The Apache Camel project pointed a frontier AI model at 19 years of integration code and said: find what we missed. It found 165 bugs for the upcoming 4.22 LTS release. Not cosmetic issues — concurrency races, silent data loss scenarios, security gaps, and edge cases buried deep in 350+ connectors. We fixed all of them — every single one — with a median fix time of 1 day, the same pace this project has maintained for 17 of the last 19 years.
Getting started with the Camel CLI used to mean installing a JDK, then jbang, then finally running jbang camel@apache/camel init for the first time. That friction is gone. install.sh and install.ps1 get the Camel CLI Launcher running on your machine with a single command, no package manager and no separate jbang install required. One-line install On macOS and Linux: curl -fsSL https://camel.apache.org/install.sh | sh On Windows, in PowerShell: irm https://camel.apache.org/install.ps1 | iex Both installers resolve and install the latest published release by default, or a specific version if you request one with --version (install.
Apache Camel and AI AI is a hot topic in the Apache Camel community. When thinking about how to leverage AI in the Apache Camel ecosystem, there are broadly two directions: Incorporating AI services into Apache Camel integrations themselves Utilizing AI services in the development and operation of Apache Camel integrations Direction 1 includes the Apache Camel AI components. Combining the Wanaku MCP router, which has been featured on this blog several times, with Camel also falls into this category.