Ken Muse
GitHub, Maven, and Packages
Java makes it surprisingly easy to manage and package complex projects using Apache Maven. One question I’m frequently asked – how does this integrate with GitHub Actions? Turns out that the answer is “surprisingly well!”

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Mythical Development Heroes

Mythical Development Heroes

Last week, we examined common myths about time. Software also has hero myths, which harm developers and limit productivity in astounding ways.

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Mythical Development Time

Mythical Development Time

Time is a precious resource. Did you know it’s also the source of common myths among managers? And those myths can drain productivity (and happiness) from teams…

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Preventing GitHub Actions Injection Attacks
If you can code it, someone will find a way to exploit it ( accidentally or intentionally). Anytime development efforts are involved, it’s important to minimize security risks and bugs. This is also true with GitHub Actions, which allows you to script advanced automation solutions. Because of this, it’s important to understand where injection can occur and how to avoid it.

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The Life of a Commit After Git Squash
Git has some interesting behaviors built into it. For example, it makes it easy to squash a set of commits into a single commit. This creates a very simple history. But what happens if that history that you’re eliminating has a tag applied to it? Does that tag get eliminated? Does it point to the newly squashed commit? Today’s article explores what to expect in that situation … and why.

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Modeling the Hidden Costs of Development
In the last post, we explored the expensive nature of technical debt and bad development practices. Today, we look at how to create financial models that help you to understand your actual costs.

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The Hidden Costs of Bad Development Practices
Bad development practices create debt. The interest on that debt can literally make or break a company, and nobody is immune. With Internet Explorer becoming the latest casualty, it’s a good time to explore the problem.

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Doing DevOps With Databricks
Databricks is a powerful tool for processing data. This is big data, so how do we thing about implementing DevOps practices for these environments?

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Implementing DevOps for Azure Data Factory
Knowing how Azure Data Factory is meant to be used, we can look at how to implement automation to validate and deploy the code from one environment to another.

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Azure Data Factory DevOps
Azure Data Factory provides some great features to make it quick and easy to load and transform data. Did you know it supports DevOps practices?

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