Last updated March 24, 2023

This article contains my collection of learning resources and reading material to help me grow and stay up to date on industry topics.

With the adoption of new techniques comes the inevitable and inadvertent introduction of bad habits. Agile transformation is no exception. The countless frameworks, certifications, and literature (including articles like this one) describe a wide landscape with varying practices and differing opinions. This lack of clarity makes it hard for teams without practical experience to adopt Agile methods effectively and easy to misinterpret best practices. In this article, I describe some of the most common Agile misconceptions, why they are harmful to teams, and what you can do to recognize and fix them.

This post provides a step-by-step guide to creating a company-managed Scrum project in Jira. Jira supports multiple project types. I'll briefly discuss the differences between Scrum and Kanban and why you might select a particular project template.

This past week, I had a discussion with a student team about microservices. This is a topic I've wanted to write about for a while and given the immediate relevance to this team, I finally made it a priority.

The microservices architecture is a popular and growing trend in many technology organizations today. But its implementation is often met with unsurmountable challenges by unprepared teams. This article discusses some of the challenges of microservices and how to overcome them.

With the recent introduction of Mermaid support in GitHub Markdown, I wanted to explore Mermaid in some more detail. In this article I'll walk through my exploration of diagrams as code with Mermaid and show some detailed examples of practical Mermaid diagrams.

Regardless of discipline, many fields need to be able to process, manipulate, and visualize data. This article introduces the basics of plotting data with Python using Matplotlib. View the notebook on Github or experiment with it yourself on Google Colab.

This article discusses some of the factors that contribute to project success and what you as an individual team member can do to influence that success. When I began writing this article, I intended it as a guide for my undergraduate senior design teams. As such, some of the examples below are aimed at that context.

As teams mature their DevOps capabilities one of the questions that inevitably arises is this: How do we achieve traceability between deployed versions and source code? Because at some point or another, we will encounter an issue in production that doesn't seem to make sense given the code the engineering team has on hand. The goal to know, with certainty, what version of the source code aligns with the deployed system is instrumental to enabling the team to solve the right problem.