Systems | Development | Analytics | API | Testing

You can make your API observability posture more powerful and beneficial by treating Moesif as an engineering implement. The platform automatically captures API traffic out-of-the-box and provides actionable analytics and visualizations. However, the degrees to which they precisely and empirically illustrate the data, depend on where and how you’ve integrated Moesif.

API and AI services now sit at the heart of modern products. However, the more we use them, the harder it seems to become to account for the budget. Launching an AI product often leads to massive end-of-period bills. This requires attributing costs to the key internal power users and consumption drivers. The challenge is identifying the departments, products, or projects responsible for the consumption, and the extent to which they contribute.

DreamFactory and Postman serve fundamentally different roles in the API development lifecycle. DreamFactory is an API generation and backend platform that automatically creates production-ready REST APIs from databases and other data sources, while Postman is an API development environment focused on testing, documentation, and collaboration. Though both platforms involve API management, DreamFactory generates and deploys APIs while Postman helps developers test and consume them.

Non-crashing bugs don’t make your app crash, but they can ruin the user experience and hurt your app’s ratings. Fixing these issues is critical to keeping users happy. Here’s a quick rundown of the most common non-crashing bugs and how to address them.

This blog expands on insights Amjadh Ifthikar shared during his WSO2Con Asia 2025 presentation. Watch the full session here.

Concurrency means running multiple tasks at the same time, and it’s a great way to ensure our apps stay responsive. Swift 5.5 introduced structured concurrency and the closely related concept of async/await to improve the management of asynchronous code, part of a wave of changes designed to ensure simpler code, improved error handling and automatic task lifecycle management.

The EU AI Act is here, and for many enterprises, it represents a massive coordination challenge. As the world’s first comprehensive AI law, it mandates strict governance on transparency, risk management, and data quality. For platform engineers and architects, the immediate question is operational: How do we comply with these new regulations without forcing every developer to rewrite their applications?