BrandPost: Network Fabrics: 5 Common Misconceptions Dispelled

What’s old is new again. This statement rings true as the industry rallies behind fabric networking again. Fabrics are not a new technology; they’ve been around since 2011/2012. However, we’ve seen increased uptake for fabrics outside of the traditional data center and into the enterprise campus. As the use cases and the technology continue to evolve, this blog clarifies some common misconceptions you may have about fabric technology.1. They are only for the data center Not anymore. Going back 5-6 years, network fabrics were originally designed to solve how to stretch L2 VLANs across subnets for VM migrations and mobility. We now see far more use cases for network fabrics that extend to the enterprise campus portion of the network. Examples include network automation, zero-touch provisioning, simplified network segmentation, and even high-performance multicast without the use of any complex PIM protocols.To read this article in full, please click here

BrandPost: Campus networks: Practical tips for the digital age

Recently, we released our new analyst report: Rethinking Campus Networks of the Future. It examines trends that are impacting campus networks and includes a few practical solutions for bringing enhanced automation, security and visibility into the campus network overall. We’ll report on the specifics in this blog.To read this article in full, please click here

BrandPost: Internet Routing: Requirements for the Data Center & Campus

In a recent blog, we discussed connectivity options for enterprise data centers building hybrid clouds. One of the options was to connect cloud providers directly over the internet, which has the advantage of being able to use an existing internet connection. It’s the easiest option and you can connect to any number of cloud service providers. Following that article, we wrote about scaling the modern data center, covering interface density and other requirements for data center solutions, whether housed on enterprise premises or in colocation facilities. Here, we’ll focus on internet connectivity and some of the requirements, including scale.To read this article in full, please click here

IDG Contributor Network: Network performance monitoring market poised for explosive growth

A recent Gartner report on network performance monitoring and diagnostics (NPMD) estimated the market to a whopping $2.1 billion and growing at a compound annual growth rate (CAGR) of 15.9 percent, with more growth in sight. Wow. So what will drive this growth and why?New approaches to harvesting network data using sophisticated big data analytics techniques combined with cloud computing and machine learning technologies is the answer. This perfect confluence of technologies is poised to redefine the conventional infrastructure management market.Central to this shift is the use of analytics technologies and strategies to extract new insights and value from data produced by and collected from the network to drive business value.To read this article in full, please click here

IDG Contributor Network: Network performance monitoring market poised for explosive growth

A recent Gartner report on network performance monitoring and diagnostics (NPMD) estimated the market to a whopping $2.1 billion and growing at a compound annual growth rate (CAGR) of 15.9 percent, with more growth in sight. Wow. So what will drive this growth and why?New approaches to harvesting network data using sophisticated big data analytics techniques combined with cloud computing and machine learning technologies is the answer. This perfect confluence of technologies is poised to redefine the conventional infrastructure management market.Central to this shift is the use of analytics technologies and strategies to extract new insights and value from data produced by and collected from the network to drive business value.To read this article in full, please click here

The EIGRP SIA Incident: Positive Feedback Failure in the Wild

Reading a paper to build a research post from (yes, I’ll write about the paper in question in a later post!) jogged my memory about an old case that perfectly illustrated the concept of a positive feedback loop leading to a failure. We describe positive feedback loops in Computer Networking Problems and Solutions, and in Navigating Network Complexity, but clear cut examples are hard to find in the wild. Feedback loops almost always contribute to, rather than independently cause, failures.

Many years ago, in a network far away, I was called into a case because EIGRP was failing to converge. The immediate cause was neighbor flaps, in turn caused by Stuck-In-Active (SIA) events. To resolve the situation, someone in the past had set the SIA timers really high, as in around 30 minutes or so. This is a really bad idea. The SIA timer, in EIGRP, is essentially the amount of time you are willing to allow your network to go unconverged in some specific corner cases before the protocol “does something about it.” An SIA event always represents a situation where “someone didn’t answer my query, which means I cannot stay within the state machine, so I Continue reading

Bidders Off And Running After $1.8 Billion DOE Exascale Super Deals

Supercomputer makers have been on their exascale marks, and they have been getting ready, and now the US Department of Energy has just said “Go!”

The requests for proposal have been opened up for two more exascale systems, with a budget ranging from $800 million to $1.2 billion for a pair of machines to be installed at Oak Ridge National Laboratory and Lawrence Livermore National Laboratory and a possible sweetener of anywhere from $400 million to $600 million that, provided funding can be found, allows Argonne National Laboratory to also buy yet another exascale machine.

Oak Ridge, Argonne, and Livermore …

Bidders Off And Running After $1.8 Billion DOE Exascale Super Deals was written by Timothy Prickett Morgan at The Next Platform.

Give Meaning to 100 billion Events a Day – The Analytics Pipeline at Teads

This is a guest post by Alban Perillat-Merceroz, Software Engineer at Teads.tv.

In this article, we describe how we orchestrate Kafka, Dataflow and BigQuery together to ingest and transform a large stream of events. When adding scale and latency constraints, reconciling and reordering them becomes a challenge, here is how we tackle it.


Teads for Publisher, one of the webapps powered by Analytics

 

In digital advertising, day-to-day operations generate a lot of events we need to track in order to transparently report campaign’s performances. These events come from:

  • Users’ interactions with the ads, sent by the browser. These events are called tracking events and can be standard (start, complete, pause, resume, etc.) or custom events coming from interactive creatives built with Teads Studio. We receive about 10 billion tracking events a day.
  • Events coming from our back-ends, regarding ad auctions’ details for the most part (real-time bidding processes). We generate more than 60 billion of these events daily, before sampling, and should double this number in 2018.

In the article we focus on tracking events as they are on the most critical path of our business.

Simplified overview of our technical context with the two main Continue reading

SDKLT

Logical Table Software Development Kit (SDKLT) is a new, powerful, and feature rich Software Development Kit (SDK) for Broadcom switches. SDKLT provides a new approach to switch configuration using Logical Tables.

Building the Demo App describes how to get started using a simulated Tomahawk device. Included, is a CLI that can be used to explore tables. For example, the following CLI output shows the attributes of the sFlow packet sampling table:
BCMLT.0> lt list -d MIRROR_PORT_ENCAP_SFLOW
MIRROR_PORT_ENCAP_SFLOW
  Description: The MIRROR_PORT_ENCAP_SFLOW logical table is used to specify
               per-port sFlow encapsulation sample configuration.
  11 fields (1 key-type field):
    SAMPLE_ING_FLEX_RATE
        Description: Sample ingress flex sFlow packet if the generated sFlow random
                     number is greater than the threshold. A lower threshold leads to
                     higher sampling frequency.
    SAMPLE_EGR_RATE
        Description: Sample egress sFlow packet if the generated sFlow random number is
                     greater than the threshold. A lower threshold leads to
                     higher sampling frequency.
    SAMPLE_ING_RATE
        Description: Sample ingress sFlow packet if the generated sFlow random number is
                     greater than the threshold. A lower threshold leads to
                     higher sampling frequency.
    SAMPLE_ING_FLEX_MIRROR_INSTANCE
        Description: Enable to copy ingress flex sFlow packet samples to the ingress
                     mirror member using the sFlow mirror instance configuration.
    SAMPLE_ING_FLEX_CPU
        Description: Enable to copy ingress flex  Continue reading

Network Break 179: Microsoft Targets Edge Computing; HCI Revenues Boom

Take a Network Break! Edge computing is the new hotness for traditional IT vendors as Microsoft and HPE, via its Aruba business unit, target edge computing infrastructure and software for new growth.

Meanwhile, Intel sells embedded software developer Wind River to a private equity firm, and we review the potential financial impact to legacy networking vendors as AT&T plans a massive whitebox rollout.

HCI revenues skyrocket in 2017; Delta, Sears, and Sacks Fifth Avenue get hacked; and Panera Bread picks a security fight with the wrong person.

We’ve got links to all the stories we cover just after our sponsor messages.

Sponsor: InterOptic

InterOptic offers high-performance, high-quality optics at a fraction of the cost. Find out more at InterOptic.com, and if you re attending Interop 2018 in Vegas, stop by the InterOptic booth to learn how they can help you spec the right optics for your network.

Coffee Talk: Kentik

Stay tuned after the news for a Coffee Talk conversation with sponsor Kentik. Kentik makes a big data platform to provide actionable insight from network data. Our guest is co-founder and CEO Avi Freedman, and we talk about how to use network data for fun and packets!

Show Links:

Continue reading

Mellanox, Ixia and Cumulus: Part 1

When I saw that Mellanox was presenting at Networking Field Day 17, I was definitely curious. When I found out that I would in fact be watching a joint presentation by Mellanox, Cumulus Networks and Ixia, it is fair to consider my interest piqued. Why would these three companies present together?

Cumulus/Mellanox/Ixia Logos

It turns out that these three companies present quite a compelling story, both individually–as you would probably expect–but also when used in combination. This post looks at the role of Mellanox Ethernet switches in an Ethernet fabric.

Mellanox

To me, Mellanox has been one of those ‘behind the scenes’ companies whose hardware is all over the place but whose name, in Ethernet circles at least, is less well known. Storage and compute engineers on the other hand are likely more familiar with the Mellanox name, especially in the context of Infiniband switches and network interface cards (NICs). In 2016 Mellanox acquired EZchip, allowing the development of some very capable Ethernet switches and an expansion of the company’s portfolio; to paraphrase Amit Katz (VP, WW Ethernet Switch), Mellanox connects PCI-Express interfaces together by building NICs, cables and switches.

At the Networking Field Day event in February 2018, Continue reading

Deep Learning In R: Documentation Drives Algorithms

Hard to believe, but the R programming language has been with us since 1993.

A quarter century has now passed since the authors Gentleman and Ihaka originally conceived the R platform as an implementation of the S programming language.

Continuous global software development has taken the original concepts originally inspired by John Chambers’ Scheme in 1975 to now include parallel computing, bioinformatics, social science and more recently complex AI and deep learning methods. Layers have been built on top of layers and today’s R looks nothing like 1990’s R.

So where are we at, especially with the emerging opportunities …

Deep Learning In R: Documentation Drives Algorithms was written by James Cuff at The Next Platform.

1 … 1,654 1,655 1,656 1,657 1,658 … 3,841