Systems | Development | Analytics | API | Testing

Perfecto AI: Financial Trading App Stock Simulator

This video demonstrates Perfecto AI in action, showcasing its advanced test automation capabilities within a financial trading app stock simulator. See how Perfecto AI, powered by Perforce Intelligence, eliminates the need for brittle scripts and manual frameworks — instead delivering AI-driven actions and natural language prompts that automate testing processes from setup to validation. Observe how it verifies critical components like graphs, colors, and trends, delivering consistent and reliable results even as user interfaces evolve.

Beyond the Buzz: Predicting the Next Five Years of Data AI Gateways

Data AI Gateways are reshaping how businesses manage APIs by automating key processes like creation, security, and scaling. These platforms simplify API operations, reduce costs, and improve efficiency, making them essential for enterprises navigating AI adoption. Here's what you need to know: What They Do: Automatically generate APIs, enforce security (e.g., RBAC), and integrate multiple databases. Why They Matter: Tackle challenges like siloed systems, scaling, and AI governance.

The Benefits of Continuous Integration: A Guide to Streamlining Your Business

DevOps is the delivery process that focuses on the cross-functional approach of building and shipping applications in a faster manner through automation of infrastructure, workflow as well as performance evaluation. One of the most essential components of DevOps is CI/CD, which acronym for continuous integration (CI) and continuous delivery (CD).

How to Avoid N+1 Queries in Django Python

Django is a powerful web framework that simplifies how developers interact with databases through its Object-Relational Mapping (ORM) system. However, even with its benefits, it’s easy to fall into performance pitfalls such as the N+1 query problem. In this article, we’ll explore what N+1 queries are, why they can be an issue for your application, and how to mitigate them using Django’s best practices. Let's dive in!

Beyond console.log: Smarter Debugging with Modern JavaScript Tooling

Ask any JavaScript developer their most used debugging tool and chances are the answer will be console.log. It’s immediate, low friction, and available in every browser. For development, it’s fantastic. But for production and complex applications, if you rely on console.log alone, cracks begin to show. It lacks context, doesn’t persist, and makes reproducing or analyzing user-reported issues a challenge. In this article, we’ll look at smarter, scalable debugging strategies.

It's time to start prioritizing every side of API discovery

Join us for a deep dive into API discovery – and why it’s time to treat it like a first-class priority. In this session, we’ll explore what we mean by the “two sides of API discovery” and why unifying both sides with a comprehensive solution is critical to driving API adoption and reuse, strengthening your organization’s security posture, and mitigating the financial and developer productivity-related costs associated with API sprawl.

Kong AI Gateway 3.11: Reduce Token Spend, Unlock Multimodal Innovation

Today, I'm excited to announce one of our largest Kong AI Gateway releases (3.11), which ships with several new features critical in building modern and reliable AI agents in production. We strongly recommend updating to this version to get access to the latest and greatest that AI infrastructure has to offer.

Kong Gateway Enterprise 3.11 Makes APIs & Event Streams More Powerful

We’re excited to bring you Kong Gateway Enterprise 3.11 with compelling new features to make your APIs and event streams even more powerful, including: We’ll also touch on what’s new with Konnect networking and Active Tracing. There’s a lot to unpack, so keep on reading for the full story!

Build Your Own Internal RAG Agent with Kong AI Gateway

RAG (Retrieval-Augmented Generation) is not a new concept in AI, and unsurprisingly, when talking to companies, everyone seems to have their own interpretation of how to implement it. So, let’s start with a refresher. RAG (short for Retrieval-Augmented Generation) is a technique that injects relevant data from an external knowledge source directly into a prompt before sending it to a Large Language Model (LLM). “But wait, my model is already fine-tuned on my domain-specific data.

Bridging SQL and Vector DBs: Unified Data AI Gateways for Hybrid AI Stacks

AI systems need both structured data (like spreadsheets) and unstructured data (like images or text). SQL databases excel at structured data, while vector databases handle unstructured data for tasks like similarity searches. The solution? Hybrid AI stacks that combine both through unified Data AI Gateways.