Data streaming engineers are critical to faster AI adoption, say UK business leaders
New research shows UK executives see data streaming engineers as essential to quicker AI adoption and confident decision-making.
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Modern Software Development For Today's Systems & Applications
Announcing Confluent Platform 8.3: Powerful Apache Flink SQL operations, Easier KRaft Migrations, Expanded Monitoring and more.
Platform teams want to maximize the value of data in motion, but separate workstreams for stream processing, monitoring, KRaft migrations, and data governance create friction as environments grow. As a result, teams spend more time managing operational overhead and less time building. Today, we’re excited to announce Confluent Platform (CP) 8.3.0, built on Apache Kafka 4.3.0, reinforcing our core capabilities as a data streaming platform.
Is Your Data Architecture Actually Resilient?
Your capacity management has to go beyond ideal scenarios. It isn’t just about handling peak traffic, it’s about the failover and the failback. OCBC's George Goh explains why continuous monitoring is the only way to ensure your system is ready for the unexpected tomorrow.
Zero Data Loss: Migrating Thousands of Microservices
OCBC migrated thousands of microservices, batch jobs, and monolithic applications across multiple regions in just six hours with zero data loss. George Goh shares how six months of planning enabled flawless execution.
Redpanda vs Kafka vs Confluent: An Honest Comparison
Data streaming has moved from a niche pattern used by a handful of internet-scale companies to the default backbone for event-driven architectures, real-time analytics, and now AI pipelines. What started as log aggregation at LinkedIn has become the plumbing for fraud detection, IoT telemetry, microservices communication, and retrieval-augmented generation. Three names dominate that conversation today.
Tableflow: Turn Kafka Topics into Iceberg Tables
TL;DR: Tableflow is a Confluent Cloud feature that materializes Apache Kafka topics as Apache Iceberg or Delta Lake tables, eliminating custom data pipelines by automatically handling schematization, type conversions, schema evolution, CDC stream materialization, catalog publishing, and table maintenance.
Thousands of Migrations, Zero Data Loss: OCBC's Confluent Playbook | Life Is But A Stream
Migrating an entire bank's infrastructure without losing a single transaction sounds impossible. Yet, OCBC successfully modernized their event-driven architecture across Singapore, Malaysia, and Hong Kong with zero data loss. In this episode, George Goh (Executive Director at OCBC) joins Joseph Morais and Sami Amed (Staff Solutions Engineer at Confluent) to pull back the curtain on a massive data streaming migration, how the team executed a flawless migration of thousands of producers and consumers in a single weekend.
Stream Governance: Making Compliance a Property of Data in Motion
As organizations have transitioned from batch processing to real-time streaming architectures, a critical governance gap has emerged. Legacy data governance tools designed for databases, warehouses, and file systems assume that information is stationary and focus on protecting, classifying, and auditing data at rest.
Building Secure, Resilient, and Compliant Fraud Detection With Confluent Cloud
Banking customers expect financial transactions to be completed quickly. Fraud analysis must execute in milliseconds, so traditional batch processing systems are inherently too slow. To safeguard transactions, institutions must shift to proactive, in-flight prevention. Confluent enables this shift by using Apache Kafka and Apache Flink to continuously correlate transactional and behavioral signals, blocking malicious activity before a transaction settles.
Demo: Real-Time Context Engine for Fleet Management
Use Real-Time Context Engine and Claude, or any MCP-compatible client, to explore operational data using natural language in real time. That includes everything from simple lookups to multi-step investigative questions like: Confluent’s Real-Time Context Engine gives AI agents live access to operational context as events happen across the business. Instead of relying on stale snapshots, agents can query and reason over continuously updated tables in real time.