SI4T-Solr 1.2 for Web 8

Looking at code you wrote three years ago can sometimes be a confronting experience. In case of the code I wrote for SI4T, this was no different. After you go through the six stages of debugging and cringe at the aestestics of the code base, the only thing you can do is rewrite the stuff with the knowledge of today and be solaced by the fact that your code is actually used in production environments and not breaking too much.

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Web 8, SI4T and Storage Extensions

The release of SDL Web 8 has seen the biggest overhaul of the Content Delivery stack since Tridion 2011 and much of it has been applauded much, as the new Micro Services architecture and with it the ability to scale, deploy and be distributed in general, gives many more architectural options than just having an API in your web application connecting you to a database.

Building this while guaranteeing backward compatibility with the Tridion 2011/2013 CD stack is more than a major task and I for one am happy to see that that feat was pulled off really well. That is, unless you have overridden the default DAOFactory classes in your Deployer Storage Extensions, as is the case with the SI4T Storage Extensions. When testing SI4T with Web 8, it turned out that loading of the SI4T Storage Extension did not work in every scenario. This has to do with the subtler points of Spring Bean Class loading.

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Building and automating a scaled out Fredhopper/SmartTarget environment

While designing and building a Fredhopper/SmartTarget enterprise environment recently, a couple of interesting requirements came up. The first requirement, these days quite often asked for when building infrastructures, was that every Fredhopper component needed to be to be automatically deployed, configured and run. The second hard requirement was that in a production environment being under constant high load and being distributed across multiple data centres, the Fredhopper Index servers need to be in sync and highly available in each data centre, while having failover mechanisms causing the least amount of disruption time. After a lot of headache, trialling, erring and creating a mountain of broken Fredhopper instances in the process, we finally managed to meet requirements and this post shows the how of it.
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