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Microservices Done Right: Avoid the Antipatterns! Part 1

Accenture

Microservices architecture has become popular over the last several years. Many organizations have seen significant improvements in critical metrics such as time to market, quality, and productivity as a result of implementing microservices. Recently, however, there has been a noticeable backlash against microservices.

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Supporting Diverse ML Systems at Netflix

Netflix Tech

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems.

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

Netflix Tech

by David Berg , Ravi Kiran Chirravuri , Romain Cledat , Savin Goyal , Ferras Hamad , Ville Tuulos tl;dr Metaflow is now open-source! Get started at metaflow.org. Netflix applies data science to hundreds of use cases across the company, including optimizing content delivery and video encoding.

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

Netflix Tech

by David Berg , Ravi Kiran Chirravuri , Romain Cledat , Savin Goyal , Ferras Hamad , Ville Tuulos tl;dr Metaflow is now open-source! Get started at metaflow.org. Netflix applies data science to hundreds of use cases across the company, including optimizing content delivery and video encoding.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly Media - Ideas

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. The new category is often called MLOps. However, the concept is quite abstract.

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The Good and the Bad of Apache Kafka Streaming Platform

Altexsoft

Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time. It offers high throughput, low latency, and scalability that meets the requirements of Big Data. Plus the name sounded cool for an open-source project.”. What is Kafka?

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Scylla and Confluent Integration for IoT Deployments

Confluent

This growth depends greatly on the overall reliability and scalability of IoT deployments. Most IoT-based applications (both B2C and B2B) are typically built in the cloud as microservices and have similar characteristics. The internet is not just connecting people around the world. trillion in 2017 and anticipated to grow to over $6.5

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