Systems | Development | Analytics | API | Testing

In 2025, real-time data moved from important to mission-critical. From billion-event pipelines to AI agents reasoning over fresh data streams, the conversations this year revealed just how fast organizations are rethinking their data infrastructure and what’s possible when data streaming becomes the foundation.

Mohamed Ahmed Anwar shares why “shifting left” to process data closer to its source is key to AI agent performance, speeds RAG knowledge updates, And eases the move from legacy on-prem to scalable cloud architectures.

See how Tableflow converts data to Apache Iceberg or Delta Lake format, and how it can be integrated with Amazon Redshift to query and analyze customer activity snapshots.

Ramon Cidade shares why Apache Flink was a game changer at Current 2025 in New Orleans, and gives his take on what makes the data streaming event so special: the community, the people, and the technology they’re innovating with.

What does the future hold for agentic AI? Lucia Cerchie predicts a shift from chatbots to more agent-to-agent interactions built into real-world business workflows.

From the heart of the expo hall at Current NOLA, this special episode drops you into the conversations, energy, and the breakthroughs as they happened. Host, Joseph Morais, and co-host, Adi Polak talk with data streaming leaders and community voices to unpack how teams are using Apache Kafka and Apache Flink to power low-latency, AI-ready applications—covering patterns from usage-based billing and hybrid operations to cost efficiency and streaming governance. You’ll also hear how shift-left processing and governance make AI-ready data possible at scale.

Experience the vibe of Current NOLA! Big insights, thought-provoking conversations, and real voices from the data streaming community.#current25.

See how Debezium captures real-time data changes from a Postgres database. Watch how inserts, updates, and deletes work and are being streamed instantly, ensuring exceptional auditability, reproducibility, and replayability of the data.

Monitoring is old school. Agentic AI makes observability autonomous. Learn how it can be used to spot patterns, find issues, and keep systems healthy—all on its own.