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mainly because of mundane reasons related to softwareengineering. The infrastructure should allow them to exercise their freedom as data scientists but it should provide enough guardrails and scaffolding, so they don’t have to worry about softwarearchitecture too much. Metaflow removes this cognitive overhead.
This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like softwareengineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. SoftwareArchitecture. This approach is not novel.
mainly because of mundane reasons related to softwareengineering. The infrastructure should allow them to exercise their freedom as data scientists but it should provide enough guardrails and scaffolding, so they don’t have to worry about softwarearchitecture too much. Metaflow removes this cognitive overhead.
It seems unrealistic wanting the best of both world (speed and reliability) but the field of softwareengineering established during the past decade that speed and reliability can both be achieved. A good engineering organization moves at speed with high reliability. It doesn’t need to be a choice of one over the other.
Defining Aggregate Boundaries Deciding that specific business operations should succeed or fail together sounds like a simple requirements gathering exercise. If you’d like to go through the whole process of modelling domains, shaping the softwarearchitecture, and finding aggregates, join my 2 day workshop at DDD EU in February 2020.
Topic modeling shows that corporations are looking for cloud skills, softwarearchitecture (a more senior skill to aspire to), AI skills, Kubernetes, Java, Python, microservices, security, and Linux. And, let’s face it, everyone wants product managers. All of these learning tools help teach critical thinking.
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