Systems | Development | Analytics | API | Testing

In the modern era of AI-based innovations and cloud transitions, businesses face the challenge of managing complex processes across multiple systems — and the rate of change is only accelerating. At the same time, businesses need to ensure that the introduction of new innovations driven by accelerated business transformation doesn’t break existing processes and systems.

In the space of APIs for consuming up-to-date data (say, events or state available within an hour of occurring) many API paradigms exist. There are file- or object-based paradigms, e.g., S3 access. There’s database access, e.g., direct Snowflake access. Last, we have decoupled client-server APIs, e.g., REST APIs, gRPC, webhooks, and streaming APIs.

White box testing is a testing method where testers evaluate the quality of a system with full knowledge of its internal structures. Here, the testers have access to the system's source code and understand how it operates internally. They know not only what the software does but also how it achieves those results. In this article, we’ll learn more about white box testing in-depth, the common techniques used, and white box testing best practices.

In a world where microservices have become very popular, the connectivity aspects between systems take center stage when it comes to prioritizing quality engineering. Postman's State of API report highlights that technical and non-technical stakeholders recognize the growing importance of APIs and their testing as part of the enterprise strategy.

Generative AI has received the lion’s share of the press. With good reason—it’s revolutionizing the way we do work and do business. But it’s not the only game in town. Predictive AI also places a role across enterprise use cases like demand forecasting, maintenance, and customer experience. This blog will discuss these two types of AI: generative AI and predictive AI.

We are thrilled to kickstart this first launch week with autoscaling - now generally available! Our goal is to offer a global and serverless experience for your deployments. Autoscaling makes this vision a reality. Say goodbye to overpaying for unused resources and late-night alerts for unhealthy instances or underprovisioned resources! During the autoscaling public preview, we received key feedback around scaling factors.

Django is designed to be secure by default, which means that its got a number of featured out of the box to protect against common Web vulnerabilities, including SQL injection, cross-site scripting (XSS), and cross-site request forgery (CSRF). Its extensive documentation, active community, and strong ecosystem of reusable apps and libraries make it a common choice for developers looking to create scalable and maintainable Web applications.

Handwriting code for database APIs can be a time consuming and expensive process that often exposes organizations to a variety of risks relating to quality, consistency, and developer effort. DreamFactory specialises in REST API generation for a range of databases that gives you the ability to generate a secure, fully documented API in minutes.

As the wave of AI sweeps through the technology landscape, many have hopped on board. Interestingly enough, and often overlooked, is that many AI capabilities are served through APIs. Fancy user interfaces integrate with the actual mechanisms where the magic happens: the APIs. So, when generating revenue through AI platforms, the APIs drive the revenue.

The mid-sized enterprise is the fastest-growing market opportunity for data storage. But not just any storage system will do. These days, mid-sized enterprises must handle the complexities of unremitting data growth and distributed infrastructure, meet sustainability goals, manage the diverse storage needs of mission-critical applications, and respond to user requirements. Oh, and they need uninterrupted access to their data no matter what.