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The following commit(s) were added to refs/heads/main by this push:
new 2955a1fb #1504: Remove Camel 4.10.x docs as its EOL (#1511)
2955a1fb is described below
commit 2955a1fbfc86dc4b15de1433a1f43399af9c51d8
Author: Claus Ibsen <[email protected]>
AuthorDate: Sat Feb 14 07:41:34 2026 +0100
#1504: Remove Camel 4.10.x docs as its EOL (#1511)
* #1504: Remove Camel 4.10.x docs as its EOL
---
antora-playbook-snippets/antora-playbook.yml | 5 -----
content/blog/2025/02/camel-tensorflow-serving/index.md | 8 ++++----
content/blog/2025/04/camel-kserve/index.md | 8 ++++----
content/blog/2025/07/camel-jbang-infra/index.md | 10 +++++-----
4 files changed, 13 insertions(+), 18 deletions(-)
diff --git a/antora-playbook-snippets/antora-playbook.yml
b/antora-playbook-snippets/antora-playbook.yml
index 17ec0962..d98d0f4b 100644
--- a/antora-playbook-snippets/antora-playbook.yml
+++ b/antora-playbook-snippets/antora-playbook.yml
@@ -18,7 +18,6 @@ content:
branches:
- main
- camel-4.14.x
- - camel-4.10.x
- camel-3.22.x
start_paths:
# eip
@@ -32,21 +31,18 @@ content:
branches:
- main
- release-2.9.x
- - release-2.7.x
start_path: docs
- url: https://github.com/apache/camel-kamelets.git
branches:
- main
- 4.14.x
- - 4.10.x
start_path: docs
- url: https://github.com/apache/camel-quarkus.git
branches:
- main
- 3.27.x
- - 3.20.x
start_path: docs
- url: https://github.com/apache/camel-quarkus-examples.git
@@ -65,7 +61,6 @@ content:
branches:
- main
- camel-spring-boot-4.14.x
- - camel-spring-boot-4.10.x
- camel-spring-boot-3.22.x
start_paths:
- components-starter
diff --git a/content/blog/2025/02/camel-tensorflow-serving/index.md
b/content/blog/2025/02/camel-tensorflow-serving/index.md
index cd43ec4a..09817c74 100644
--- a/content/blog/2025/02/camel-tensorflow-serving/index.md
+++ b/content/blog/2025/02/camel-tensorflow-serving/index.md
@@ -13,15 +13,15 @@ As noted in the [previous
article](/blog/2025/02/camel-torchserve/), the recent
[^1]: Camel TorchServe component has been provided since 4.9.
-* [TorchServe component](/components/4.10.x/torchserve-component.html)
-* [TensorFlow Serving
component](/components/4.10.x/tensorflow-serving-component.html)
-* [KServe component](/components/4.10.x/kserve-component.html)
+* [TorchServe component](/components/next/torchserve-component.html)
+* [TensorFlow Serving
component](/components/next/tensorflow-serving-component.html)
+* [KServe component](/components/next/kserve-component.html)
Previously we [wrote about the TorchServe
component](/blog/2025/02/camel-torchserve/), this time we introduce the
TensorFlow Serving component.
## TensorFlow Serving component
-[TensorFlow Serving](https://www.tensorflow.org/tfx/guide/serving) is the
serving feature provided by the popular machine learning framework TensorFlow.
By using the [Camel TensorFlow
Serving](/components/4.10.x/tensorflow-serving-component.html) component, you
can invoke AI models deployed on the TensorFlow Serving model servers through
their [gRPC Client
APIs](https://github.com/tensorflow/serving/blob/2.18.0/tensorflow_serving/apis/prediction_service.proto).
+[TensorFlow Serving](https://www.tensorflow.org/tfx/guide/serving) is the
serving feature provided by the popular machine learning framework TensorFlow.
By using the [Camel TensorFlow
Serving](/components/next/tensorflow-serving-component.html) component, you can
invoke AI models deployed on the TensorFlow Serving model servers through their
[gRPC Client
APIs](https://github.com/tensorflow/serving/blob/2.18.0/tensorflow_serving/apis/prediction_service.proto).
## Preparation
diff --git a/content/blog/2025/04/camel-kserve/index.md
b/content/blog/2025/04/camel-kserve/index.md
index 766fe1c2..e2ed2f25 100644
--- a/content/blog/2025/04/camel-kserve/index.md
+++ b/content/blog/2025/04/camel-kserve/index.md
@@ -13,15 +13,15 @@ In the previous blog posts
([camel-tensorflow-serving](/blog/2025/02/camel-tenso
[^1]: The Camel TorchServe component has been available since version 4.9.
-* [TorchServe component](/components/4.10.x/torchserve-component.html)
-* [TensorFlow Serving
component](/components/4.10.x/tensorflow-serving-component.html)
-* [KServe component](/components/4.10.x/kserve-component.html)
+* [TorchServe component](/components/next/torchserve-component.html)
+* [TensorFlow Serving
component](/components/next/tensorflow-serving-component.html)
+* [KServe component](/components/next/kserve-component.html)
We previously wrote about the [TorchServe](/blog/2025/02/camel-torchserve/)
and [TensorFlow Serving](/blog/2025/02/camel-tensorflow-serving/) components.
This post introduces the KServe component, concluding the series.
## KServe Component
-[KServe](https://kserve.github.io/website/) is a platform for serving AI
models on Kubernetes. KServe defines an API protocol enabling clients to
perform health checks, retrieve metadata, and run inference on model servers.
This KServe API [^2] allows you to interact uniformly with KServe-compliant
model servers. The [Camel KServe](/components/4.10.x/kserve-component.html)
component enables you to request inference from a Camel route to model servers
via the KServe API.
+[KServe](https://kserve.github.io/website/) is a platform for serving AI
models on Kubernetes. KServe defines an API protocol enabling clients to
perform health checks, retrieve metadata, and run inference on model servers.
This KServe API [^2] allows you to interact uniformly with KServe-compliant
model servers. The [Camel KServe](/components/next/kserve-component.html)
component enables you to request inference from a Camel route to model servers
via the KServe API.
[^2]: [KServe Open Inference Protocol
V2](https://kserve.github.io/website/latest/modelserving/data_plane/v2_protocol/)
diff --git a/content/blog/2025/07/camel-jbang-infra/index.md
b/content/blog/2025/07/camel-jbang-infra/index.md
index e0277c80..a0d3c3a7 100644
--- a/content/blog/2025/07/camel-jbang-infra/index.md
+++ b/content/blog/2025/07/camel-jbang-infra/index.md
@@ -81,7 +81,7 @@ $ camel infra run aws s3
Notice how the JSON output provides all the configuration details we need for
the AWS S3 component. There's almost a 1:1 mapping between the infra output and
component configuration.
-let's write some code and create a simple Camel route that uploads files to
S3. For this purpose, we'll use the [Apache Camel AWS S3
component](/components/4.10.x/aws2-s3-component.html), the JSON provided by the
`camel infra run aws s3` command contains all the informations to get started
with the component:
+let's write some code and create a simple Camel route that uploads files to
S3. For this purpose, we'll use the [Apache Camel AWS S3
component](/components/next/aws2-s3-component.html), the JSON provided by the
`camel infra run aws s3` command contains all the informations to get started
with the component:
```java
import org.apache.camel.builder.RouteBuilder;
@@ -148,7 +148,7 @@ $ camel infra run kafka
}
```
-In this case we have a perfect 1:1 match between the properties from the
`infra run` command and the [Apache Camel Kafka
component](/components/4.10.x/kafka-component.html), the only required property
for the Kafka component is `brokers`, let's update the previous route with the
new requirements:
+In this case we have a perfect 1:1 match between the properties from the
`infra run` command and the [Apache Camel Kafka
component](/components/next/kafka-component.html), the only required property
for the Kafka component is `brokers`, let's update the previous route with the
new requirements:
```java
import org.apache.camel.builder.RouteBuilder;
@@ -211,7 +211,7 @@ camel infra run ftp
> Note: For most infra services, Docker images via Testcontainers are executed
> behind the scenes. The infra command exposes most of the components from the
> [Apache Camel test
> infra](https://github.com/apache/camel/tree/main/test-infra). There's no
> magic behind it—we're reusing the same infrastructure that we use to test
> Camel itself. Some services, like the FTP one, don't need Docker; instead,
> an embedded FTP service is spun up.
-Let's update the previous route. Instead of the file component, the [Apache
Camel FTP component](/components/4.10.x/ftp-component.html) has to be used,
using Java DSL there is not an easy 1:1 mapping between the component and the
`infra run ftp` JSON, but we would have 1:1 mapping using YAML DSL.
+Let's update the previous route. Instead of the file component, the [Apache
Camel FTP component](/components/next/ftp-component.html) has to be used, using
Java DSL there is not an easy 1:1 mapping between the component and the `infra
run ftp` JSON, but we would have 1:1 mapping using YAML DSL.
```java
import org.apache.camel.builder.RouteBuilder;
@@ -285,7 +285,7 @@ $ camel infra run qdrant
}
```
-For a plain Camel scenario, the [Apache Camel JMS
component](/components/4.10.x/jms-component.html) configuration is a little bit
cumbersome, [luckily there are
examples](https://github.com/apache/camel-kamelets-examples/tree/main/jbang/artemis)
that shows how this can be done.
+For a plain Camel scenario, the [Apache Camel JMS
component](/components/next/jms-component.html) configuration is a little bit
cumbersome, [luckily there are
examples](https://github.com/apache/camel-kamelets-examples/tree/main/jbang/artemis)
that shows how this can be done.
Let's create an `application.properties` file and add the following
configuration, in this case, we'll use `camel infra run artemis` informations
to fill the `application.properties`
@@ -348,7 +348,7 @@ The `camel run` command has to be updated, to include the
`application.propertie
$ camel run CamelRoute.java application.properties
```
-Finally, let's create the Camel route that consumes from the queue and inserts
data into Qdrant. Of course, before doing that, we need to create embeddings
from the content of the body. This can be easily done with the [Apache Camel
Langchain4j Embeddings
component](/components/4.10.x/langchain4j-embeddings-component.html).
+Finally, let's create the Camel route that consumes from the queue and inserts
data into Qdrant. Of course, before doing that, we need to create embeddings
from the content of the body. This can be easily done with the [Apache Camel
Langchain4j Embeddings
component](/components/next/langchain4j-embeddings-component.html).
Before that, the collection has to be created in Qdrant, let's use Camel to
achieve this:
