Fluid Thinking

Datacenter Renaissance: part one

With the rise of Kubernetes, enterprise investments in legacy datacenters can become significant economic leverage, by converting legacy IT ops into private clouds. While many enterprises have considered divesting their datacenter infrastructure, and moving primarily or purely into public cloud environments, they may be missing a significant economic opportunity. Kubernetes, along with other automation, provides a unique opportunity to transform cost centers into value-producers, creating efficiencies and accelerating innovation.

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You don't need Kubernetes when...

You can find several unironic blogs describing how static content sites can be delivered on Kubernetes; some will admit that this qualifies as “applied over-engineering”, but they’re just being silly. Clearly, Kubernetes is a great blogging platform. Nonetheless, I don’t blog on Kubernetes.

Let’s face it, you probably don’t need Kubernetes for your startup or enterprise.

A few reasons you’ll never need it:

This post is satire.

Seriously though, my blog doesn’t run on Kubernetes, as far as I know, because hosted static-site solutions are good enough for my needs. They probably use Kubernetes behind the scenes. 🤷‍♂️

If you are responsible for running mission-critical apps on resilient infrastructure, I’d be happy to help you evaluate Kubernetes. When needed, we can talk about the enterprise-scale Kubernetes management solutions I’ve helped develop. (Wait, why didn’t we name them Picard and Riker?!)

Orchestrated Chaos: a Tale of Radical Progress

How my team pivoted a product strategy, delivered a product from idea to alpha in weeks, and launched a new product with mind-boggling speed.

This year in my career has been absolutely amazing. We’ve delivered profound results by learning a new way to produce software that our customers love, quickly and responsively. This story conveys my recollection of this pivotal time in our careers, and the agile software principles that made us successful.

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Data Model Fluidity in Analytics

The world of data, intelligence and analytics perpetually evolves, so too will the data structures we work with. With the rising popularity of data lakes, there’s a steadily increasing need for developers, consultants, and vendors to work with all kinds of data, be it structured, unstructured, or semistructured.

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Continuous Deployment with Python Packages

Streamline your Python development with GitLab CI; automate build, test, and publication of libraries to PyPI package repositories.

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