fast-paced software development environment, the integration of AI into DevOps revolutionizes the way teams approach testing. AI, particularly GenAI , proves to be a game-changer, offering unprecedented efficiency and accuracy in software testing processes. By automating repetitive tasks and providing actionable insights, AI is not only enhancing the quality of software but also accelerating deployment cycles.

API generation automatically creates an API based on pre-defined code and specific requirements, such as data access methods. APIs are the essential unit of a hybrid integration platform (HIP), an architectural approach to connecting everything or anything through a digital pulse. In this hustle to connect everything digitally, organizations need a process to acquire safe and secure APIs. API generation can make this happen, allowing companies to generate and deploy APIs without writing code.

Last week, mobile app developers gathered in Cupertino, California, and tuned in across the globe to hear the latest news and future roadmap for Apple at their annual developer conference, WWDC 2024. And Apple did not disappoint.

Integrating artificial intelligence (AI) into business operations is no longer optional—it’s necessary. Yet, too often, businesses fail to reap the full rewards. AI can’t produce the results that impress stakeholders and drive tangible results unless you take a strategic approach to its deployment.

In the age of AI, enterprises are increasingly looking to extract value from their data at scale but often find it difficult to establish a scalable data engineering foundation that can process the large amounts of data required to build or improve models. Designed for processing large data sets, Spark has been a popular solution, yet it is one that can be challenging to manage, especially for users who are new to big data processing or distributed systems.

The telecom industry is undergoing an unprecedented transformation. Fueled by tech advancements such as 5G, cloud computing, Internet of Things (IoT) and machine learning (ML), telecoms have the opportunity to reshape and streamline operations and make significant improvements in service delivery, customer experience and network optimization.

Digitization efforts across manufacturing have created new opportunities with digital twins, predictive maintenance and cloud systems.

The healthcare sector is one where change occurs rapidly. Medical devices are now becoming more complex, networked, and downright indispensable to patients’ lives; such devices include pacemakers, insulin pumps, sophisticated diagnostic tools, and telemedicine platforms, contributing immensely towards modernizing medicine.