Dette er CodeArts blog. Vi deler thought-leadership og tekniske tips og tricks - men som regel på engelsk.
Adhering to Consent with Cookie Information for Episerver
In the EU the past year has added even more rules and regulations to which cookies can be set, which data can be collected and which consents are needed for it. While it may not be tricky to add a basic consent box, adding one that adhere to all the proper legislation and then follow the consents given can be a bit more challenging. In this post I take a deep dive into how Cookie Information's solution together with their Connector for Episerver can make it easier - and faster to accomplish.
Thoughts on the Episerver/Optimizely Acquisition
When one of the market leaders in digital experience / content management / e-commerce acquires the market leader in Optimization and Experimentation - great things can be expected. But how will it differ from the optimization techniques used by Episerver customers today? Here are my thoughts.
Experimenting with Wikipedia topics for Content
Automatically tagging your content with topics from a known, well described topic base like Wikipedia can have many cool uses. You can organize your content, suggesting keywords and outbound links, not to mention that you can build up interest profiles of your visitors. These interest profiles can the be used to suggest appropriate content and keep your visitors engaged. Inspired by Episerver Content Intelligence and a couple of earlier projects I've done in the past, I decided to perform an experiment to see how far I could get with a DIY approach as opposed to the traditional cloud-based NLP/AI.
Powerslice: Identify unused blocks
Powerslice might have a few years on it's back, but it's still a great editorial tool, when you are working with large amounts of content and have access to Episerver Find. Here's an example of a recent slice I made that let's editors easily identify unused blocks.
Auto Tagging Using Search
You don't always have to go the full AI route to get AI like results. In this blog post I'll describe an approach I've used several times (and for multiple purposes) with pretty decent results. Instead of classification algorithms, deep learning or neural networks I'll just simply query my favorite search engine.
Storage Performance Aftermath - ElasticSearch Joins the Fight
In 3 previous blog posts I compared various azure storage technologies with regards to performance and scalability in typical web usage scenarios. I was actually done with the series, but with all that interesting data, I decided to throw my current favorite search/storage/no-sql technology into the mix to get an idea about how it all compares. So - ElasticSearch enters the competition!
Azure Storage Performance Showdown (Post 3)
This is the 3rd post in my Azure Storage Performance comparison. So far we've examined the typical scenario of storing/retrieving data that most dynamic websites of today deal with. In this post, we'll take a closer look at Update and Delete - and finally review the financial aspects.
Azure Storage Performance Showdown (Post 1)
Almost every project has some data you want to persist, then read, search through, update and eventually delete. With Azure there are loads of great possibilities - for example Blob Storage, Table Storage, CosmosDb, SQL Azure. I've decided to do some simple and fairly naive tests to compare these for some typical usage scenarios and see how they perform.