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Server: Google, SUSE, Mirantis, Kubernetes and Linux Containers

  • Introducing Spinnaker for Google Cloud Platform—continuous delivery made easy

    Spinnaker, developed jointly by Google and Netflix, is an open-source multi-cloud continuous delivery platform. Companies such as Box, Cisco, and Samsung use Spinnaker to create fast, safe, repeatable deployments. Today, we are excited to introduce the Spinnaker for Google Cloud Platform solution, which lets you install Spinnaker in Google Cloud Platform (GCP) with a couple of clicks, and start creating pipelines for continuous delivery.

  • SUSE Appoints First Female CEO

    SUSE has appointed Melissa Di Donato as the next CEO of the company to succeed, Nils Brauckmann, who will be retiring and leaving SUSE. “I am incredibly proud of SUSE’s progress and growth over the last eight years, which has culminated in it securing independent status,” Brauckmann said. Prior to SUSE, Di Donato was chief operating officer and chief revenue officer at SAP where she was responsible for the worldwide revenue, profit and customer satisfaction of the company’s digital core solutions.

  • Mirantis Kubernetes As A Service Is Better Than Competitors – Boris Rensk
  • Coming to grips with cloud and making choices

    On balance, it takes enterprises about 4-5 years before they report that a majority of workloads (75%) are leveraging some form of cloud environment or providers (451 Research, Voice of the Enterprise survey research). At best it’s a methodical process of reshaping investment, practices and business processes — at worst it’s a morass of failed starts, missed opportunities, poor planning and wasted effort. Enterprises should develop an objective, holistic view of their situation that allows for specific actions to be made with a clear eye as to the cost, the process, and the eventual benefits to finding the right venue for any given workload. There’s no right answer for any given situation, but there are right ways to proceed. It’s okay to have a preference for one provider or vendor, and it’s okay to be as independent and cloud-agnostic as possible. It’s okay to prioritize mass migration, and it’s okay to realize some things are better off in the enterprise datacenter. The important part is to develop ways to go into it with eyes wide open and a core understanding of the options available.

  • Get started with Kubernetes (using Python)

    So, you know you want to run your application in Kubernetes but don’t know where to start. Or maybe you’re getting started but still don’t know what you don’t know. In this blog you’ll walk through how to containerize an application and get it running in Kubernetes. This walk-through assumes you are a developer or at least comfortable with the command line (preferably bash shell).

  • Don’t Use Kubernetes Until You’ve Asked This Question

    Kubernetes technology has skyrocketed in popularity for the last few years. More and more organizations are using it to power their infrastructure, and as a result, there’s an influx of individuals learning how to use the technology in order to get a new job, upskill for an existing job, or simply to stay up-to-date with the latest tech. But why are organizations using this tech? Well, as more organizations have turned to containers in order to run their applications, they’re facing an issue: how do they manage them? Many are using Kubernetes to solve this problem. But is it the right solution?

  • Learn on Demand Systems Enables Lab Authors to Create Linux Containers

Security: Updates, VLC FUD and LinuxSecurity Turning 20

  • Security updates for Tuesday

    Security updates have been issued by Debian (libsdl2-image and libxslt), Oracle (java-1.8.0-openjdk and java-11-openjdk), Scientific Linux (java-1.8.0-openjdk and java-11-openjdk), SUSE (bzip2, microcode_ctl, and ucode-intel), and Ubuntu (clamav, evince, linux-hwe, linux-gcp, linux-snapdragon, and squid3).

  • Dodgy vids can hijack PCs via VLC security flaw, US, Germany warn. Software's makers not app-y with that claim

    In a bug-tracking ticket discussing CVE-2019-13615, VideoLAN lead developer Jean-Baptiste Kempf noted that he was unable to recreate the crash using a proof-of-concept .MP4 video, provided by a security researcher four weeks ago, that's supposed to knacker the latest version of VLC, 3.0.7.1. Nor was he able to crash the older 3.0.6 and work-in-progress releases, such as 3.0.8, he reported. "This does not crash a normal release of VLC 3.0.7.1," added Kempf. "Sorry, but this bug is not reproducible and does not crash VLC at all." VLC developer Francois Cartegnie was more blunt earlier today: "If you land on this ticket through a news article claiming a critical flaw in VLC, I suggest you to read the above comment first and reconsider your (fake) news sources."

  • Our Linux Sister Linuxsecurity.com are Celebrating their 20th Anniversary by Launching a New Website

    LinuxSecurity.com is the community’s central source for information on Linux and open source security. They follow the open source trends as they affect the community. Also they produce content that appeals to administrators, developers, home users, and security professionals. Having created a site that satisfies the needs of both IT professionals – including engineers, programmers, designers and system administrators – and those individuals seeking to learn more about security and open source, LinuxSecurity.com has grown to encompass not only their website but also two leading industry email newsletters, Linux Security Newsletter and Security Advisories Weekly.

Fedora and IBM/Red Hat Leftovers

  • ThinkPad X1 Carbon 6th gen on Fedora
  • Multitenant deployment of MongoDB using OpenShift Container Storage and using YCSB to test performance
  • IBM gives cancer-killing drug AI project to the open source community

    IBM has released three artificial intelligence (AI) projects tailored to take on the challenge of curing cancer to the open-source community. At the 18th European Conference on Computational Biology (ECCB) and the 27th Conference on Intelligent Systems for Molecular Biology (ISMB), which will be held in Switzerland later this month, the tech giant will dive into how each of the projects can advance our understanding of cancers and their treatment. 

  • IBM Open Sources Cancer-Fighting AI Project

    Now, the company has decided to make all three tools open-source, meaning scientists will be able to use them in their research whenever they please, according to ZDNet. The tools are designed to streamline the cancer drug development process and help scientists stay on top of newly-published research — so, if they prove useful, it could mean more cancer treatments coming through the pipeline more rapidly than before.

  • An OpenShift Administrator’s Guide to Onboarding Applications

    Infrastructure teams managing Red Hat OpenShift often ask me how to effectively onboard applications in production. OpenShift embeds many functionalities in a single product and it is fair to imagine an OpenShift administrator struggling to figure out what sort of conversations his team must have with an application team before successfully running an application on OpenShift. In this article, I suggest a few topics that administrators could use to actively engage with fellow application teams for the onboarding process. I have had several conversations with customers on these topics and observed that suggested approach has really helped them. By no means are these topics exhaustive, but they are sufficient to kick start the necessary and relevant conversations. Over time, I expect administrators to have larger conversations with application teams in application onboarding. 

  • OpenWhisk Gets Its Apache Software Diploma

    The OpenWhisk open source serverless platform hit graduation status as a Top-Level Project at the Apache Software Foundation. The designation comes as the serverless ecosystem continues its rapid evolution in meeting the production needs of organizations. The OpenWhisk project itself was initially born out of IBM, which donated its beta-level code into the Apache Incubator project in late 2016. IBM was using that codebase to support functions running on its IBM Cloud.

  • The browser wars and the birth of JavaScript

    Before anything like an Android device or iPhone existed, desktop computers were the battleground for the browser wars. The battle involved billions of dollars invested by a number of companies, all based on the premise that whoever ruled the desktop browser market would own the internet. Today, mobile devices account for nearly half of all website traffic. Back in the 1990s, however, almost all of the action on the web came from desktop machines, and the vast majority of those desktop machines were running some flavor of Microsoft Windows. In the browser world, the first-mover advantage belonged to Netscape Communications Corporation. They built the Netscape Navigator browser that made the web accessible to millions for the first time. Netscape had more than 80% of the market, but they also had no shortage of competition. IBM had a browser for OS/2. Oracle had the Powerbrowser, a Netscape-compatible product that included something called the Database Markup Language. The real danger to Netscape, of course, came from the company that owned more than 80% of the world’s desktops: Microsoft. Strategically, Netscape realized that the web needed to move past static web pages to reach its full potential. Even if they were created dynamically by something like a CGI script on the web server, pages didn’t change once they arrived in your browser. If you wanted to see even a slightly modified version of a page, you had to send a request back to the server and wait for a response. For all its sophistication, a web browser felt a lot like a dumb terminal attached to a mainframe. What web developers needed was a programming language that would run in the browser, taking advantage of the processing power of the desktop machine to give users a richer experience. [...] JavaScript’s dominance was cemented by the emergence of Node.js on the server side. At a minimum, it gave web developers the ability to take their JavaScript skills from the client to the server. Combined with the ability to pass functions as objects (callbacks), Node.js’s event loop popularized a whole new programming model. Suddenly, you could write a web server in just a few lines of code. Then, the rise of the Node Package Manager (npm) to manage dependencies meant a very small application could leverage other packages to do really sophisticated things. As a self-serving example, the knative-proxy package in the Coderland Compile Driver needs fewer than 40 lines of code to handle the HTTP POST and OPTIONS verbs. And it took yr author maybe 30 minutes to write. JavaScript is a simple, unpretentious language that has its fingers in every corner of your life. Turn off JavaScript in your browser and see how much of the web doesn’t work anymore. (Philosophical arguments as to whether that’s a good or bad thing are left to the reader.) No matter how or where you use the internet, Brendan Eich’s 10-day coding spree is the most important sprint in the history of computing. You don’t have to like JavaScript, but if you make a living developing for the web, you have to learn it.

Programming: Python, GCC and More

  • Stack Abuse: Python for NLP: Word Embeddings for Deep Learning in Keras

    This is the 16th article in my series of articles on Python for NLP. In my previous article I explained how N-Grams technique can be used to develop a simple automatic text filler in Python. N-Gram model is basically a way to convert text data into numeric form so that it can be used by statisitcal algorithms. Before N-Grams, I explained the bag of words and TF-IDF approaches, which can also be used to generate numeric feature vectors from text data. Till now we have been using machine learning appraoches to perform different NLP tasks such as text classification, topic modeling, sentimental analysis, text summarization, etc. In this article we will start our discussion about deep learning techniques for NLP. Deep learning approaches consist of different types of densely connected neural networks. These approaches have been proven efficient to solve several complex tasks such as self-driving cars, image generation, image segmentation, etc. Deep learning approaches have also been proven quite efficient for NLP tasks. In this article, we will study word embeddings for NLP tasks that involve deep learning. We will see how word embeddings can be used to perform simple classification task using deep neural network in Python's Keras Library.

  • Python with JSON Files

    With the growth and evolution of challenges in computer science, Python continues to rise as the primarily sought-after programming skill to solve data science problems.

  • Logging in Python

    Logging is a very useful tool in a programmer’s toolbox. It can help you develop a better understanding of the flow of a program and discover scenarios that you might not even have thought of while developing. Logs provide developers with an extra set of eyes that are constantly looking at the flow that an application is going through. They can store information, like which user or IP accessed the application. If an error occurs, then they can provide more insights than a stack trace by telling you what the state of the program was before it arrived at the line of code where the error occurred.

  • Let’s Build A Simple Interpreter. Part 16: Recognizing Procedure Calls

    Today we’re going to extend our interpreter to recognize procedure calls. I hope by now you’ve flexed your coding muscles and are ready to tackle this step. This is a necessary step for us before we can learn how to execute procedure calls, which will be a topic that we will cover in great detail in future articles. The goal for today is to make sure that when our interpreter reads a program with a procedure call, the parser constructs an Abstract Syntax Tree (AST) with a new tree node for the procedure call, and the semantic analyzer and the interpreter don’t throw any errors when walking the AST.

  • Playing Tic Tac Toe using Reinforcement Learning

    I have always been fascinated by the amazing work done by OpenAI. The one that stood out to me was a AI bot that could play the massively popular game - Dota 2. Dota 2 used to be the escape from the real world for me and my friends while I was in high school. This inspired me to learn more about the field of RL. I wanted to start small so I started with Tic Tac Toe.

  • Python zip function tutorial (Simple Examples)

    The zip() function in Python programming is a built-in standard function that takes multiple iterables or containers as parameters. An iterable in Python is an object that can be iterated or stepped through like a collection. The zip() function is used to map the same indexes of more than one iterable. Mapping these indexes will generate a zip object.

  • GCC 10 Compiler Picks Up New Scheduler Model & Cost Tables For AMD Zen 2 Processors

    While AMD developers published their "Znver2" compiler patches for Zen 2 originally back in November, months ahead of the recent Ryzen 3000 series launch, this compiler support was incomplete as it re-used the existing scheduler model and costs table of Znver1. Now though one of SUSE's compiler experts who often works in cooperation with AMD has published the new Znver2 scheduler model and costs table for Zen 2. The updated costs table better reflects the "costs" of moving and loading various registers and different instructions compared to Znver1 so the compiler can make wiser decisions for the most efficient usage. With these updated costs to reflect faster multiplication and 256 vector paths, there is better GNU C Library performance in particular and SUSE developer Jan Hubicka noted that the memory copy performance "wins" even for small blocks.

  • PyCoder’s Weekly: Issue #378 (July 23, 2019)