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Running OpenShift Origin on Windows

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OpenShift is the most interesting PaaS offering these days for me. Not only because it is part of the Red Hat family of products, but because it holds everything I expect from a modern PaaS. It supports image based deployments (with Docker-Images), abstracts operational complexity (e.g. networking, storage and health checks) and greatly supports DevOps with an integrated tooling stack. ...

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Writing an Event-Sourced CQRS Read Model

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Discussions about event sourcing and CQRS seem to usually focus on the overall system architecture or various flavors of domain-driven design in CQRS context. However, the read models are often neglected, even though there are some interesting considerations on this side as well. In this post we’re going to present a sample implementation of populating a view model by consuming ...

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The GO Portfolio Roadmap

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Summary Products don’t exist in isolation. Instead, they are often related to other products, which they help sell or they share features and components with. Think, for instance, of the Microsoft Office suite or the iPod product line. If your product is part of a family, then you will benefit from a portfolio roadmap, a plan that shows how the ...

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The (slightly tongue in cheek) role of the database administrator

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As a former DBA, I find a disturbing trend toward a value proposition that is almost nonexistent among a recent crop of database administrators. Maybe having some background and/or working with other stellar DBAs in the past has spoiled me, but here’s the workflow I’ve find more and more common. scenario – production application has slowed down for a few ...

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Docker Machine, Compose & Swarm: How They Work Together

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During the past year, Docker has been hard at work creating simple to use tools to set up container hosts (Machine), manage multiple containers linked together (Compose), and treating your container hosts as a cluster (Swarm). Even though they are meant to be simple, these tools are very powerful, and they require some planning before you run off and deploy ...

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Help Professional Developers Survive

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A developer’s life is not simple. Developers need to contend with adding new software features, quickly, from different customers, while keeping up with technology. And do some support work in the middle. And, also meetings. However, the road to improvement through this complex situation can be a strange one. It sometimes starts with these suggestions, heard around in recent retrospectives: We need ...

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SparkR: Add new column to data frame by concatenating other columns

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Continuing with my exploration of the Land Registry open data set using SparkR I wanted to see which road in the UK has had the most property sales over the last 20 years. To recap, this is what the data frame looks like: ./spark-1.5.0-bin-hadoop2.6/bin/sparkR --packages com.databricks:spark-csv_2.11:1.2.0   > sales <- read.df(sqlContext, "pp-complete.csv", "com.databricks.spark.csv", header="false")   > head(sales) C0 C1 C2 ...

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Resource versioning with Spring MVC

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When serving static resources, it is common practice to append some kind of version information to the resource URL. This allows the browser to cache resources for an unlimited time. Whenever the content of the resource is changed, the version information in the URL is changed too. The updated URL forces the client browser to discard the cached resource and ...

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Scala typeclass explained: Implement a String.read function

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In this short article I’d like to explain how you can use the typeclass pattern in Scala to implement adhoc polymorphism. We won’t go into too much theoretical details in this article, the main thing I want to show you is how easy is really is to create a flexible extensible model without tying your domain model to specific implementation ...

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