Systems | Development | Analytics | API | Testing

Want secure, AI-ready data access? DreamFactory's Role-Based Access Control (RBAC) system simplifies managing who can access what in your databases and APIs. Why it matters: Poor data management causes 1 in 3 AI projects to fail. Breaches by insiders cost $4.99 million on average, yet only 24% of AI projects include proper security. How DreamFactory helps: Assign roles to users, control access to specific data, and limit actions (like view vs. edit) without custom code.

We're excited to introduce a major update to the Choreo CLI: support for the Model Context Protocol (MCP). This enhancement brings conversational AI capabilities into your development workflow, enabling you to manage your Choreo environment using natural language commands.

Let's talk about a problem that might sound simple but gets complex quickly: copying data from one Kafka cluster to another. As our Kafka usage grows, many of us find ourselves managing multiple clusters and needing to share data between them. Or worst still, sharing data to an external cluster. During a London meetup, we explored why this happens, what existing solutions offer, and why we decided to build our own Kafka replicator. Here's what we learned.

Agriculture has long been the backbone of human survival, proof of our deep connection with and dependence on nature. But as the world evolves, so do the challenges in farming. From shrinking arable land to unpredictable weather patterns, how can farmers keep up? How do we ensure there's enough food for future generations? There’s no doubt that farming has come a long way, but let’s be honest, it’s getting harder every year.

When you think of artificial intelligence in transportation, what’s the first image that comes to mind? Is it self-driving cars smoothly cruising city streets, or maybe delivery drones zipping through the skies? While the dream of fully autonomous vehicles might still be on the horizon, the reality is that AI is already reshaping how we move, every single day. Look how our Co-founder is enjoying the view in a self-driving car in the USA! ‍ Yes, you saw that right, it’s fully autonomous.

How does GDPR impact AI innovation, and what affects might AI have on regulations like GDPR? According to McKinsey, 78% of companies now use AI in at least one area of their business as of July 2024. But this quick adoption brings challenges for organisations handling data from the European Union and the UK. The main challenge for InfoSec and other enterprise leaders is clear. Using AI effectively means being able to develop faster.

The demand for AI-driven applications is surging, and enterprises have reached an inflection point where they can no longer afford fragmented, siloed development. Traditionally, AI development is done by data scientists or machine learning experts with deep expertise in multiple tools and frameworks.

AI is everywhere. Depending on who you ask, it’s either making developers obsolete, or it’s just hype. But for those of us who’ve actually used AI tools in real-world engineering workflows, especially in complex distributed systems, the truth lies somewhere in between. At Multiplayer, we’ve spent the past few years exploring how AI can—and can’t—help solve two of the most persistent challenges in distributed systems: documentation and debugging.