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IBM/Red Hat and Intel Leftovers

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Red Hat
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  • Troubleshooting Red Hat OpenShift applications with throwaway containers

    Imagine this scenario: Your cool microservice works fine from your local machine but fails when deployed into your Red Hat OpenShift cluster. You cannot see anything wrong with the code or anything wrong in your services, configuration maps, secrets, and other resources. But, you know something is not right. How do you look at things from the same perspective as your containerized application? How do you compare the runtime environment from your local application with the one from your container?

    If you performed your due diligence, you wrote unit tests. There are no hard-coded configurations or hidden assumptions about the runtime environment. The cause should be related to the configuration your application receives inside OpenShift. Is it time to run your app under a step-by-step debugger or add tons of logging statements to your code?

    We’ll show how two features of the OpenShift command-line client can help: the oc run and oc debug commands.

  • What piece of advice had the greatest impact on your career?

    I love learning the what, why, and how of new open source projects, especially when they gain popularity in the DevOps space. Classification as a "DevOps technology" tends to mean scalable, collaborative systems that go across a broad range of challenges—from message bus to monitoring and back again. There is always something new to explore, install, spin up, and explore.

  • How DevOps is like auto racing

    When I talk about desired outcomes or answer a question about where to get started with any part of a DevOps initiative, I like to mention NASCAR or Formula 1 racing. Crew chiefs for these race teams have a goal: finish in the best place possible with the resources available while overcoming the adversity thrown at you. If the team feels capable, the goal gets moved up a series of levels to holding a trophy at the end of the race.

    To achieve their goals, race teams don’t think from start to finish; they flip the table to look at the race from the end goal to the beginning. They set a goal, a stretch goal, and then work backward from that goal to determine how to get there. Work is delegated to team members to push toward the objectives that will get the team to the desired outcome.

    [...]

    Race teams practice pit stops all week before the race. They do weight training and cardio programs to stay physically ready for the grueling conditions of race day. They are continually collaborating to address any issue that comes up. Software teams should also practice software releases often. If safety systems are in place and practice runs have been going well, they can release to production more frequently. Speed makes things safer in this mindset. It’s not about doing the “right” thing; it’s about addressing as many blockers to the desired outcome (goal) as possible and then collaborating and adjusting based on the real-time feedback that’s observed. Expecting anomalies and working to improve quality and minimize the impact of those anomalies is the expectation of everyone in a DevOps world.

  • Deep Learning Reference Stack v4.0 Now Available

    Artificial Intelligence (AI) continues to represent one of the biggest transformations underway, promising to impact everything from the devices we use to cloud technologies, and reshape infrastructure, even entire industries. Intel is committed to advancing the Deep Learning (DL) workloads that power AI by accelerating enterprise and ecosystem development.

    From our extensive work developing AI solutions, Intel understands how complex it is to create and deploy applications for deep learning workloads. That?s why we developed an integrated Deep Learning Reference Stack, optimized for Intel Xeon Scalable processor and released the companion Data Analytics Reference Stack.

    Today, we?re proud to announce the next Deep Learning Reference Stack release, incorporating customer feedback and delivering an enhanced user experience with support for expanded use cases.

  • Clear Linux Releases Deep Learning Reference Stack 4.0 For Better AI Performance

    Intel's Clear Linux team on Wednesday announced their Deep Learning Reference Stack 4.0 during the Linux Foundation's Open-Source Summit North America event taking place in San Diego.

    Clear Linux's Deep Learning Reference Stack continues to be engineered for showing off the most features and maximum performance for those interested in AI / deep learning and running on Intel Xeon Scalable CPUs. This optimized stack allows developers to more easily get going with a tuned deep learning stack that should already be offering near optimal performance.

More in Tux Machines

Chromium/Mozilla Firefox: Chrome 78 Beta, Keygen Setback and iframes

  • Chrome 78 Beta: a new Houdini API, native file system access and more

    Unless otherwise noted, changes described below apply to the newest Chrome Beta channel release for Android, Chrome OS, Linux, macOS, and Windows. Find more information about the features listed here through the provided links or from the list on ChromeStatus.com. Chrome 78 is beta as of September 19, 2019.

  • Chrome 78 Hits Beta With Native File System API, Much Faster WebSockets

    Google on Friday released the Chrome 78 web-browser beta following last week's release of Chrome 77. Chrome 78 Beta is coming with a new Houdini API or more formally known as the CSS Properties and Values API Level 1, which lets developers register variables as fully custom CSS properties and can better handle animations and other use-cases.

  • Firefox 69 dropped support for <keygen>

    With version 69, firefox removed the support for the <keygen> feature to easily deploy TLS client certificates. It's kind of sad how used I've become to firefox giving me less and less reasons to use it...

  • [Mozilla] Restricting third-party iframe widgets using the sandbox attribute, referrer policy and feature policy

    Adding third-party embedded widgets on a website is a common but potentially dangerous practice. Thankfully, the web platform offers a few controls that can help mitigate the risks. While this post uses the example of an embedded SurveyMonkey survey, the principles can be used for all kinds of other widgets. Note that this is by no means an endorsement of SurveyMonkey's proprietary service. If you are looking for a survey product, you should consider a free and open source alternative like LimeSurvey.

DM-Clone Target Added To Linux 5.4 For Efficient Remote Replication Of A Block Device

Added to the device mapper (DM) code with the Linux 5.4 kernel is an interesting addition that benefits those wanting to carry out some interesting use-cases around remote replication of block devices. As explained in the original patch proposal for dm-clone, "dm-clone produces a one-to-one copy of an existing, read-only device (origin) into a writable device (clone): It presents a virtual block device which makes all data appear immediately, and redirects reads and writes accordingly. The main use case of dm-clone is to clone a potentially remote, high-latency, read-only, archival-type block device into a writable, fast, primary-type device for fast, low-latency I/O. The cloned device is visible/mountable immediately and the copy of the origin device to the clone device happens in the background, in parallel with user I/O." Read more

Devices: One Laptop Per Child (OLPC) XO-1.75, PiCAN3 CAN-Bus Board and BeagleBoard

IBM, Red Hat and Fedora

  • OpenShift Commons Gathering in Milan 2019 – Recap [Slides]

    On September 18th, 2019, the first OpenShift Commons Gathering Milan brought together over 300 experts to discuss container technologies, operators, the operator framework and the open source software projects that support the OpenShift ecosystem. This was the first OpenShift Commons Gathering to take place in Italy. The standing room only event hosted 11 talks in a whirlwind day of discussions. Of particular interest to the community was Christian Glombek’s presentation updating the status and roadmap for OKD4 and CoreOS. Highlights from the Gathering induled an OpenShift 4 Roadmap Update, customer stories from Amadeus, the leading travel technology company, and local stories from Poste Italiane and SIA S.p.A. In addition to the technical updates and customer talks, there was plenty of time to network during the breaks and enjoy the famous Italian coffee.

  • Powering the hybrid cloud on next-generation hardware: Red Hat Enterprise Linux on IBM System Z and LinuxONE

    For more than five years we have been driving our technology strategy around the idea that the future of enterprise IT does not reside solely in an enterprise datacenter or in the public cloud. Instead the next wave of computing is built on a blend of these technologies and infrastructure: in short, the future is hybrid. The value of hybrid clouds comes from the choice it delivers, pairing the control of the corporate datacenter alongside the scale and flexibility of public clouds. We strongly feel, however, that the most valuable hybrid clouds are those that offer not only a choice of deployment type and location, but also a choice of the underlying architecture and the capacity to run on multiple public clouds. [....] With RHEL available on Z15 and LinuxONE III, this helps pave the way for the rest of Red Hat’s hybrid cloud portfolio, including Red Hat OpenShift, to emerge on IBM enterprise platforms. We’re pleased to continue our work with IBM in bringing the world’s leading enterprise Linux platform to their next-generation systems.

  • Red Hat OpenStack Platform 15 Marks End of Short-Term Support

    Red Hat OpenStack Platform 15 is the last release that will only be supported for a year, as the company moves to a new model to support the open-source cloud platform.

  • Fedora rawhide – fixed bugs 2019/07