Systems | Development | Analytics | API | Testing

Building Secure AI Agents with Kong's MCP Proxy and Volcano SDK

Modern AI applications are no longer just about sending prompts to an LLM and returning text. As soon as AI systems need to interact with real business data, internal APIs, or operational workflows, the problem becomes one of orchestration, security, and control. The challenge is to build secure AI agents without embedding fragile logic or exposing sensitive systems directly to a model. This is where a layered architecture using Volcano SDK, DataKit, and Kong MCP Proxy becomes compelling.

How DreamFactory Accelerates SOC 2 Compliance with Secure API Management

DreamFactory is a secure, self-hosted enterprise data access platform that provides governed API access to any data source, connecting enterprise applications and on-prem LLMs with role-based access and identity passthrough. Organizations working toward SOC 2 compliance face a familiar set of challenges: inconsistent access controls, fragmented data access security, noisy or incomplete logs, risky custom integrations, and difficulty proving governance during an audit.

The Fastest Way to Generate SmartBear-Ready OpenAPI Specs from Real Backend Systems | DreamFactory

Executive Summary: Organizations spend weeks or months manually reverse-engineering legacy databases into OpenAPI specifications before they can leverage SmartBear's powerful API toolchain. DreamFactory eliminates this bottleneck entirely.

Build Agentic Workflows: Expose API Orchestration as MCP Tools with Kong AI Gateway

Learn how to expose an API orchestration workflow as an MCP server using Kong AI Gateway, configure semantic guardrails, and build an agent with the Volcano SDK. We onboard GPT-4 behind /llm, orchestrate with DataKit, and debug MCP tools in Insomnia—end-to-end without adding server code.

Can We Still Trust the Code? #speedscale #qualityassurance #digitaltwin #trust #devops

The "Velocity Gap" is real. AI like Claude and GitHub Copilot are pumping out code faster than ever, but there’s a catch: Engineers don't trust it yet. We’re moving away from the old days of "clicking around" in a test environment, but how do we verify code at the speed of light? Ken breaks down why the future of QA isn't just "testing," it’s simulation. Video collab with @ScottMooreConsultingLLC Learn More: speedscale.com.

Query Optimization Strategies for Database APIs: A Complete Technical Guide

Database performance is often the primary bottleneck in API-driven applications. Whether you're serving a mobile app, powering a microservices architecture, or exposing enterprise data through REST APIs, slow queries translate directly to poor user experience, increased infrastructure costs, and system scalability challenges. This guide explores proven query optimization strategies that development teams can implement to dramatically improve API performance.

A Developer's Guide to MCP Servers: Bridging AI's Knowledge Gaps

Have you ever asked an AI assistant to generate code for a framework it doesn't quite understand? Maybe it produces something that looks right, but the syntax is slightly off, or it uses deprecated patterns. The AI is working hard, but it lacks the specific context it needs to truly help you. The Model Context Protocol (MCP) was designed to bridge this knowledge gap by giving AI assistants access to domain-specific knowledge and capabilities they don't have built in.

Escaping the Integration Tax: Why Your Partners Are Stuck in Limbo (and How to Onboard in Days, Not Months)

In a high-interest-rate environment, the most expensive asset a bank can hold is a signed partner contract that isn’t generating transaction revenue. For many regional banks, the 4–6 month gap between “contract signed” and “first transaction” is driven by manual compliance reviews, fragmented security processes, and custom integration work that delays go-live. We call this the “Integration Tax.”