Using HAProxy as an API Gateway, Part 1

An API gateway is a layer of software between the frontend UI and backend services that routes requests intelligently. Read on to learn how HAProxy Enterprise Edition excels as an API gateway.
“Danger! Avalanche Area” is a sign you’ll see when you drive through some parts of Colorado. Looking at the surrounding mountains in winter, you get the feeling that you’re creeping by sleeping giants that might pour down a surge of snow at any moment. If that weren’t enough, driving alone through such a place can seem like if you were to be buried, would anyone ever know?
In your work as an IT operator, the weight of managing modern IT systems can give you the same, anxious feeling. The complexity that builds up in infrastructure is like snow forming on a mountainside. If you get buried, how long will it take before people know? You’ve got to offload complexity wherever


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Ferret – Declarative web scraping

What is it?
ferret is a web scraping system aiming to simplify data extraction from the web for such things like ui testing, machine learning and analytics.Having it’s own declarative language, ferret abstracts away technical details and complexity of the underlying technologies, helping to focus on the data itself.It’s extremely portable, extensible and fast.
Show me some code

The following example demonstrates the use of dynamic pages.First of all, we load the main Google Search page, type search criteria into an input box and then click a search button.The click action triggers a redirect, so we wait till its end.Once the page gets loaded, we iterate over all elements in search results and assign output to a variable.The final for loop filters out empty elements that might be because of inaccurate use of selectors.
LET google = DOCUMENT(“https://www.google.com/”, true)

INPUT(google, ‘input[name=”q”]’, “ferret”)
CLICK(google, ‘input[name=”btnK”]’)

WAIT_NAVIGATION(google)

LET result = (
FOR result IN ELEMENTS(google, ‘.g’)
RETURN {
title:


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Facebook launches PyTorch 1.0

Earlier this year, we shared a vision for making AI development faster and more interoperable. Today, during our first-ever PyTorch Developer Conference, we are announcing updates about the growing ecosystem of software, hardware, and education partners that are deepening their investment in PyTorch. We’re also bringing together our active community of researchers, engineers, educators, and more to share how they’re using the open source deep learning platform for research and production, and walking through more details on the preview release of PyTorch 1.0.
PyTorch 1.0 accelerates the workflow involved in taking breakthrough research in artificial intelligence to production deployment. With deeper cloud service support from Amazon, Google, and Microsoft, and tighter integration with technology providers ARM, Intel, IBM, NVIDIA, and Qualcomm, developers can more easily take advantage of PyTorch’s ecosystem of compatible software, hardware, and developer tools. The more software and hardware that is compatible with PyTorch 1.0, the easier it


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Fastai v1 for PyTorch: Fast and accurate neural nets using modern best practices

Written: 02 Oct 2018 by Jeremy Howard

Note from Jeremy: Want to learn more? Listen to me discuss fastai with Sam Charrington in this in-depth interview.

Summary

Today fast.ai is releasing v1 of a new free open source library for deep learning, called fastai. The library sits on top of PyTorch v1 (released today in preview), and provides a single consistent API to the most important deep learning applications and data types. fast.ai’s recent research breakthroughs are embedded in the software, resulting in significantly improved accuracy and speed over other deep learning libraries, whilst requiring dramatically less code. You can download it today from conda, pip, or GitHub or use it on Google Cloud Platform. AWS support is coming soon.

About fast.ai

fast.ai’s mission is to make the power of state of the art deep learning available to anyone. In order to make that happen, we do three things:

Research how to apply state


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How to Install Apache Kafka Distributed Streaming Platform on Ubuntu

Apache Kafka is a distributed streaming platform developed by Apache Software Foundation and written in Java and Scala. Apache Kafka was originally developed by LinkedIn, and was open sourced in 2011. In this tutorial, we will show you how to step-by-step install and configure Apache Kafka on Ubuntu 18.04.


Original URL: https://www.howtoforge.com/tutorial/ubuntu-apache-kafka-installation/

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Rich-text editing platform Tiny raises $4M, launches file management service

Maybe you’ve never heard about Tiny, but chances are, you’ve used its products. Tiny is the company behind the text editors you’ve likely used in WordPress, Marketo, Zendesk, Atlassian and other products. The company is actually the result of the merger of Moxiecode, the two-person team behind the open source TinyMCE editor, and Ephox, the company behind the Textbox.io editor. Ephox was the larger company in this deal, but TinyMCE had a significantly larger user base, so Tiny’s focus is now almost exclusively on that.
And the future of Tiny looks bright thanks to a $4 million funding round led by BlueRun Ventures, the company announced today (in addition to a number of new products). Tiny CEO Andrew Roberts told me the round mostly came together thanks to personal connections. While both Ephox and Moxiecode were profitable, now seemed like the right time to try to push for growth.
Roberts also noted that


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