Systems | Development | Analytics | API | Testing

Container technologies are always evolving — and we're not talking Tupperware here. Over the past years, service mesh has emerged as a crucial component for managing complex, distributed systems. As organizations increasingly adopt Kubernetes for orchestrating their containerized applications, understanding how to effectively implement and utilize a service mesh within this environment becomes paramount.

Artificial intelligence (AI) is kind of a big deal. And when things are a big deal, they're ripe to be exploited. Fortunately, mounting concerns about AI security and privacy are met by plenty of guidance on best practices from the good folks in the open source world. The OWASP AI Security Project has emerged as a crucial initiative, offering developers clear, actionable guidance on designing, creating, testing, and procuring secure and privacy-preserving AI systems.

Kong has been named to the Forbes 2024 Cloud 100 for the fourth year in a row!

APIs are the backbone of the modern enterprise. However, troubleshooting API errors and resolving issues quickly can be challenging given their role in application operational continuity and customer experience. Time-sensitive resolution demands monitoring and deep analytical insights into API performance and usage. Combining both these capabilities in one tool accelerates real-time resolution and empowers stakeholders to surface business-critical API performance metrics through a self-service motion.

We're pleased to announce the general availability of Kong Insomnia 9.3.3. This release ships with numerous improvements, particularly around performance. We strongly recommend updating to this latest version to get the best user experience in your daily workflow with Insomnia.

From smart homes to wearable devices to connected cars, the Internet of Things (IoT) is bringing about a new era of hyper-connectivity. Experts expect investments in the IoT ecosystem to rise above $1 trillion in 2026 — with no signs of slowing down. Application programming interfaces (APIs) are the backbone of IoT, ensuring scalability and security across billions of connected devices.

Manufacturing has been one of the most prominent industries worldwide since the Industrial Revolution. Since then, from producing textiles to computer chips, manufacturers have always looked for ways to innovate. In the age of AI and APIs (or application programming interfaces), tech companies are looking for technological breakthroughs to gain an edge over the competition.

A service mesh is a mechanism for managing communications between the various individual services that make up modern applications in a microservice-based system. When a service mesh is applied, all inter-service communication is routed through proxies, which can be used to implement networking features such as encryption and load balancing.

API rate limiting involves using a mechanism to control the number of requests an API can handle in a certain time period. It's a key process for ensuring that APIs perform to a high level, provide a quality user experience, and protect the system from overload.

As a developer working with microservices architectures, you may find yourself facing numerous challenges. Managing multiple services, each with its own potential points of failure, can be complex. Issues such as communication difficulties, security concerns, and lack of visibility are common in these environments. These challenges are not unique. As microservices architectures expand, they often introduce complexities that can be demanding for development teams to handle.