July 2026 Summaries

The Agentic Data Plane is a crucial governance and runtime layer designed to manage AI agents' interactions with data, tools, identities, and models, filling a gap in current enterprise infrastructure that existing identity management and API gateways cannot address. As AI agents increasingly perform actions autonomously across multiple systems, a unique infrastructure is needed to provide identity, policy enforcement, and comprehensive activity trails for these agents, something not currently offered by traditional systems. Unlike traditional API gateways that manage services, the Agentic Data Plane introduces governance for agents by managing identity, tool calls, and model usage, promoting open standards to ensure interoperability across diverse environments and avoiding vendor lock-in. The Redpanda Agentic Data Plane distinguishes itself by enabling deployment within an organization's own cloud infrastructure, maintaining data sovereignty, and supporting comprehensive agent identity and action tracking through a streaming-native data integration layer. This approach ensures that agents operate under explicit governance, with a focus on compliance, security, and real-time data access, thereby closing the infrastructure gap for deploying autonomous agents in enterprise environments.

Redpanda Connect introduces a native Oracle CDC input that captures data changes from Oracle databases using LogMiner, eliminating the need for Debezium, Kafka Connect runtime, or a JVM. This update allows for the creation of an efficient two-stage data pipeline where changes are streamed from Oracle to a durable Redpanda topic and then into ClickHouse, using simple YAML configurations. The process is designed to facilitate the movement of data from a central Oracle operational system to a high-performance ClickHouse analytics environment without overburdening the source database. By streaming changes through Redpanda, users can maintain data durability, enable replay capabilities, and expand the data pipeline without additional load on Oracle. This setup uses Docker for containerization and can be initiated with a free 30-day trial license. The pipeline is designed to be scalable, allowing for the inclusion of multiple tables and the potential to fan out data to various sinks, such as a data lake, without re-engaging the Oracle database.