Category: Usefull Links

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Continuous Delivery Pipeline for Kubernetes using Spinnaker

Kubernetes is now the de-facto standard for container orchestration. With more and more organizations adopting Kubernetes, it is essential that we get our fundamental ops-infra in place before any migration. This post will focus on pushing out new releases of the application to our Kubernetes cluster i.e. Continuous Delivery Source: Continuous Delivery Pipeline for Kubernetes using Spinnaker Always interesting to...

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Build a Federation of Multiple Kubernetes Clusters With Kubefed V2

I have found it really very interesting and I believe that it will be extremely useful. A step-by-step guide to building a Kubernetes federation for managing multiple regions’ clusters with KubeFed Source: Build a Federation of Multiple Kubernetes Clusters With Kubefed V2

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Agile data science: Evaluation and baseline model

A different point of view on how the idea of Agile is applied also in the process of understanding and evolution of AI models Agile data science: Evaluation and baseline model Infrastructure that enables rapid prototyping for model development Source: Agile data science: Evaluation and baseline model

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Machine Learning and Real-Time Analytics in Apache Kafka Applications

This article is very useful because it discuss and compare two different options for AI model deployment: model servers with remote procedure calls (RPCs), and natively embedding models into Kafka client applications. This example uses TensorFlow, but the underlying principles are also valid for other machine learning/deep learning frameworks or products, such as H2O.ai, Deeplearning4j, Google’s Cloud Machine Learning Engine,...

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Event Architecture

Useful event-sourcing Pattern!

A very interesting article that I find very useful! Here are shared some of the common producer models, which show how to transform a classic architecture to an Event Sourcing model. Below is the link to the complete article! In part one, we learned about how at Nordstrom we’ve been exploring and implementing event-sourcing as an architectural pattern. In part…...

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Evolutions of Big Data Analisys for streaming data and machine learning solutions

The ecosystem of Big Data analysis has evolved in recent years with new databases, streaming data and machine learning solutions which  require more than the classic deployment model. The revolution of Container technologies try to cover these new objectives and there are possible to accomplish in the organizations. Below 2 articles where you can start thinking about what is most...

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How Booking.com Uses Kubernetes for Machine Learning

Recommended reading: Sahil Dua explained how Booking.com has been able to scale machine learning (ML) models for recommending destinations and accommodation to their customers using Kubernetes, at QCon London conference. In particular, he stressed how Kubernetes elasticity and resource starvation avoidance on containers helps them run computationally (and data) intensive, hard to parallelize, machine learning models. Source: How Booking.com Uses...

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Emscripting a C library to Wasm

From the blog of Google Developers an very interesting article on how to run C code in a modern browser via Emscripten and WebAssembly   Checkout it on Emscripting a C library to Wasm  |  Web  |  Google Developers Do you know what Emscripting is? just quote the official site Emscripten is an Open Source LLVM to JavaScript compiler. Using...