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.

The next evolution in QA: How AI is changing software testing

Shipping high-quality software quickly is challenging. QA professionals are facing pressure to test more, faster in a world where GenAI is pushing delivery – all while trying to cut costs. For years, manual testing and traditional automation tools like Selenium have been the standard. But both come with challenges. Manual testing alone can be slow and prone to errors, while Selenium and similar tools require coding expertise, need constant script maintenance, and are easily broken by UI changes.

How to create a test cycle | Zephyr

SmartBear Zephyr is the Jira-native test management and automation platform that empowers your team to deliver better software, faster. Organizing your testing into Test Cycles is the best way to align your QA efforts with specific sprints, releases, and versions, ensuring your team stays focused and on schedule. This short demo video guides you through the process of setting up and populating your Test Cycles. You’ll learn how to define execution windows, link cycles to specific release versions, and pull in test cases from across different Jira projects to create a unified testing effort.

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.