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Why applying chaos engineering to data-intensive applications matters

Dynatrace

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. This significantly increases event latency.

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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. Performance-as-a-self-service .

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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. When interviewing software engineers, I always provide at-home coding tests which focus on design.

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Cloud Adoption in 2020

O'Reilly

. • More than one-third have adopted site reliability engineering (SRE); slightly less have developed production AI services. Software engineers represent the largest cohort, comprising almost 20% of all respondents (see Figure 1 ). For this audience, SRE’s future is brighter than AI’s, however. Respondent Demographics.

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Uncovering Hidden Business Rules with DDD Aggregates

Strategic Tech

The answer is performance, but more importantly concurrency conflicts. With an understanding of the performance and concurrency implications of enforcing Invariant Business Rules we can ask the business, what would happen if a patient booked two appointments on the same day or a reschedule wasn’t instantly provided?