Apache Karaf Cellar 2.3.0 released

The latest Cellar release (2.2.5) didn’t work with the new Karaf branch and release: 2.3.0.

If the first purpose of Cellar 2.3.0 is to be able to work with Karaf 2.3.x, actually, it’s more than that.

Let’s take a tour in the new Apache Karaf Cellar 2.3.0.

Apache Karaf 2.3.x support

Cellar 2.3.0 is fully compatible with Karaf 2.3.x branch.

Starting from Karaf 2.3.2, Cellar can be install “out of the box”.
If you want to use Cellar with Karaf 2.3.0 or Karaf 2.3.1, in order to avoid some Cellar bootstrap issue, you have to add the following property in etc/config.properties:


org.apache.aries.blueprint.synchronous=true

Upgrade to Hazelcast 2.5

As you may know, Cellar is clustered provision tool powered by Hazelcast.

We did a big jump: from Hazelcast 1.9 to Hazelcast 2.5.

Hazelcast 2.5 brings a lot of bug fixes and interesting new features. You can find more details here: http://www.hazelcast.com/docs/2.5/manual/multi_html/ch18s04.html.

In Cellar, all Hazelcast configuration is performed using an unique file: etc/hazelcast.xml.

Hazelcast 2.5 gives you more properties to configure your cluster, and the behaviors of the cluster events. The default configuration is largely enough for most use cases, but thanks to this Hazelcast version, you have the possibility to perform fine tuning.

More over, some new features are interesting for Cellar, especially:

  • IPv6 support
  • more complete backup support, when a node is disconnected from the cluster
  • better security and encryption support
  • higher tolerancy to connection failures
  • parallel IO support

Cluster groups persistence

In previous Cellar versions, the cluster groups were not store, and relay only on the cluster states. It means that it was possible to loose an existing cluster group if the group didn’t have any node.

Now, each node stores the cluster groups list, and its membership.

Like this, the cluster groups are persistent and we can restart the cluster, we won’t loose the “empty” cluster groups.

Cluster event producers, consumers, handlers status persistence

A Cellar node uses different components to manage cluster events:

  • the producer (one per node) is responsible to broadcast a cluster event to the other nodes
  • the consumer (one per node) receives cluster events and delegates the handling of the event to a handler
  • handlers (one per resource) handles a specific cluster events (features, bundles, etc) and update the node local states

The user has a complete control on producer, consumer, handlers. It means that it can stop or start the node producer, consumer, or handler.

The problem is that the current state of the producer/consumer/handler was not persistent. It means that a restart of the node will reset producer/consumer/handler to the default state (and not the previous one).
To avoid this issue, the producer/consumer/handler state is now persistent on the local node.

Smart synchronization

The synchronization of the different resources supported by Cellar is now better than before. Cellar now checks the local state of the node. Cellar checks a kind of diff between the local state and the state on the cluster. If the states differ, Cellar updates the local state as described on the cluster.

For the config especially, to avoid important CPU consumption, some properties are not considered during the synchronization because they are local to the node (for instance, service.factoryPid).

A new command has been introduced (cluster:sync) to “force” the synchronization of the local node with the cluster. It’s interesting when the node has been disconnected from the cluster, and you want to re-sync as soon as possible.

Improvement on Cellar Cloud support

My friend Achim (Achim Nierbeck) did a great job on the Cellar Cloud support.
First, he fixes some issues that we had on this module.

He gave a great demo during JAX: Integration In the Cloud With Camel, Karaf and Cellar.

Improvement on the cluster:* commands and MBeans

In order to be closer to the Karaf core commands, the cluster:* commands (and MBeans) now provide exactly the same options that you can find in the Karaf core commands.

And more is coming …

The first purpose of Cellar 2.3.0 is to provide a version ready to run on Karaf 2.3.x, and insure the stability. So I postponed some new features and improvements to Cellar 2.3.1.

In the mean time, I also released a new Cellar 2.2.6 release, containing mostly bug fixes (for the ones that still use Karaf 2.2.x with Cellar 2.2.x).

Comments

Post a Comment

Popular posts from this blog

Exposing Apache Karaf configurations with Apache Arrow Flight

Image
This blog post shows how to use Apache Arrow and Arrow Flight in Apache Karaf runtime. The code base is available here: https://github.com/jbonofre/karaf-arrow . Apache Arrow ? Apache Arrow is composed by: The Arrow format (specification). Format implementations with different languages (C, Java, Go, Rust, ...). Extra subprojects like Flight, Flight SQL, ADBC, nanoarrow, ... Apache Arrow format is a in-memory columnar format, super efficient for scanning and iterating a large chunks of data. In traditional memory buffer, we focus on "row". Apache Arrow format "groups" data per column, which is much more efficient on modern CPUs/GPUs. The Apache Arrow format is basically a specification. We have several implementations for this specification: C C++ C# Go Java Python Ruby Rust As the purpose of this blog post is to show Apache Arrow in Apache Karaf, we will use Arrow Java. In addition, Apache Arrow also provides several...
Read more

Getting started with Apache Karaf Minho

Image
Apache Karaf Minho Apache Karaf Minho is a new runtime, completely created from scratch. The objectives are: super easy to use and run ligtning fast, including GraalVM support Kubernetes compliant to be easily used on the cloud helping to optimize cloud costs by supporting applications colocation providing turnkey services allowing you to create Minho applications in a minute Minho is composed by: minho-boot is the core of Minho. It contains the runtime launcher and the core services (service registry, lifecycle service, configuration service, ...). minho-* services provided additional functionnalities in the runtime. You can use these services to create your own services, it's also where you will find the services managing sepcific kind of applications, allowing colocation. minho-tooling optionally provide convenient tools to create your own runtime. It includes minho-maven-plugin for instance. In this blog post, we will take a quick tour on A...
Read more

Using Apache Karaf with Kubernetes

Image
In a previous blog post ( http://blog.nanthrax.net/?p=893 ), I introduced the “new” docker support in Karaf and the use of Karaf static distribution. This post follows the previous one by illustrating how to use Karaf docker image with a Kubernetes cluster. Preparing Karaf static docker image As in the previous blog post, we are preparing a Karaf static distribution based docker image. For this blog post, I’m using the example provided in Karaf: https://github.com/apache/karaf/tree/master/examples/karaf-docker-example/karaf-docker-example-static-dist . I’m just building the distribution as usual: karaf-docker-example-static-dist$ mvn clean install Preparing kubernetes testing cluster For this blog, I’m using a minikube installed locally. The installation is pretty simple: Download minikube from https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64 Rename minikube-linux-amd64 as minikube Copy minikube in your path, for instance /us...
Read more