Technology Short Take 96

Welcome to Technology Short Take 96! Ahead, lying in wait, is a unique collection of links, articles, and thoughts about various data center technologies. Browse if you dare…OK, so I’m being a bit melodramatic. It’s still some good stuff here!

Networking

  • Via Matt Oswalt and Michael Bushong, I came across this article on Juniper’s use of P4. Interesting stuff…P4 definitely has the potential to dramatically reshape networking in new ways, in my humble opinion.
  • Maxime Lagresle of XING outlines how they went about troubleshooting an unexplained connection timeout on Kubernetes/Docker.
  • Ajay Chenampara outlines how POAP (Power On Auto Provisioning), a feature of Cisco NX-OS, works to streamline provisioning new network switches.
  • Don Schenck has a high-level overview of Istio and service meshes.
  • Daniel Álvarez has a good article describing some OVN profiling and optimizing he recently performed. I believe the patches he mentioned in the post have already been accepted into the OVN codebase.

Servers/Hardware

Nothing this time around; sorry! If you have some articles you feel are worthy of inclusion in the next Tech Short Take, send them my way!

Security

Hyperconverged infrastructure gets its own Gartner magic quadrant

Hyperconvergence is winning over enterprises that are drawn to its potential to ease management, streamline the deployment of new workloads, and optimize infrastructure costs.As much as 20 percent of business-critical applications currently deployed on three-tier IT infrastructure will transition to hyperconverged infrastructure by 2020, predicts Gartner, which recently gave the technology its own magic quadrant.[ Check out our What is hyperconvergence? and learn whether your network and team are up to hyperconverged storage. ] The magic quadrant is Gartner’s signature format for tech market analysis, and in prior years, the research firm tackled hyperconvergence as part of its integrated-systems research.To read this article in full, please click here

Hyperconverged infrastructure gets its own Gartner magic quadrant

Hyperconvergence is winning over enterprises that are drawn to its potential to ease management, streamline the deployment of new workloads, and optimize infrastructure costs.As much as 20 percent of business-critical applications currently deployed on three-tier IT infrastructure will transition to hyperconverged infrastructure by 2020, predicts Gartner, which recently gave the technology its own magic quadrant.[ Check out our What is hyperconvergence? and learn whether your network and team are up to hyperconverged storage. ] The magic quadrant is Gartner’s signature format for tech market analysis, and in prior years, the research firm tackled hyperconvergence as part of its integrated-systems research.To read this article in full, please click here

Video: Automated Data Center Fabric Deployment Demo

I was focused on network automation this week, starting with a 2-day workshop and continuing with an overview of real-life automation wins. Let’s end the week with another automation story: automated data center fabric deployment demonstrated by Dinesh Dutt during his part of Network Automation Use Cases webinar.

You’ll need at least free ipSpace.net subscription to watch the video.

Watch the video

ISOC’s Hot Topics at IETF 101

Tomorrow begins IETF 101 in London, United Kingdom, and it’s the third time that an IETF has been held in the country. Following on the heels of our Rough Guide to IETF 101 where we go in-depth about specific topics of interest, the ISOC Internet Technology Team is again highlighting the latest IPv6, DNSSEC, Securing BGP, TLS and IoT related developments as the week progresses.

Below are the sessions that we’ll be following in the coming week. Note this post was written in advance so please check the official IETF 101 agenda for any updates, room changes, or final details.

Monday, 18 March 2018

Tuesday, 19 March 2018

Getting AI Leverage With GPU-Optimized Systems

The artificial intelligence revolution is quickly changing every industry, and modern data centers must be equipped to capitalize on these extraordinary new capabilities. Hewlett Packard Enterprise (HPE) and Nvidia are partnering to bring best-of-breed AI solutions to every customer, offering AI-integrated systems, services, and support capabilities to help all organizations seamlessly optimize their AI foundation, deliver differentiated outcomes, and gain competitive advantage.

High performance computing has become key to solving many of the world’s grand challenges in the realms of science, industry, and engineering. However, traditional CPUs are increasingly failing to deliver the performance gains they used to, and the …

Getting AI Leverage With GPU-Optimized Systems was written by Timothy Prickett Morgan at The Next Platform.

A Secure Supply Chain for Kubernetes, Part 2

Two weeks ago we shared how the upcoming release of Docker Enterprise Edition (Docker EE) is able to secure the software supply chain for Kubernetes; just as it does for Docker Swarm through a combination of scanning for vulnerabilities and implementing image promotion policies. In this blog, we’ll take a closer look at another part of this solution – Docker Content Trust and image signing.

When combined with granular Role Based Access Controls [RBAC] and the secure clustering features of Docker EE, organizations get a secure container platform solution that is ready for the enterprise.

Restricting Unverified Kubernetes Content

As discussed in Part 1 of this blog post, organizations typically have a “supply chain” for how applications progress from a developer’s laptop to production, whether that is on-premises or in the cloud. For larger organizations, the team that handles QA and testing is not always the same team that develops the applications. There may also be a separate team that handles staging and pre-production before an application is pushed to production. Since an application can pass through several teams before it gets deployed, it’s important for organizations to be able to validate the source of the application.

Docker Content Trust Continue reading

Practical Computational Balance: Contending with Unplanned Data

In part one of our series on reaching computational balance, we described how computational complexity is increasing logarithmically. Unfortunately, data and storage follows an identical trend.

The challenge of balancing compute and data at scale remains constant. Because providers and consumers don’t have access to “the crystal ball of demand prediction”, the appropriate computational response to vast, unpredictable amounts of highly variable complex data becomes unintentionally unplanned.

We must address computational balance in a world barraged by vast and unplanned data.

Before starting any discussion of data balance, it is important to first remind ourselves of scale.  Small …

Practical Computational Balance: Contending with Unplanned Data was written by James Cuff at The Next Platform.

Building vs. buying your engineering staff

Should I build it or buy it? It’s an age old question often used in reference to furniture, websites and risky home remodeling projects (DIY is fun, I swear!). Same goes for your engineering team — should I hire and build out an engineering staff or should I outsource an engineering team?

According to a 2016 study done by Deloitte, 72% of organizations with over $1 billion in revenue are outsourcing their IT functions. However, only 31% of them plan to increase this spending in the following year. Could this allude to investments for inhouse staff? Maybe. In the following paragraphs, we will discuss the pros and cons of creating an inhouse vs. outsourcing engineering staff.

Building vs. buying engineering — two methods

Let’s start with some simple definitions.

Building an engineering team: We’re talking about hiring people. When I say building, I mean recruiting talent, hiring them full time, offering benefits and keeping them engaged with exciting projects. I also mean hiring experts in the field who are lifelong learners and are excited about innovation. In time, they give back to the company through their developed expertise, loyalty and institutional knowledge. Those are your people.

Buying an engineering Continue reading

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