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Stop empowering people – End disempowerment!


In the last two posts I’ve discussed some problems with of self-organizing teams and highlighted the need to be clearer about what is actually meant when talking of, that is naming, self-organizing teams. At a minimum the labels need clear definition (I suggested some definitions and I hope someone knows some better ones.) I went further and I called for ...

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Spark 101: What Is It, What It Does, and Why It Matters


Recently, a new name has entered many of the conversations about big data. Some people see the popular newcomer Apache Spark™ as a more accessible and more powerful replacement for Hadoop, the original technology of choice for big data. Others recognize Spark as a powerful complement to Hadoop and other technologies, with its own set of strengths, quirks and limitations. ...

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Running OpenShift Origin on Windows


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


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


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


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


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


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


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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