The transition from Kafka Summit to Current is now complete, with this year's London conference now rebranded to match Confluent’s US and India events and providing a strong indicator that the real-time ecosystem now extends far beyond Apache Kafka. With more than 2,200 attendees, in-depth technical presentations, and countless exhibitor hall discussions, it is evident that real-time streaming is here to stay and the ecosystem is evolving quickly, branching out into AI-native systems, multi-technology stacks, and production-grade stream processing.
What We Saw
For the third consecutive year, Factor House was on the ground in London as a Silver Sponsor, running product demos, meeting clients, and, more importantly, learning about the needs of engineers managing complex deployments, platform teams integrating Flink and Kafka, and architects exploring AI built on live data.
While the Kafka Summit name has been replaced, Kafka remains a foundational technology. However, attention is shifting to system-level control, end-to-end observability, and tools that reduce operational friction without sacrificing power. We’re focused on that space with Kpow for Kafka, Flex for Flink, and, soon, the Factor Platform.
Key Signals
AI Is Going Event-Driven - But Engineers Remain Cautious
Streaming-first AI was a recurring theme at Current. Sessions like "Flink Jobs as Agents" (Airy Inc.) explored how AI agents can interact with a live state, reacting in real time rather than relying on stale snapshots.
But several engineers we spoke to flagged concerns.
While Kafka and Flink provide the backbone, durable, deterministic, and observable, the idea of introducing autonomous agents into critical pipelines raised eyebrows. There’s excitement, yes, but also scepticism around operational safety, debuggability, and unintended consequences. As one engineer put it:
“If an LLM is making decisions in my pipeline, I want to know what it saw, why it acted, and how to stop it fast.”
Visibility and control are not optional; they’re the line between innovation and outage. AI might be event-driven, but it’s still infrastructure. And infrastructure needs guardrails.
Production Resilience > Architectural Purity
Sessions from OpenAI, AWS, and Daimler all emphasized pragmatism. OpenAI’s Changing Engines Mid-Flight offered real lessons on handling Kafka migrations under load. Elegant designs are great, but shipping reliable systems matters most.
Flink Is Now a First-Class Citizen
Flink moved from curiosity to cornerstone. Teams from ShareChat, Wix, and Pinterest shared how they reduced latency and costs while simplifying their pipelines. However, Flink remains operationally raw; hence, Flex, our UI and API, is designed to make Flink observable and manageable in real production environments.
Noteworthy Tools
We saw an uptick in focused tools solving specific friction points, some standouts for us:
- ShadowTraffic – Safe, controlled Kafka traffic simulation.
- RisingWave – Real-time SQL queries over Kafka streams.
- Gravitee – Fine-grained Kafka API access control.
- Imply – Sub-second dashboards on live data.
- Snowplow – Clean, structured enrichment pipelines for streaming events.
Where Factor House Fits
As complexity grows and streaming intersects with AI, teams need visibility, safety, and efficiency, not more abstraction. Our upcoming Factor Platform unifies Kpow and Flex into a single control plane for data in motion, enabling teams to manage Kafka and Flink with confidence across clusters, clouds, and regions, and providing a layer of clarity across an organizations complete streaming ecosystem.
If you’d like to learn more about Factor House products book a demo today.