Stuff The Internet Says On Scalability For July 13th, 2018

Hey, it's HighScalability time:

 

Steve Blank tells the Secret History of Silicon Valley. What a long, strange trip it is.

 

Do you like this sort of Stuff? Please lend me your support on Patreon. It would mean a great deal to me. And if you know anyone looking for a simple book that uses lots of pictures and lots of examples to explain the cloud, then please recommend my new book: Explain the Cloud Like I'm 10. They'll love you even more.

 

  • $27 billion: CapEx invested by leading cloud vendors in first quarter of 2018; $40 billion: App store revenue in 10 years; $57.5 billion: venture investment first half of 2018; 1 billion: Utah voting system per day hack attempts; 67%: did not deploy a serverless app last year; $1.8 billion: made by Pokeman GO; $13 billion: Netflix's new content budget; 

  • Quotable Quotes:
    • @davidbrunelle: The best developers and engineering leaders I've personally worked with do *not* have a notable presence on GitHub or public bodies of speaking or writing work. I worry that a lot of folks confuse celebrity and visibility with talent and ability.
    • Bernard Continue reading

We’ve Added a New Machine Learning Course to Our Video Library!

This is a 2 and a half hour introductory course in Machine Learning. It’s taught by Yogesh Kulkarni, a practitioner and instructor in the field of Machine learning.


Why You Should Study This Topic:

 Machine Learning is getting more popular each day. It is not just hype, but an essential technique made possible and powerful by the availability of data. Studying Machine Learning is imperative, and Python is a good programming environment to get started with the basics. This workshop will not only familiarize you with this powerful and popular techniques, but will also give you the confidence necessary to venture into this on your own, thereby improving your chances of a lucrative career ahead.


Who Should Watch:

 This course is for anyone who wants to become more familiar with Machine Learning. It is recommended to have some knowledge of college level mathematics and programming using Python. You can be from any domain, such as Finance, Engineering, Agriculture, Biology, etc. you will know a new problem-solving technique which could be of great help in your own domain.


What You’ll Learn:

 You will learn what Artificial Intelligence is, how it relates to Machine Learning and Deep Learning, what’s the core idea Continue reading

Two studies show the data center is thriving instead of dying

Once again research is showing that rumors of the demise of the data center are greatly exaggerated. One study shows across-the-board growth in IT spending, while a second predicts that the financial services sector is really set to explode.Market research firm IHS Markit surveyed IT managers at 151 North American organizations and found that most of them expect to at least double the amount of physical servers in their data centers by 2019.“We are seeing a continuation of the enterprise DC growth phase signaled by last year’s respondents and confirmed by respondents to this study. Enterprises are transforming their on-premises DC to a cloud architecture, making the enterprise DC a first-class citizen as enterprises build their multi-clouds,” wrote Clifford Grossner, senior research director in the cloud and data center research practice at IHS Markit.To read this article in full, please click here

Two studies show the data center is thriving instead of dying

Once again research is showing that rumors of the demise of the data center are greatly exaggerated. One study shows across-the-board growth in IT spending, while a second predicts that the financial services sector is really set to explode.Market research firm IHS Markit surveyed IT managers at 151 North American organizations and found that most of them expect to at least double the amount of physical servers in their data centers by 2019.“We are seeing a continuation of the enterprise DC growth phase signaled by last year’s respondents and confirmed by respondents to this study. Enterprises are transforming their on-premises DC to a cloud architecture, making the enterprise DC a first-class citizen as enterprises build their multi-clouds,” wrote Clifford Grossner, senior research director in the cloud and data center research practice at IHS Markit.To read this article in full, please click here

[Sponsored] Short Take – Cumulus Networks

In this sponsored Network Collective Short Take, Pete Lumbis joins us to talk about how Cumulus Networks is offering a new disaggregated approach to network operations. There are some common concerns when it comes to a disaggregated model and in this conversation we focus on how Cumulus is making support, operations, and procurement fit within the models and experiences you are used to. All of this while still empowering engineers to take advantage of the power and flexibility that Cumulus Linux has to offer. For more information about Cumulus Linux, visit https://cumulusnetworks.com

 

Pete Lumbus
Guest
Eyvonne Sharp
Host

The post [Sponsored] Short Take – Cumulus Networks appeared first on Network Collective.

IDG Contributor Network: Machine learning takes a load off in network management

As networks become more software-driven, they generate vastly greater amounts of data, which provides some challenges: adhering to compliance and customer privacy guidelines, while harvesting the massive amounts of data—it is physically impossible for humans to tackle the sheer volume that is created. But the vast amounts of data also provide an opportunity for businesses: leveraging analytics and machine learning to gather insights that can help network management move from reactive to proactive to assurance. This doesn’t just mean a massive shift in technology because the human element won’t simply go away. Instead, by combining human intellect and creativity with the computing power AI offers, innovative design and management techniques will be developed to build self-improving intelligent algorithms. The algorithms allow networks to operate in a way that far outweighs networks of the past.To read this article in full, please click here

IDG Contributor Network: Machine learning takes a load off in network management

As networks become more software-driven, they generate vastly greater amounts of data, which provides some challenges: adhering to compliance and customer privacy guidelines, while harvesting the massive amounts of data—it is physically impossible for humans to tackle the sheer volume that is created. But the vast amounts of data also provide an opportunity for businesses: leveraging analytics and machine learning to gather insights that can help network management move from reactive to proactive to assurance. This doesn’t just mean a massive shift in technology because the human element won’t simply go away. Instead, by combining human intellect and creativity with the computing power AI offers, innovative design and management techniques will be developed to build self-improving intelligent algorithms. The algorithms allow networks to operate in a way that far outweighs networks of the past.To read this article in full, please click here

Independence, Impartiality, and Perspective

In case you haven’t noticed recently, there are a lot of people that have been going to work for vendors and manufacturers of computer equipment. Microsoft has scored more than a few of them, along with Cohesity, Rubrik, and many others. This is something that I see frequently from my position at Tech Field Day. We typically hear the rumblings of a person looking to move on to a different position early on because we talk to a great number of companies. We also hear about it because it represents a big shift for those who are potential delegates for our events. Because going to a vendor means loss of their independence. But what does that really mean?

Undeclaring Independence

When people go to work for a manufacturer of a computing product, the necessarily lose their independence. But that’s not the only case where that happens. You can also not be truly independent if you work for reseller. If your company specializes in Cisco and EMC, are you truly independent when discussion Juniper and NetApp? If you make your money by selling one group of products you’re going to be unconsciously biased toward them. If you’ve been burned or had Continue reading

IDG Contributor Network: 4 ways data science services is helping businesses reach IoT goals, faster

Data scientists are an essential part of an IoT deployment. They fill a critical need to interpret data and provide valuable context around machine learning. However, as IoT initiatives expand and mature in a business, in-house data science resources can become thinly stretched. This creates a data pile-up that is a surefire way to set your deployment back.Hiring more data scientists is typically not an option either as there is a significant shortage in the market. Demand is only going up too: Gartner predicts that a shortage of data scientists will hinder 75% of organizations from reaching their full potential with IoT through 2020. Because hiring is difficult, time consuming and expensive, many organizations are turning to data science services to fill in resource gaps. Outsourcing data scientists has the dual benefit of helping keep IoT initiatives moving forward while freeing up internal resources to focus on other areas of the business.To read this article in full, please click here

Technology Short Take 102

Welcome to Technology Short Take 102! I normally try to get these things published biweekly (every other Friday), but this one has taken quite a bit longer to get published. It’s no one’s fault but my own! In any event, I hope that you’re able to find something useful among the links below.

Networking

Security

Your IoT security concerns are stupid

Lots of government people are focused on IoT security, such as this recent effort. They are usually wrong. It's a typical cybersecurity policy effort which knows the answer without paying attention to the question. Government efforts focus on vulns and patching, ignoring more important issues.


Patching has little to do with IoT security. For one thing, consumers will not patch vulns, because unlike your phone/laptop computer which is all "in your face", IoT devices, once installed, are quickly forgotten. For another thing, the average lifespan of a device on your network is at least twice the duration of support from the vendor making patches available.

Naive solutions to the manual patching problem, like forcing autoupdates from vendors, increase rather than decrease the danger. Manual patches that don't get applied cause a small, but manageable constant hacking problem. Automatic patching causes rarer, but more catastrophic events when hackers hack the vendor and push out a bad patch. People are afraid of Mirai, a comparatively minor event that led to a quick cleansing of vulnerable devices from the Internet. They should be more afraid of notPetya, the most catastrophic event yet on the Internet that was launched by subverting an automated patch Continue reading
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