Systems | Development | Analytics | API | Testing

Performance Under Pressure: Why AI Gateways Matter for Real-Time AI

Real-time AI is transforming how businesses operate, from faster decision-making to improved customer experiences. But to handle the speed and complexity of real-time data, enterprises rely on AI gateways. AI gateways act as intermediaries, ensuring smooth, secure, and scalable communication between AI models and enterprise systems. Here's why they matter: Speed: They process and route data instantly, critical for industries like finance, healthcare, and logistics.

Ai Assistant Functionality And Validation: A Complete Guide

An uninterrupted user experience often relies upon AI assistants which are working normally; we must better facilitate AI assistants’ integration into our daily lives and work by ensuring that the AI assistants operate as intended. Testing and validation is necessary to help you refine the interaction.

Workshop Automations 101: Introduction to API Platform-as-a-Service Concepts and Delivery Methods

Discover the fundamentals of delivering API management as a platform service with Kong Konnect. In this introductory workshop, we’ll explore essential concepts and methodologies that Platform Providers use to provide scalable, self-service API management capabilities to Platform Consumers.

Shift Left on Performance Testing - Without Killing Developer Velocity

Traditional performance testing often comes late in the delivery cycle, typically just before release. By then, performance issues are usually quite expensive to fix, can delay deployments, and frustrate development velocity. A Shift Left testing approach addresses this by integrating performance testing early in the development cycle so issues surface while they’re still easy and cheap to fix.

What's the Difference Between Zephyr and Xray?

When choosing the best test management solution for your team, there are a lot of options and decisions to make. What are your current testing needs, and what will you need in the future? Do you want a standalone solution, or something native to Jira? When you’re comparing capabilities, it can be hard to tell from a tester, admin, or consultant’s perspective what the day-to-day usability and experience will be like with each tool.

Is MindsDB Safe for Enterprise Use? Security Risks and Alternatives

MindsDB has gained attention for its promise to act as a “SQL server for AI”, enabling users to write natural language prompts that convert into executable database queries. While this may appeal to data scientists and AI teams, enterprise CISOs and compliance leaders should proceed with caution. Recent disclosures have revealed critical security vulnerabilities in MindsDB’s platform that raise serious questions about its suitability for sensitive or regulated environments.

Top 7 AI Solutions for API Testing and Monitoring in 2025

APIs are the nervous system of modern software—and as AI systems like large language models (LLMs) become deeply embedded across products and platforms, the demand for fast, secure, and scalable API infrastructure has never been higher. From early-stage startups to global enterprises, organizations rely on APIs not just to move data, but to power real-time intelligence, automation, and customer experiences.

Best Ai Coding Tools In 2025: Top Assistants For Developers

Ever since AI tools came into the picture, it has transformed a lot of industries. An industry most evolved due to this revolution of AI is the software Development industry. There have been discussions about AI for coding being so good that it holds the potential to replace developers, which might be debating but precisely a false claim.

EP 16: Modernization Unpacked: Perspectives

In this live episode, recorded at WSO2Con Europe 2025, hosts *Sanjiva* and *Asanka* are joined by *Jeremy* *Schneider,* Senior Partner & Co-Head of Global Software & High-Tech Practice at McKinsey & Company, to explore the challenges and opportunities of platformless modernization and the cultural transformation required for organizations to become software-driven. They discuss the importance of leadership in understanding technology, the "build vs. buy" debate in platformless architecture, and how organizations can empower teams with autonomy while maintaining governance.