It is a happy day here at Ortus Solutions as we bring you yet again a plethora of releases of all our major open source libraries. This is the culmination of over 6 months of hard work to get you updates for all of our major open source libraries and even a new library, TestBox. You can read more about our releases in our engineering blog:
Much work and dedication has gone by these past few months in order to bring you the final release of TestBox v1.0.0. For those of you that do not know what TestBox is, TestBox is a next generation testing framework for ColdFusion that is based on BDD (Behavior Driven Development) for providing a clean obvious syntax for writing tests. It contains not only a testing framework,...
We are so excited to bring you our 1.0.0 Release Candidate of TestBox. Much work and dedication has gone through this release and a final release is imminent. For those of you that do not know what TestBox is, TestBox is a next generation testing framework for ColdFusion that is based on BDD (Behavior Driven Development) for providing ...
We are very excited to partner up with the great folks at Couchbase to bring you an awesome webinar on November 19th, 2013. Myself, Brad and Tug will be presenting on the amazing features of the Couchbase NoSQL server and how it can be leveraged for scalability with CFML applications. Here is a synopsis of the webinar:
Scaling ColdFusion (CFML) Applications with Couchbas...
We are so pleased to bring you another addition to our Ortus product lineup: TestBox. TestBox is a next generation testing framework for ColdFusion that is based on BDD (Behavior Driven Development) for providing a clean obvious syntax for writing tests. It contains not only a testing fr...
We are excited to be part of CFCamp 2013 for the third year now. This is truly an awesome conference with over 26 different sessions, amazing speakers and of course it is hosted in one of my favorite cities in the world, Munich! So head over to their ...
So far in this series, we’ve introduced you to Couchbase Server and showed you how to set up a cache cluster. Then we covered using that cluster as an ORM Secondary Cache as well as connecting to it through our open source CacheBox Provider. Today, we’re going to show how to get the deepest integration yet for those of you running Railo’s Open Source CFML server via our upcoming Ortus Railo Couchbase Extension. Our extension will allow you to leverage Couchbase directly from Railo as a caching engine, but also as a storage container for session or even client scope variables. The extension also introduces several native ColdFusion functions that will allow you to interact with Couchbase directly from CFML code for your NoSQL or Caching needs. So let's get to it and start off by introducing our extension.
CFML has a set of cache-related functions that allow you to set and retrieve objects from an application cache. Adobe ColdFusion uses EHCache, an in-process Java caching solution. Railo, the open source CFML engine, also can use EHCache, but they went a step further and introduced a pluggable cache architecture that allows you to write a Java adapter class that will connect to any underlying caching engine; much how CacheBox works but right into the engine.
Railo also allows these caches to be used for session or client storage as an added bonus. This is extremely handy if you have a farm of load balanced web servers and you want to use session storage without using session replication or enabling sticky sessions on your load balancer. By configuring your session storage to use an out-of-process distributed cache you are allowing your site to scale out easily since the application servers won't be taxed with storing session data for all your users in their in-process heap. It will also allow for your session information to survive server restarts and provide a much better user experience for your application. Lastly, it can allow your load balancers to run round-robin algorithms instead of the typical sticky session approach. This will bring a much more stable cluster farm where load can be distributed evenly and without user segregation.
Couchbase is not only an amazing caching solution but also a NoSQL database, as we have seen throughout our series. Having the capabilities to interact with it easily via CFML was our next step of introducing several native CFML functions thanks to Railo's extension architecture. This is where we come in. We here at Ortus Solutions have developed a commercial extension for Railo Server that adds Couchbase support for the native cache functions, as well as query/template/function caches, session/client storage and native CFML functions for NoSQL integration. This extension is built on top of the Couchbase Java SDK and truly gives you low-level access to the power of Couchbase Server.
In our previous posts, we covered how to get Couchbase installed and set up your first cluster. Then we showed you how to use Couchbase for an ORM secondary cache. Now it’s time to showcase our Couchbase CacheBox provider that we released just a few days ago. This is a CFML provider that uses the Java SDK for Couchbase and lets you create one or more named caches in CacheBox that connects to one or more buckets in a Couchbase cluster. Once you connect up CacheBox, you can seamlessly also store ColdBox Platform cached events/views in Couchbase along with anything else you use the CacheBox API for. So basically you have full Couchbase storage capabilities from ColdBox and non-ColdBox applications. Let’s get started!
ForgeBox and Code
The CacheBox Couchbase provider does not ship with the ColdBox core, but can be found in our community repository; ForgeBox. You can use this provider in any installation of CacheBox that is bundled with the ColdBox Platform, or in a standalone installation. Here’s some handy links for you:
- Official ForgeBox Entry - http://www.coldbox.org/forgebox/view/Couchbase-Provider
- GitHub Repository - https://github.com/ColdBox/cachebox-couchbase
- Documentation - http://wiki.coldbox.org/wiki/CacheBox-Couchbase.cfm
In our first two posts, we covered how to install Couchbase server and get a cluster up and running. In this post we are going to put that cluster of yours to use and show you how to configure it as an ORM secondary cache provider for your ColdFusion applications.
Please remember that the installation instructions are pretty much the same for Adobe ColdFusion and Railo CFML.
If your “cluster” is still just a single server, don’t worry. The size and configuration of a Couchbase cluster is seamlessly invisible to the connecting client. Meaning you can grow and scale your cluster without changing your setup/connection code.
At this point in time, there is no Couchbase-specific library for a Hibernate secondary cache, but luckily for us, Couchbase is compatible with the memcached protocol, so we can use the memcached library. The only drawback is that if you are connecting on the standard port of 11211 to Couchbase, the library will only be able to connect to the “default” bucket. To use a named bucket for your ORM Secondary cache, you will need to assign the Couchbase bucket you create to a unique port number with NO password when you create it in Couchbase Administrator application.
This is our second part of our Couchbase and CFML series that we started last week. In our first post, “Installation and Introduction to Couchbase” we talked about Couchbase Server, how to install it, and how it can help create a fast and scalable caching layer for your applications. Today we’re going to talk about setting up a Couchbase cluster and look at our first use for it: as a Hibernate secondary cache for ColdFusion ORM.
In our previous post we set up a very simple cluster of only one node. Let’s look at how Couchbase lets you expand your cluster horizontally as your needs increase. A cluster can have as many nodes as you want, seriously! All nodes in a cluster will be exact copies of each other in regards to their buckets and even their configuration. When you set up the first node, you will choose how much RAM you want for each node in that cluster to allocate itself. You can only add a new node to the cluster if it has enough RAM to allow for the node size specified in the cluster at setup. Therefore, the total amount of RAM in the entire cluster will be the node size times the number of nodes.