Tuesday, April 28, 2015

A policeman in a Jar

What DevOps do?

This is a good question, no one dares to admit that she doesn't know

What is IT infrastructure?

The nicest explanation I learned from Otter Networks
The physical and organisational structures and facilities (e.g. buildings, roads, schools and hospitals ) needed for the existence of a society or enterprise.
In IT we can consider anything in a computer system that is not the application infrastructure. Application software is a set of one or more programs designed to carry out operations for a specific application. Application software cannot run on itself but is dependent on system software to execute.

A policeman in jar 

Image 1: A policeman in a jar, Bucharest 1969, when president Nixon visited Romania ruled by Ceausescu.
In  Romanian, it means "Un Militian la borcan". He was sitting inside that red and white "jar" cold in the winter, hot in the summer, and manually changed the lights from red to green and green to red according to his own mood or judgement. If he needed to go to a bathroom, he locked the jar with a key and visited a restaurant or a shop nearby, sometimes for hours before re-opening his jar.

When we emigrated in the West, people often asked: "Is it true that in Romania there are still policemen in a jar, changing manually the stoplights?"  "Yes", we said. And everybody laughed, At the time, there were almost no cars on the street, except public transportation and government officials Pobeda cars, The policeman-in-a-jar manual style of traffic control, worked, sort of.

Legacy Data Centers

Most of the data centers today are legacy data centers. They were not designed as Software Defined Data Centers (SDDC), Software defined Networks (SDN)  and Software Designed Storage (SDS),

In a matter on one year or so, all 2015 legacy Data Center will be laughed at, as Policemen in Jars. A change in infrastructure is a nightmare and the user experience or pleasure is no where in sight.
Image 2: Data Center Migration . The 2015 version of a policeman-in-a-jar

The power of DevOps

See below an excellent illustration from Dynatrace, one of the leading DevOps organization disguised as Performance Measurement people. They are much more than that.

Image 3: Self-explanatory, from  Dynatrace e-book

The results of DevOps

These achievements are attributed to DevOps. It all started with Flickr in 2009.
  • Flickr was one of the first to announce they were following DevOps principles with 10 deployments a day way back in 2009
  • TurboTax recently made 165 production changes during peak tax season resulting in 50% increase in website conversion rate.
  • Amazon deploys at an amazing pace: every 11.6s with 23,000 deployments a day. They have had 75% fewer outages since 2006, 90% fewer outage minutes, and only 0.001% deployments cause a problem
Now see these claims, impossible not to like and impossible to validate
30x more frequent deployments
8000x faster lead times than peers
2x the change success rate
12x faster mean time to recover
2.5x more likely to exceed profitability, market share and productivity goals
50% higher market capital growth over 3 years

Great. But how do you hire a DevOp?

 DevOps are hard to identify and hire. They are very smart guys. Each one uses different tools, software and skills to offer results, and one company is rarely compatible with another DevOps company. As a sesoned DevOp founder described his place in Europe
 in Berlin there is a thriving startup scene. Many of these fledgling companies are composed of a few guys; usually trying to work agile; putting together their application whilst simultaneously trying to work out how to use the AWS API and remember what the hell a subnet mask is meant to do.
These "fledgling companies" are magicians and show you miracles out of a black box. These are the kind of talent one can not hire, unless acquihiring their firms

A simple question

Does it make sense to stop trying to program data center infrastructure on equipment that was never designed for this purpose? It's amazing how the DevOps went beyond the "policemen-in-a-jar" stage, juggling with amazing skill. But there is a limit to it 
Image 4: The limit of Juggling

The Redfish Specification

This is what Dell, Intel, HP and Emerson are doing: A Datacenter Manageability fit for the 21st Century
Redfish is a modern intelligent manageability interface and lightweight data model specification that is scalable, discoverable and extensible.
Redfish is suitable for a multitude of end-users, from the datacenter operator to an enterprise management console.
I can write an imaginary blog entry when the new generation Redfish based, using Intel dis-aggregated hardware concept will make every developer a DevOps. They can program the infrastructure, the containers and the multiple operating systems as easy as coding apps today

Ericsson

From Otter Networks FreeIPA Technical Briefs
One of the main tenants of Cloud is the rejection of traditional IT practices. The big ITIL manuals went straight into the bin as agile teams rejected traditional system administration as a way of handling IT. This transformation has, for the most part, been extremely positive for Business. Business leaders no longer have to claw through a mountain of bureaucratic change control in order to get a new feature implemented
Ericsson response to this insightful observation is in this white paper  Ericsson Introduces a Hyperscale Cloud Solution based on HDS 8000 hardware platform
As the massive growth of information technology services places increasing demand on the datacenter it is important to re-architect the underlying infrastructure, allowing companies and end-users to benefit from an increasingly services-oriented world.
Datacenters need to deliver on a new era of rapid service delivery. Across network, storage and compute there is a need for a new approach to deliver the scale and efficiency required to compete in a future where “hyperscale” is a pre-requisite
Read the white paper.  I am not dreaming. 

 Disclosure

I don’t say anything online that I wouldn’t say in person. I am now an evangelist on contract to the Ericsson Cloud Product Team.  What I say are exclusively my thoughts, views, opinions or understanding of a topic or issue, and not my employer's. I can be wrong even though I try hard not to be. I will admit to mistakes, correct them promptly and even apologize where it is appropriate.

Sunday, April 05, 2015

We are in a boom again

The following data come from  a CB Insights guest blog from Cue Capital, It’s a Boom, Not a Bubble. The article is dated March 31, 2015

It substantiates with numbers what I wrote in May 2014, out in my blog What looks like a doom, is a boom .

The erratic valuations disappeared

Figure 1: 2015 versus 2000 Top Nasdaq Price Earning
Yahoo with  earnings 418 times the valuation in 2000 is no longer in the top 10 list. Oracle bought Sun only to disappear both of them from list. Dell is gone. Companies that did not exist before in 2000 like Google and Facebook top the list in 2015. Apple had a fabulous renaissance. Cisco made it on the list, but bruised with PE ratio 10x lower

NASDAQ index is back to the 2000 level

Amazing: it took 15 years, but we did it and looking at the PE ratios, all is toned down. The investors are more educated, yet now seems the NASDAQ is solid.

Figure 2: NASDAQ is back to 2000 level

Amazing difference in top NASDAQ companies by market cap


Figure 3:Nasdaq  Market Cap ranking 2015 versus 2000

Big Data was a stumbling block to take decisions

In another entry on this blog:  From Big Data to Big Decisions
    I quoted the opinion of Larry Fink,  the CEO and Chairman of the largest asset management firm in the word, Blackrock (three and half trillions dollars under their administration)
  1. The markets in America reflect a lot of fear. We are bombarded with information that we can not make sense out of it. We can't decide whether this  Big Data information  is good or is bad.
  2. As a result every CEO, government decision maker handling money only invests short term.  Some CEO's buy back shares to invest the cash in government bonds at 2% interest rate. Companies sit on lots of cash, too afraid to spend it. 
  3. Banks have tons of money, they sit in the vaults without making loans. The banks want to make loans, but say someone who qualified for a loan in 2007, does no longer qualify. The companies who qualify, they do not need any loans as they have tons of cash already.
  4. The main inhibitor, it is worth repeating, is not Big Data itself. It is the fear of it. The top decision makers in our society, the CEOs and the Government economists, are unsure how this big data can be used.
 Define speed as "How quickly we can go from data to decisions?", said one young founder of a big data company. But this speed is only partially dependent upon technology.After all the price of a security is determined by our belief that will go up

Future traps and future hopes

I am thinking of the buyers of Hortonworks stock, who have not a clue what Hadoop is. Or the new container technology, like Docker, CoreOS. The public, and even some VCs don't understand this technology well enough.

But there is a new generation of investors who are just as innovative, if not not more innovative than the entrepreneurs they fund. Peter Thiel,, Elon Musk in general all the so called PayPal mafia entrepreneurs.

The recent invention of  incubators  made successful entrepreneurs from nice school kids The side effect is the creation of new type of successful entrepreneurs, young, arrogant, what David Brooks describes as "avatars of success" who never faced any obstacles in life and never hit their heads into a wall.
They got 3.8 grade-point averages in high school and college. They served in the cliché leadership positions on campus. They got all the perfect consultant/investment bank internships. During off-hours they distributed bed nets in Zambia and dug wells in Peru.
 When you read these résumés, you have two thoughts. First, this applicant is awesome. Second, there’s something completely flavorless here. This person has followed the cookie-cutter formula for what it means to be successful and you actually have no clue what the person is really like except for a high talent for social conformity. 
These avatars of success  are bound to fail one day, as humans inevitably do and learn what we already know

Figure 4: What incubator entrepreneurs should learn
If they don't learn this, the sameness of the new incubator companies success may trigger another bubble in the future.

The Unicorns

Quote from Cue Ball Report
 There are a record number of startup “unicorns” – VC-backed companies valued at over $1Bn – in existence, including well-known names such as Uber, AirBnb, and Dropbox.  Altogether, as of this writing, there are now 78 unicorns, and more than 20 of them reached this milestone in just the past year.
Figure 5: The Unicorns 2014 (see text above)
The #1 Unicorn is Xiaomi, who are based in China. They are an Apple me-too. This questions for how much longer Apple will maintain leadership just making phones and pads, when Xiaomi can do the same things at lower investments for highest valuations? Uber is an internet taxi service and can be displaced by a competitor anytime. Palantir is not an incubator company, and it is the most solid among the top 20 Unicorns. Yer Airbnb, Dropbox, Snapchat are incubator born.

According to a thread in Quora What's the success rate of startups that have been funded by Y Combinator? "There are anywhere between 404 and 468 startups that have been funded by Y Combinator. There are also three states for a Y Combinator funded startup: Exited, Operating and Dead"

The update daily picture is here
Figure 6: Data updated daily on this web site 
This shows an impressive 75% of the Y Combinator startups still active. However  nearly 75% of the total value of companies they have funded is accounted for in two big players (Dropbox and Airbnb)

This to me is about sieving sands from Sacramento river looking for gold

The next mind blowing success investments (like Google)  will come from non-conformists and underdogs , not from incubators.

Wednesday, April 01, 2015

Ericsson cloud factories and historical cloud definitions

What is  cloud computing?

This blog turned ten years old  this month. Over the years we have different evolving answers to this simple question. Here is a chronological list of the most popular cloud definitions as I see it.

The 2009 definition from Cloud Computing discussion group

From Nati Shalom blog, (I was a contributor too)
There are two main driving forces for Cloud-Computing:
1. On demand computing i.e. the ability to get a resource when I need it in matters of minutes.
2. Pay-per use i.e. the ability to pay only for what I use.
The rest is implementation detail.

NIST cloud computing  definition 

NIST (The National Institute of Standards and Technology)  cloud definition expanded over the years to  two pages. I just quote the beginning here:
Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics, three service models, and four deployment models.
This is most accurate, long, academic, monotonous definition of cloud computing. It is good definition to teach students Cloud Computing 101

It overlooks the simple fact that  Cloud Computing is a business model. I know many people who asked: Why should we use any other definition?  Because one can not build a business reading it.

Amazon Web Service Cloud Computing Definition

"Cloud Computing", by definition, refers to the on-demand delivery of IT resources and applications via the Internet with pay-as-you-go pricing.
This is a much shorter definition applicable right away in practice  It is a business model  definition.

But what business model? AWS defines a business model for the maximum Amazon benefits. It says, I (Amazon) offer the infrastructure, to you  (the customer) to run your apps. You pay me (AWS) for the usage. I set my pricing, it is up to you, Mr. Cloud Customer to figure out how to make money.

Amazon cloud computing definition is practically the same with definition from 2009 Cloud Computing group. The great differentiator is that they actually tell you how to do this step by step, in the next paragraph after  their definition

The dominant Cloud Computing perception  is inspired from AWS success

Now the popular belief is that a cloud is what Amazon does, We are convinced that the AWS business model is equivalent to the word "cloud"

See the post  The winners of 2014 Cloud IaaS Gartner Magic Quadrant     Gartner modified the definition of the cloud (they call it IaaS Cloud) to fit AWS business model:
We draw a distinction between cloud infrastructure as a service, and cloud infrastructure as a technology platform; we call the latter cloud-enabled system infrastructure (CESI). In cloud IaaS, the capabilities of a CESI are directly exposed to the customer through self-service. However, other services, including noncloud services, may be delivered on top of a CESI; these cloud-enabled services may include forms of managed hosting, data center outsourcing and other IT outsourcing services. In this Magic Quadrant, we evaluate only cloud IaaS offerings; we do not evaluate cloud-enabled services
There is no surprise why Amazon is the absolute market leader in Cloud-IaaS Gartner quadrant

A metaphor

One metaphor is that AWS cloud definition is like the parallel postulate of Euclid. A mathematician must be crazy to challenge something so obvious.  But this is exactly what happened to the mathematician Janos Bolyai 
He became so obsessed with Euclid's parallel postulate that his father wrote to him: "For God's sake, I beseech you, give it up. Fear it no less than sensual passions because it too may take all your time and deprive you of your health, peace of mind and happiness in life". János, however, persisted in his quest and eventually came to the conclusion that the postulate is independent of the other axioms of geometry and that different consistent geometries can be constructed on its negation.
He wrote to his father: "I created a new, different world out of nothing."
This world was the non-euclidean geometry.

Every new business model for cloud computing must have its own definition, based on facts no one noticed before

Ericsson Cloud Fundamentals

You can have a look at the new Ericsson White Paper Next Generation Data Centers Infrastructure

According to a Reuters press release
 Over the past decade Web-based services like Google, Facebook, Amazon and Microsoft have stopped buying finished computers, storage devices and network components and instead developed their own systems in-house to create massive, low-cost datacenters in the cloud to serve billions of users.
None of Google, Facebook and Amazon like companies buy external IaaS resources. They are self-sufficient . So why many Fortune 2000 companies can't do the same?
CIO are thinking today how to begin to modernize the end-to-end IT infrastructure, so it can be a factory. Once this happens, it can generate top-line revenues for the company and it could be a strategic differentiator.
The next generation cloud  and will give organizations the platform they need to transform from a sense of “deploy and hope” to one of trust and security
This video below features Jason Hoffman, CTO Ericsson Cloud Computing. He explains the Ericsson Cloud Fundamentals in more detail.


Disclosure

I don’t say anything online that I wouldn’t say in person. I am now an evangelist on contract to the Ericsson Cloud Product Team.  What I say are exclusively my thoughts, views, opinions or understanding of a topic or issue, and not my employer's. I can be wrong even though I try hard not to be. I will admit to mistakes, correct them promptly and even apologize where it is appropriate.

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