Systems | Development | Analytics | API | Testing

Summarize with AI: ChatGPT Claude Google AI Mode Grok Perplexity In today’s data-driven world, business intelligence and analytics play a huge role in better understanding your customers, improving your operations, and making actionable business decisions. While there’s no doubt about the value of implementing a BI solution, many ERP users face the same challenges around the quality and credibility of their data.

That’s a wrap on API Summit 2025! At our eighth annual event, the brightest minds in the worlds of APIs and AI gathered in New York City to define the next chapter of digital innovation. We're entering an era where APIs are not just connecting services but connecting intelligence. APIs are the neural pathways of this new AI world, where agents will reason, act, and collaborate through endpoints. At this year's API Summit, we saw how quickly this vision is becoming reality.

In the evolving landscape of agentic systems, Confluent and Google Cloud together emerge as critical enablers, providing the real-time infrastructure that underpins efficient, reliable, and intelligent data flow. This powerful synergy addresses key challenges in agent-to-agent (A2A) communication, interaction with external resources, and the overall stability and observability of complex multi-agent environments.

The new StudioAssist Agent Mode turns your AI assistant in Katalon Studio into a connected, context-aware testing partner. It now supports MCP Servers, HTTP-based services that let the agent fetch real-time information and perform actions directly inside your project. Katalon ships with two built-in MCP Servers: You can also add your own HTTP-based MCP Servers to extend StudioAssist’s reach. (Note: authentication support is coming soon.)

Imagine an airline system monitoring traffic around an airport. If it detects a major delay, countless systems may need to react instantly: Ground operations to adjust flows. Some of these systems will still connect via API, traditional MQ or iPaaS technologies, but the data’s volume and urgency and the ease of decoupling apps make architecting with Kafka the better fit. The natural question is: should all these applications & systems connect to the same Kafka cluster?

Testing database-driven applications is notoriously painful. If your app depends on MySQL, you’ve probably spent hours setting up local databases, running migrations, loading data, and then cleaning everything up just to rerun your tests. This repetitive cycle slows development, breaks pipelines, and introduces inconsistency between local and production environments.

For the tenth consecutive time, Gartner has named Google Cloud Apigee a Leader in the 2025 Gartner Magic Quadrant for API Management.

Query templates in BigQuery data clean rooms let you create pre-defined queries that run against specific tables, reducing the risk of data exfiltration.

Federal agencies are right to prioritize commercial off-the-shelf (COTS) solutions for procurement modernization. Recent executive orders have provided a clear mandate for 'buy before build'—steering agencies toward proven, market-ready technology to accelerate mission delivery. But not all off-the-shelf procurement solutions are created equal. The technology landscape has evolved, revealing a critical divide in the world of off-the-shelf acquisition software.

Healthcare organizations are under growing pressure to connect legacy EHR (Electronic Health Record) and ERP (Enterprise Resource Planning) systems while safeguarding patient privacy and meeting strict compliance standards. Most of these systems — Epic, Cerner, MEDITECH, Infor, Oracle, SAP, and others — rely on enterprise-grade databases like Oracle, SQL Server, IBM DB2, SAP HANA, InterSystems IRIS, and PostgreSQL.