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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. Check out Dynatrace’s Load testing tool integration.

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Building High-Quality Software

DZone

It sits at the very beginning of the process before the code is written and can save an immense amount of time down the road (of somebody spending tons of time just to get to a dead-end). I really like what one of the smartest people with whom I worked said: “A good design is a design where you can see the code”. Important note.

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Microservices vs. monolithic architecture: Understanding the difference

Dynatrace

Shifting from monolith to microservices makes it easier to test, develop, and release innovative features more rapidly. Data supports this shift from monolithic architecture to microservices approaches. ” In developing critical applications and services , it’s crucial to understand legacy software development.

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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

Use Cases and Requirements At Netflix, our counting use cases include tracking millions of user interactions, monitoring how often specific features or experiences are shown to users, and counting multiple facets of data during A/B test experiments , among others.

Latency 251
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Ready for changes with Hexagonal Architecture

The Netflix TechBlog

Having our core logic isolated means we can easily change data source details without a significant impact or major code rewrites to the codebase. One of the main advantages we also saw in having an app with clear boundaries is our testing strategy?—?the We try to minimize the amount of these tests.

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

The Netflix TechBlog

A key observation was that most of our data scientists had nothing against writing Python code. Data scientists want to retain their freedom to use arbitrary, idiomatic Python code to express their business logic?—?like The steps can be arbitrary Python code. like they would do in a Jupyter notebook.

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What is distributed tracing and why does it matter?

Dynatrace

Especially in dynamic microservices architectures, distributed tracing is essential to monitor, debug, and optimize distributed software architecture, such as microservices. Debug systems, isolate bottlenecks, and resolve code-level performance issues. How does distributed tracing work?