Introducing Play with Kubernetes

Every month for the last year, thousands of people have used Play with Docker and the accompanying hands-on Play with Docker Classroom training site. These sites allow you to use and learn Docker entirely within your own browser, without installing anything. Last summer, we quietly launched the companion site Play with Kubernetes, to give people a full command line while learning Kubernetes on the command line. And today we’re launching a new Kubernetes training site, the Play with Kubernetes Classroom.

The Play with Kubernetes Classroom is a workshop environment just like the Play with Docker Classroom. We currently have an extensive Kubernetes workshop originally based on Jérôme Petazzoni’s Container Training Kubernetes workshop. But instead of doing it all locally or setting up VMs in the cloud, you can now run through the workshop entirely in the browser.

Like the Play with Docker Classroom, we’ll be curating contributions of additional labs from the community. So give Kubernetes in your browser a try, and then come on over to the Play with Kubernetes repository to share your own tutorials with the community.

Try Kubernetes in the browser Continue reading

Datanauts 135: An Introduction To Edge Computing

It turns out you can t do it all in the cloud. And thus, we have the rise of edge computing, in which data is collected, processed, and analyzed close to the source of its creation and close to where people and systems need it.

The goals of edge computing include improving performance, reducing the costs and time of data transmission, and creating new applications to take advantage of that data.

Our guide to edge computing is Alex Marcham. Alex is a technologist, writer and researcher. You can find his work at NetworkArchitecture2020.com.

We level-set with a working definition of edge computing, examine the notion of locality and what it means for edge computing, and discuss latency issues.

We explore edge computing use cases such as industrial processes and video surveillance, and dive into the infrastructure that drives this technology.

Show Links:

Network Architecture 2020

Alex Marcham on Twitter

The post Datanauts 135: An Introduction To Edge Computing appeared first on Packet Pushers.

Making AI Users Accountable For Their Algorithms

Any new and powerful technology always cuts both ways.

The rapid rise of the machine learning flavor of artificial intelligence is due to the fact that, unlike prior approaches, it actually works and therefore can be embraced by a wide swath of businesses, research and educational institutions, and technology companies. …

Making AI Users Accountable For Their Algorithms was written by Jeffrey Burt at .

History Of Networking – Martin Casado – Software Defined Networking

Today, every network vendor sells a solution labeled “software-defined”. But in the 2000’s, the networking stack was driven by constraints in hardware that could not be changed. In this History of Networking, Martin Casado joins us to talk about the ideas that drove his research in software-defined networking and his thoughts on hardware and software in networking.

 

Martin Casado
Guest
Russ White
Host
Jordan Martin
Host
Eyvonne Sharp
Host

Outro Music:
Danger Storm Kevin MacLeod (incompetech.com)
Licensed under Creative Commons: By Attribution 3.0 License
http://creativecommons.org/licenses/by/3.0/

The post History Of Networking – Martin Casado – Software Defined Networking appeared first on Network Collective.

Canadian Youth Advocates Participate in Enhancing IoT Project

On May 14, a group of young people who are currently working on or are studying tech, politics, computer science, and the Internet of Things (IoT) met for a two-hour Youth Advocates for IoT Security round table. This event was a part of the Internet Society’s year-long initiative, the Canadian Multistakeholder Process – Enhancing IoT Security in partnership with Innovation, Science and Economic Development, the Canadian Internet Registration Authority, CANARIE, and CIPPIC. It serves as just one of several workshops that will be held during the process to develop recommendations for a set of norms and policies to secure the IoT in Canada.

The round table offered an opportunity for young people in school or their early careers to voice their opinions and provide unique inputs for consideration on the following aspects of IoT security:

  • How young people currently use IoT devices;
  • How they anticipate these devices will be used in the future; and
  • Effective ways of educating young consumers about IoT security.

The group discussed the ways in which IoT devices have become seemingly ubiquitous in youth’s lives. IoT devices have also become integral, and often required, parts of classroom learning and workplaces. Now, the lines Continue reading

What’s quantum computing [and why enterprises need to care]

The first thing to know about quantum computing is that it won’t displace traditional, or ‘classical’ computing. The second thing to know: Quantum computing is still a nascent technology that probably won’t be ready for prime time for several more years.And the third thing you should know? The time to start protecting your data’s security from quantum computers is now.[ Learn how server disaggregation can boost data center efficiency and how Windows Server 2019 embraces hyperconverged data centers . | Get regularly scheduled insights by signing up for Network World newsletters. ] Here’s an overview of what you should know about quantum computing.To read this article in full, please click here

Who’s developing quantum computers?

There are two main camps in the quantum computing development, says Ashish Nadkarni, Program Vice President of Computing Platforms, Worldwide Infrastructure at IDC. In the first camp are entrenched players from the world of classical computing. And in the second are quantum computing startups.“It’s a highly fragmented landscape,” Nadkarni says. “Each company has its own approach to building a universal quantum computer and delivering it as a service.”[ Now see What is quantum computing [and why enterprises should care.] Classic-computing vendors pioneer quantum computing Along with IBM, other classical computing companies staking a claim in the emerging field of quantum computing include:To read this article in full, please click here

What’s quantum computing [and why enterprises need to care]

The first thing to know about quantum computing is that it won’t displace traditional, or ‘classical’ computing. The second thing to know: Quantum computing is still a nascent technology that probably won’t be ready for prime time for several more years.And the third thing you should know? The time to start protecting your data’s security from quantum computers is now.[ Learn how server disaggregation can boost data center efficiency and how Windows Server 2019 embraces hyperconverged data centers . | Get regularly scheduled insights by signing up for Network World newsletters. ] Here’s an overview of what you should know about quantum computing.To read this article in full, please click here

Who’s developing quantum computers?

There are two main camps in the quantum computing development, says Ashish Nadkarni, Program Vice President of Computing Platforms, Worldwide Infrastructure at IDC. In the first camp are entrenched players from the world of classical computing. And in the second are quantum computing startups.“It’s a highly fragmented landscape,” Nadkarni says. “Each company has its own approach to building a universal quantum computer and delivering it as a service.”[ Now see What is quantum computing [and why enterprises should care.] Classic-computing vendors pioneer quantum computing Along with IBM, other classical computing companies staking a claim in the emerging field of quantum computing include:To read this article in full, please click here

Multi-tier load-balancing with Linux

A common solution to provide a highly-available and scalable service is to insert a load-balancing layer to spread requests from users to backend servers.1 We usually have several expectations for such a layer:

scalability
It allows a service to scale by pushing traffic to newly provisioned backend servers. It should also be able to scale itself when it becomes the bottleneck.
availability
It provides high availability to the service. If one server becomes unavailable, the traffic should be quickly steered to another server. The load-balancing layer itself should also be highly available.
flexibility
It handles both short and long connections. It is flexible enough to offer all the features backends generally expect from a load-balancer like TLS or HTTP routing.
operability
With some cooperation, any expected change should be seamless: rolling out a new software on the backends, adding or removing backends, or scaling up or down the load-balancing layer itself.

The problem and its solutions are well known. From recently published articles on the topic, “Introduction to modern network load-balancing and proxying” provides an overview of the state of the art. Google released “Maglev: A Fast and Reliable Software Network Load Balancer” describing their Continue reading

Why is Network Automation So Hard?

This blog post was initially sent to the subscribers of my SDN and Network Automation mailing list. Subscribe here.

Every now and then someone asks me “Why are we making so little progress on network automation? Why does it seem so hard?”

There are some obvious reasons:

However, there’s a bigger elephant in the room: every network is a unique snowflake.

Read more ...

Pixie: a system for recommending 3+ billion items to 200+ million users in real-time

Pixie: a system for recommending 3+ billion items to 200+ million users in real-time Eksombatchai et al., WWW’18

(If you don’t have ACM Digital Library access, the paper can be accessed either by following the link above directly from The Morning Paper blog site, or from the WWW 2018 proceedings page).

Pinterest is a visual catalog with several billion pins, which are visual bookmarks containing a description, a link, and an image or a video. A major problem faced at Pinterest is to provide personalized, engaging, and timely recommendations from a pool of 3+ billion items to 200+ million monthly active users.

Stating the obvious, 3 billion or so items is a lot to draw recommendations from. This paper describes how Pinterest do it. One of the requirements is that recommendations need to be calculated in real-time on-demand. I’m used to thinking about the shift from batch to real-time in terms of improved business responsiveness, more up-to-date information, continuous processing, and so on. Pinterest give another really good reason which is obvious with hindsight, but hadn’t struck me before: when you compute recommendations using a batch process, you have to calculate the recommendations for every user Continue reading

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