Systems | Development | Analytics | API | Testing

One of the principals of Moesif’s efforts has been making API analytics more accessible and easier to use for everyone. We have helped enterprises of different sizes and use cases grow and succeed with their API and AI products through data-backed insights.

Learn how to easily create a REST API for Oracle, whether on-premise or in the Cloud, with DreamFactory. This enables instant, secure REST API auto-generation, and seamless integration with applications, BI dashboards, and AI pipelines—all without the need for custom coding.

To monetize digital content, we have used means like ad networks, affiliate links, and paywalls. However, with the fast and widespread adoption of AI, demand for high-quality data has increased. To make sure Large Language Models (LLMs) models deliver value and accurate results, a wide spectrum of content is often scraped and trained on without permission or compensation. This includes blogs, product and technical docs, forums, and research papers.

The rise of AI agents has reshaped software economics; businesses have been increasingly adopting them for efficiency, scale, and delivering values faster. However, pricing them has remained a hard problem. By the established norms, you would tie cost to headcount or access, but that doesn’t fit; traditional methods misalign with how agents deliver value. And newer approaches often create more confusion than clarity.

We're very excited to announce Kong Operator 2.0! Kong Operator is an evolution of Kong Ingress Controller (KIC) and Kong Gateway Operator into a single Kubernetes offering to simplify deployment, management, configuration, and upgrades of your Kong Gateway instances on Kubernetes.

AI coding tools like ChatGPT, GitHub Copilot, and Claude have completely changed how we write software. From humble beginnings where non-AI-enabled code assistants made intelligent code suggestions, like Intellisense, the latest agentic tools can generate entire functions, suggest optimal algorithms, and even scaffold complete applications in minutes. However, as any developer who’s worked with AI-generated code knows, the output isn’t always perfect.

Imagine that you need to know the exact location of the train that you’re about to catch. Trains can be equipped with IoT sensors that can publish location coordinates via Kafka streams in real time. You will be using a mobile application to view a train’s location. Mobile applications and web applications are compatible with WebSocket, a web-friendly protocol, but the location data is received via a Kafka stream. How do we convert the real-time Kafka feed into a real-time WebSocket feed?

When your application crashes during peak traffic or returns cryptic error messages to frustrated users, the culprit is often hiding in plain sight: untested APIs. According to recent industry data, APIs now account for 71% of all internet traffic, yet many businesses still treat API testing as an afterthought.