Performance Processing Software Architecture Software Engineering 
Dynatrace
MAY 23, 2024
Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data.
Dynatrace
MARCH 3, 2020
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. Performance-as-a-self-service .
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Strategic Tech
MARCH 16, 2021
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. In fact, Software Design EventStorming is like a DSL for designing business processes that translate directly into code.
O'Reilly
FEBRUARY 2, 2020
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. Second, the behavior of AI systems changes over time.
O'Reilly
OCTOBER 19, 2021
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.
The Netflix TechBlog
DECEMBER 3, 2019
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.
The Netflix TechBlog
DECEMBER 3, 2019
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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