In this blogpost, we’ll walk through a modern approach to developing Apache Camel applications. We’ll build a distributed log analyzer that automatically detects errors and uses an LLM for root cause analysis. Along the way, we’ll explore how tools like Camel JBang and Kaoto make development incredibly productive, and why Apache Camel’s YAML DSL is a perfect match for LLM-assisted development. Why Apache Camel? Before diving into the implementation, let’s address why Apache Camel is an excellent choice for this kind of system.

Continue reading ❯

AIUSECASES

The integration of Large Language Models (LLMs) into enterprise applications has become increasingly important. Whether you’re building intelligent document processing pipelines, automated customer support systems, or data privacy solutions, the ability to seamlessly connect your integration flows with AI capabilities is essential. Apache Camel 4.17 introduces the new camel-openai component, providing native integration with OpenAI and OpenAI-compatible APIs for chat completion. In this post, we’ll explore the component’s features and demonstrate a practical use case: Personal Identifiable Information (PII) redaction using structured output.

Continue reading ❯

AI

It’s the time of the year when we take a look back at 2025, and compile a brief summary (by numbers) of the Apache Camel project(s). You can find previous year 2024 numbers here. Camel 2025 in Numbers Number of Camel Core / Camel Spring Boot releases in 2025: 25 Number of Camel Quarkus releases in 2025: 18 Number of Camel Karavan releases in 2025: 3 Number of Camel K releases in 2025: 5

Continue reading ❯

ROADMAP