Systems | Development | Analytics | API | Testing

The Hidden Cost of Building Your Own LLM Data Layer

For most businesses, the break-even point for self-hosting only makes sense if processing 100–200 million tokens daily. Otherwise, managed API solutions are more cost-effective, faster to deploy, and easier to maintain. Alternatives like DreamFactory offer pre-built, secure API layers, saving time and money while simplifying enterprise AI integration. Bottom line: Building your own LLM data layer is a major investment with hidden challenges.

Security Testing Explained: Protecting Modern Applications And Apis

Security testing helps identify weaknesses in software before attackers can exploit them. It protects sensitive data, ensures system stability, and controls user access. With web, mobile, and API-based applications growing rapidly, security threats are increasing. Security testing helps teams detect risks early, prevent breaches, and meet compliance standards.

From APIs to Agentic Integration: Introducing Kong Context Mesh

The promise of agentic AI is clear: autonomous systems that can reason, plan, and act on your behalf. But there's a fundamental problem standing between that vision and enterprise reality: agents need context to make decisions, and that context lives scattered across your organization. Context is any data — or any abstraction that enables access to data — that an agent needs to do its job. Customer records in your CRM. Inventory levels behind your fulfillment APIs.

Tracking testing progress with reports | Zephyr

SmartBear Zephyr is the Jira-native test management and automation platform that empowers your team to deliver better software, faster. Its reporting and dashboard capabilities provide real-time visibility into your quality metrics, so you always know the status of your release. This short demo video shows you how to navigate the Zephyr Reports tab and build customized Jira Dashboards. Whether it’s via high-level execution summaries or deep-dive traceability reports, you can track coverage and identify testing bottlenecks instantly.

Introducing Agent-Flavored Markdown (AFM): No Code, Portable AI Agents

Advances in large language models (LLMs) and their widespread accessibility have transformed both what software can do and how we build it. The use of LLMs has quickly evolved from simple single-turn interactions to AI agents that reason, use tools, manage state, and operate autonomously.

Introducing Agent-Flavored Markdown (AFM): Natural Language Definitions for Framework-Agnostic AI Agents

Advances in large language models (LLMs) and their widespread accessibility have transformed both what software can do and how we build it. The use of LLMs has quickly evolved from simple single-turn interactions to AI agents that reason, use tools, manage state, and operate autonomously.

Modernizing Integration & API Management with Kong and PolyAPI

APIs and integrations are the foundation of the modern enterprise. Every organization needs to securely connect systems, move data, and automate workflows, all while maintaining control, visibility, and flexibility. Increasingly, those same APIs are also being consumed by AI-powered applications and agents that must interact safely with underlying business systems.