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Nurturing Design in Your Software Engineering Culture

Strategic Tech

There are a few qualities that differentiate average from high performing software engineering organisations. I believe that attitude towards the design of code and architecture is one of them. Martin Fowler argues that internal quality of a software system enables new features and improvements to be delivered more sustainably.

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Up your quality and agility factor – using automation to build “performance-as-a-self-service”

Dynatrace

For software engineering teams, this demand means not only delivering new features faster but ensuring quality, performance, and scalability too. One way to apply improvements is transforming the way application performance engineering and testing is done. Get started today! .

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AI meets operations

O'Reilly

Source code is relatively less important compared to typical applications; the training data is what determines how the model behaves, and the training process is all about tweaking parameters in the application so that it delivers correct results most of the time. How do we test software whose behavior is fundamentally probabilistic?

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MLOps and DevOps: Why Data Makes It Different

O'Reilly

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. All ML projects are software projects.

DevOps 138
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From Domains to Value Streams

Strategic Tech

The 2010s were a turning-point in the history of software engineering. or “How do software architecture, domains, Conway’s Law, Team Topologies, and value streams all fit together?”. Team Flow Event Storming is also a great technique for mapping out and visualizing value stream-like processes collaboratively.

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Open-Sourcing Metaflow, a Human-Centric Framework for Data Science

The Netflix TechBlog

mainly because of mundane reasons related to software engineering. We heard many stories about difficulties related to data access and basic data processing. While a typical machine learning workflow running on Metaflow touches only a small shard of this warehouse, it can still process terabytes of data.

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O’Reilly serverless survey 2019: Concerns, what works, and what to expect

O'Reilly

We suspect this points to a general drift toward software teams taking more responsibility for infrastructure, and increasingly, enabled by serverless options. As noted earlier, the majority of survey respondents are software engineers. Industries of survey respondents. Organization size of survey respondents.