Resources

Every click, transaction, deployment, service call and model response generates a signal about what's happening across your business. Most organizations already collect that data. The challenge is turning growing volumes of telemetry into the visibility, reliability and responsiveness modern digital businesses require.

How to effectively build and scale retrieval-augmented generation (RAG) for real-time Generative AI applications using Confluent’s Data Streaming Platform. Leverage connectors, Flink, and stream governance across 4 steps: data augmentation, inference, workflows, and post-processing.

This one-pager examines why traditional observability stacks become more costly and complex as operational data volumes grow. Discover how a shared data streaming backbone can help teams maintain visibility during demand spikes, route telemetry to multiple downstream systems and change observability tools without rebuilding data pipelines.

Explore insights from 4,625 IT leaders on how data streaming platforms are accelerating AI adoption, powering agentic AI, delivering measurable ROI, and helping organizations turn real-time data into competitive advantage.

Managing Kafka at scale can pull engineering teams away from the work that drives innovation. This guide examines common Kafka deployment approaches, reveals the hidden costs of self-management and highlights practical patterns for building scalable, governed and AI-ready streaming applications.

Wondering why observability costs keep rising while visibility keeps shrinking? This white paper explores five common signs of observability debt, including duplicate telemetry pipelines, fragmented data flows, visibility gaps during incidents, and growing engineering overhead. Learn how high growth organizations are rethinking their telemetry foundation to reduce complexity, improve reliability, and support observability, analytics, security, and AI from the same operational data.

Download the “Kafka In the Cloud: Why It’s 10x Better With Confluent” ebook to take a deep dive into how Confluent harnessed the power of the cloud to build a data streaming platform that’s 10x better than Apache Kafka, so you can leave your Kafka management woes behind.

Learn why most AI projects stall before production and why context, not bigger models, is the missing piece. Discover the pillars of Context Engineering and a practical framework for unifying architecture for continuous context so your AI agents and applications act on fresh info to deliver ROI.

See how banks and financial institutions use real-time data streaming to modernize systems, enable instant payments, reduce fraud, and meet compliance needs. Authored by Kai Waehner, Confluent’s Global Field CTO.