Systems | Development | Analytics | API | Testing

Lenses 6.2 - Trusting Agents to build & operate event-driven applications

At Lenses, our goal has always been to help organizations get the most out of their streaming data. We started with visibility into the Apache Kafka, moving up to the part that drives value, the application layer and now the Agentic layer. Lenses 6 moved us into a multi-Kafka world, as increasing, our clients aren’t just running on one type of Kafka anymore, and as sovereign cloud becomes increasingly topical (no pun intended) this is only increasing.

Your AI agent is one misconfigured MCP server away from leaking production data.

2025 was vibe coding. 2026 is Agentic Engineering - and the security rules haven't caught up. AI agents now have direct access to your databases, your APIs, your Kafka clusters. The protocol giving them that access is MCP. And most teams have no idea how exposed they are. We are fixing this problem with OAuth 2.1.

Legacy VM Footprints are Holding Back Digital Transformation

Enterprises in 2026 are under increasing pressure to modernize applications, adopt hybrid cloud architectures, and streamline operations—but their expanding and aging VMware footprints have become a major obstacle. As VMware licensing models evolve and operational costs climb, reducing or restructuring this footprint has become just as critical as adopting new platforms.

JavaScript Is Evolving Faster Than Ever - And JSConf Spain Made It Impossible to Ignore

There’s something powerful about stepping away from your day-to-day work and being surrounded by people asking the same questions you’ve been thinking about: At JSConf Spain, those answers don’t come from a single talk. They emerge from patterns — ideas that repeat across different speakers, different companies, and different perspectives.

What is an AI Data Gateway? | DreamFactory

An AI Data Gateway is a secure intermediary that connects enterprise data sources (like databases and file systems) with AI systems. It simplifies how AI accesses data while enforcing strict security, compliance, and governance measures. Instead of allowing direct access to sensitive data, the gateway uses secure REST APIs to control and monitor all interactions.

The new rules of QA for AI-driven finserv

Contents AI is now embedded across the entire software development lifecycle. Developers use it to generate code. Product managers use it to prototype features. Teams use it to move from idea to deployment faster than ever. Code moves faster. Features ship more frequently. Iteration cycles shrink. Across industries, companies that embrace this speed have a distinct competitive advantage. But in highly regulated industries, including financial services, speed can’t come at the cost of quality.

Automated Mobile Testing: Redefining Quality Assurance with AI Integration

The contemporary mobile ecosystem is incredibly complicated. Applications today are not standalone anymore; they are dynamic, heavy in features, and constantly communicating with cloud solutions, wearables, and IoT devices. Although the use of traditional test automation has contributed to enabling engineering teams to remain in step with agile delivery, the sheer number of fragmented devices and continually changing user interfaces has revealed the limitations associated with it.

How CARIAD Powers Software-Defined Vehicles with Real-Time Data Streaming | Life Is But A Stream

45 million vehicles, 90 markets, 12+ iconic brands, each with its own data silos, standards, and infrastructures. In this episode, Chetan Alatagi, Solution Architect reveals how they transitioned from fragmented legacy ETL silos to a Unified Data Ecosystem—a global data streaming highway that turns vehicle telemetry into real-time value.

The Role of Integration in the Agentic Enterprise

In this episode of, *Steve Jordan* and *Shafreen Anfar* from WSO2 explore how integration is paving the way for the agentic enterprise, where humans and AI agents collaborate to drive business success. They discuss how seamless connectivity across systems provides agents with the real-time context and ability to take action that is necessary to scale AI from simple pilots to full-scale production. The conversation also highlights the importance of robust security, governance, and observability in managing this new digital workforce.