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new a1c641dd docs(blog): Hawtio AI: Utilizing AI in the Operational Phase
of Camel Integrations (#1691)
a1c641dd is described below
commit a1c641dd861578e3997baab797985a37a1293bb8
Author: Tadayoshi Sato <[email protected]>
AuthorDate: Wed Jul 8 14:57:43 2026 +0900
docs(blog): Hawtio AI: Utilizing AI in the Operational Phase of Camel
Integrations (#1691)
* docs(blog): Hawtio AI: Utilizing AI in the Operational Phase of Camel
Integrations
* docs(blog): Hawtio AI - add mention to Camel CLI and TUI
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+---
+title: "Hawtio AI: Utilizing AI in the Operational Phase of Camel Integrations"
+date: 2026-07-10
+draft: false
+authors: [tadayosi]
+categories: ["AI", "Tooling"]
+keywords: ["apache camel", "hawtio", "AI", "management console",
"diagnostics", "monitoring"]
+preview: "Hawtio AI is a new plugin that extends Hawtio's management and
diagnostics console with AI-powered capabilities, enabling intelligent
diagnosis of Camel application MBeans and laying the groundwork for automated
operations in the operational phase of Camel integrations."
+---
+
+## 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:
+
+1. Incorporating AI services into Apache Camel integrations themselves
+2. Utilizing AI services in the development and operation of Apache Camel
integrations
+
+Direction 1 includes the [Apache Camel AI
components](/components/4.18.x/ai-summary.html). Combining the [Wanaku MCP
router](https://www.wanaku.ai/), which has been featured on this blog several
times, with Camel also falls into this category.
+
+Direction 2, on the other hand, applies AI at a completely different phase
from direction 1. [Camel CLI](/manual/camel-jbang.html) and [Camel
TUI](/manual/camel-jbang-tui.html) are already integrated with MCP (Model
Context Protocol), enabling vibe coding for Camel applications using these
tools. In addition, an ambitious AI coding assistant tool called
[Camel-Kit](https://github.com/luigidemasi/camel-kit) is currently under
development. [Kaoto](https://kaoto.io/) would also be a candida [...]
+
+[Hawtio](https://hawt.io/) is the de-facto tool and console for managing and
diagnosing Camel applications. Within the Camel ecosystem, it sits in a unique
position to apply AI at this operational phase.
+
+## What is Hawtio AI?
+
+[Hawtio AI](https://github.com/hawtio/hawtio-ai-plugin), currently under
development by the Hawtio team, is a subproject that extends Hawtio's
traditional JMX over HTTP management and diagnostics capabilities with AI.
+
+Hawtio AI is implemented as one of Hawtio's plugins. Users can enable Hawtio
AI functionality in their Hawtio console by opting in to the dependency as
follows:
+
+```xml
+<dependency>
+ <groupId>io.hawt.ai</groupId>
+ <artifactId>hawtio-ai-plugin</artifactId>
+ <version>0.2.2</version>
+</dependency>
+```
+
+The Hawtio AI plugin is currently at version 0.2 and is still at the MVP
stage. I am writing this blog post to give people an early look at the idea of
using AI for managing and diagnosing Camel applications, along with Hawtio AI
itself.
+
+## Design Overview
+
+The core design of the Hawtio AI plugin is a LangChain.js-based AI agent
running in a React frontend. You can switch between AI models provided by
various providers (including local models) from the preferences panel.
+
+
+
+It supports one AI model connection per Hawtio session. Application
information, such as Camel context health and route statistics, can be
retrieved via Jolokia/JMX and sent to the model to perform intelligent
operations.
+
+> **NOTE:** As described later, application data is never sent to an AI model
without the user explicitly pressing the submit button.
+
+While the set of AI models supported at this point is limited, we are
considering future support for connections to models hosted on private clouds
and to MCP servers.
+
+## Diagnosis
+
+The Hawtio AI plugin is still at the MVP stage, and the only implemented
feature is "Diagnosis."
+However, this single feature should be enough to give you a sense of Hawtio
AI's potential.
+
+Below is a screenshot of Hawtio web console attached to a `TestApp` Camel
Spring Boot application with two routes (`cron` and `simple`).
+
+
+
+In the left-hand menu, a new view named "JMX AI" has been added at the bottom
alongside Hawtio's built-in views. This is the view provided by the Hawtio AI
plugin.
+
+The JMX AI view is a replica of the existing JMX view, but with two new
additions: a "Chat" button in the upper right of the view, and a "Diagnose"
button in the Attributes tab.
+
+
+
+This "Diagnose" button provides the "diagnosis" feature. It passes the
attribute data of the currently displayed node (MBean) to the AI model and asks
whether there are any potential anomalies or issues.
+
+The diagnosis result is displayed as a response from the AI in a chat view
that opens from the right edge, as shown below. You can also continue chatting
with the AI about the diagnosis result in this chat view.
+
+
+
+By selecting a different MBean node from the JMX tree on the left, you can
diagnose the application's status from various perspectives.
+
+## Ideas Towards Version 1.0
+
+The "Diagnosis" feature is the most general-purpose feature for showcasing
Hawtio AI's potential.
+
+As we work toward completing Hawtio AI as version 1.0, we plan to implement
the following additional ideas on top of this foundational base:
+
+- Implementing one-shot prompting features tailored to specific use cases
+- Registering the JMX workspace and Jolokia interface as tools
+- Extending the Hawtio core SPI to embed functionality into existing plugin
views
+- Establishing security and AI permission controls
+
+### Implementing One-Shot Prompting Features Tailored to Specific Use Cases
+
+AI for application management and diagnostics is most powerful when focused on
specific use cases. We will implement a set of features that allow one-button
invocations of operations targeting specific MBeans for runtimes/frameworks
including Camel, with tailored system prompts. This will also include
automation capabilities that perform actual management operations via MBean
invocations.
+
+### Registering the JMX Workspace and Jolokia Interface as Tools
+
+AI agents can extend their general intelligence through tools. When rendering
the JMX MBean tree, Hawtio already holds the full application's MBean
information in its workspace, and the agent can access this information without
needing to query the server runtime again. All that is needed is to register
the workspace itself as a tool with the AI model.
+
+Furthermore, if the agent determines that it needs to invoke some MBean
operation on the server during an interaction with the user, the user should be
able to authorize the agent to do so. Registering Hawtio's existing Jolokia
interface as a tool with the AI model is all it takes.
+
+We have already developed the [Jolokia MCP
Server](https://github.com/jolokia/jolokia-mcp-server), but for Hawtio AI's
purposes, there is no need to introduce a new server layer, as exposing the
workspace and Jolokia interface as tools within the frontend is sufficient.
+
+### Extending the Hawtio Core SPI to Embed Functionality into Existing Plugin
Views
+
+Hawtio AI's JMX AI is provided as a separate view, but it would be more
convenient if the AI plugin could inject AI capabilities directly into existing
plugin views. Achieving this requires extending the current Hawtio core SPI.
+
+### Establishing Security and AI Permission Controls
+
+Finally, to make AI usable in enterprise environments, sufficient security and
permission control mechanisms are essential. In particular, it is important not
to allow the AI agent to send data or execute operations unintentionally. A
mechanism similar to RBAC that controls access and execution permissions at the
MBean level, down to individual attributes and operations, is needed. The
defaults should also be safe and restrictive.
+
+## Next Steps
+
+Hawtio, including the Hawtio AI plugin, is an open source project licensed
under Apache 2.0.
+
+The Hawtio AI plugin is under active development in this project. Opinions,
ideas, feedback, and contributions are very welcome.
+
+- <https://github.com/hawtio/hawtio-ai-plugin>
+
+If you are new to Hawtio, start here:
+
+- [hawt.io - Get Started](https://hawt.io/docs/get-started.html)
+
+If you are interested in contributing to Hawtio itself, please visit this
project:
+
+- <https://github.com/hawtio/hawtio>
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