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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. This process can also be used to track the provenance of increments.

Latency 251
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Data privacy by design: How an observability platform protects data security

Dynatrace

Creating an ecosystem that facilitates data security and data privacy by design can be difficult, but it’s critical to securing information. When organizations focus on data privacy by design, they build security considerations into cloud systems upfront rather than as a bolt-on consideration.

Design 246
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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.

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Legacy Architecture Modernisation With Strategic Domain-Driven Design

Strategic Tech

Before jumping into either of those scenarios, have a look at what Strategic Domain-Driven Design can offer you. It’s got a selection of free tools you can use for defining your technology strategy, shaping your architectural boundaries, and organising your teams. What architecture will be optimal for enabling that business vision?

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The Relationship Between Software Architecture And Business Models (and more)

Strategic Tech

If every significant architecture decision has business consequences, then knowing the business model and which trade-offs to choose is maybe the most important skill of architects. But what is the actual relationship between a business model and a software architecture? A software system is a model of a domain.

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Building High-Quality Software

DZone

It’s much better to build your process around quality checks than retrofit these checks into the existent process. NIST did classic research to show that catching bugs at the beginning of the development process could be more than ten times cheaper than if a bug reaches production. There are so many benefits. A side note.

Software 245
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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. By design, Metaflow is a deceptively simple Python library: Data scientists can structure their workflow as a Directed Acyclic Graph of steps, as depicted above.