What 200 Engineers Told Us at Current London 2025

We met over 200 engineers, architects, and platform leads at Current London 2025. On the floor, at our booth, and in sessions (Kafka lag by our CTO Stéphane Derosiaux and Kafka observability by our Head of R&D Florent Ramière), we heard the same problems repeated. Everyone's stack looked different, but the challenges were consistent.

Here are the top pain points and how they're shaping our roadmap.

Schemaless Data Causes 99% of Data Quality Issues

One platform team told us bluntly: "99% of our data quality issues are caused by schemaless data." They meant the endless workarounds required to infer schemas, manually fix sync issues with downstream analytics, and triage errors long after data had landed.

This echoed across conversations. Late validation, schema fragmentation across streams and lakes, and broken assumptions in the pipeline are slowing teams down.

What we're doing about it: We're investing heavily in data quality enforcement at the streaming level with Conduktor Trust. If quality isn't baked in before it enters your pipelines, it's already too late. Expect deeper integrations with schema registries and data formats, more proactive anomaly detection, and improved visibility into policy violations.

Legacy System Migrations Still Take Years

Several teams shared that migrating from RabbitMQ, Tibco EMS, or legacy databases remains a multi-year slog. They're not just moving platforms. They're untangling deeply embedded processes, bridging old systems, and rethinking their entire event strategy.

What we're doing about it: We're focusing on making the migration path smoother, both technically and operationally. Better tooling for hybrid environments, clearer guidance for staging transformations, and support for gradual, low-risk cutovers.

Developers Wait Months for Access to Topics and Connectors

Developers want access to data, but self-service tooling can't keep up. Several organizations described month-long waits just to get access to the right topics or connectors. Platform teams are drowning in Slack messages, Jira tickets, and manual provisioning.

What we're doing about it: Our goal is to unlock developer autonomy without compromising security and governance. We're investing in policy-based access controls, connector templates, and scalable patterns for "Connect-as-a-Service." Domain teams, not just central admins, should configure and deploy what they need.

Flink Is Exciting but Operationally Painful

Apache Flink came up frequently, usually excitement followed by concern. Teams are intrigued by its ability to enable richer real-time use cases, but they're frustrated by the lack of RBAC controls, poor isolation of workloads, and difficulty debugging application errors.

What we're doing about it: We see Flink as a major opportunity, but it needs a scalable model to fit into platform-as-a-service architecture. We're exploring ways to bring RBAC, guardrails, and monitoring into the developer experience so Flink can scale with your team, not just your data.

Cluster Replication for Data Sharing Is a Tax, Not a Choice

Cluster replication is still the go-to solution for sharing streaming data with external partners. But almost every team we spoke to disliked the cost and complexity. One attendee summed it up: "We replicate because we have to, not because we want to."

What we're doing about it: With Conduktor Exchange, we're reimagining data sharing around a zero-duplication model. Secure, governed, and performant access to data without copying it. Our roadmap includes more granular access controls, proxy-based authorization patterns, and stronger support for cross-cluster visibility.

Real-Time Data Is Still Fragmented and Fragile

The clearest takeaway from Current: the real-time data landscape inside most organizations is still fragmented and fragile. Despite massive investments, teams are still stitching together pipelines, managing replication by default, and struggling to get clean, timely data into the hands of people who need it.

This reinforces our direction. At Conduktor, we're helping teams:

• Unify fragmented data sources: from Kafka to RabbitMQ, Amazon SQS, legacy MQs, and cloud-native streams.
• Optimize operations: governed access, schema enforcement, and in-stream validation to reduce downstream rework.
• Expand the impact of real-time data: making it easier for more teams (engineering, analytics, data scientists) to safely access trusted data, and enabling its use in GenAI and Agentic AI systems that depend on fresh, high-quality inputs.

We believe real-time operational data (transactions, events, metrics, and signals that reflect the state of the business as it happens) should be accessible, trustworthy, and actionable. Our roadmap is designed to make that a reality: less replication, tighter controls, and faster paths from source to business value.