Tuesday, July 16, 2019

The IT Toolbox #005 - Thoughts on Cybersecurity

Define a set of cybersecurity rules.

Define an architecture (be it physical, platform and/or application).

Make sure the aforementioned rules can be applied.  (It doesn't matter if they are perfect, NONE are.)

Fix the rules or what the rules break.

For the love of all that is holy, PATCH in a reasonable amount of time.  (If you use a service provider, make it a contractual obligation and/or a Key Performance Indicator (KPI).)

Make sure there is a mechanism to verify the patches are in place.

Make sure there is a mechanism to verify FW rules are CORRECT.

Segment ALL applications.  Microsegment all unique elements of all applications.  Use SSL.

PATCH everything in a reasonable amount of time (yes, it's a repeat, but many don't hear it the first time).

Be prepared to burn down ANY exposure.  Have a plan in place in the event this must happen.

Have a reporting and notification plan in place.

When an exposure is identified (and it will be) make sure you use the reporting and notification plan.

If you EVER have to break ANY of the self imposed Cyberscurity rules, segregate and enclave to limit exposure.

Tuesday, July 9, 2019

The IT Toolbox #004 - Definitions #2

AI is not AI

AI is a marketing buzz word (ok it's an acronym (or even an Initialism), but bear with me)

Definitions of AI I've personally witnessed

     AI is stealing jobs (well, boring, repetitive, mind-numbing jobs)
     AI is Machine Learning (it can/could be, but mostly isn't...yet)
     AI is data processing (so is paper shuffling)
     AI is a Virtual Agent (actually partially true, at least the native language parts)
     AI is The Terminator (nope, that's a Movie, starring Arnold Schwarzenegger and on my must                                                  watch list)
     AI is Analytics (sorry, Analytics is Analytics, representations and uses of data)
     AI is a self driving car (hopeful a self driving car is more than AI, wishing for seats, engine, etc)
     AI is Deep Learning (might be true, how supervised is the learning?)
     AI is self service (well, ok.  Gives supermarket self checkout a new meaning.)
     AI is Robotic Process Automation (not so much as a set of response triggers, but bits could be)

If you’d like to read a thoughtful description of Artificial Intelligence, have a look at this Wikipedia article: https://en.wikipedia.org/wiki/Artificial_intelligence  (15 pages and 375 references, AND 18 disambiguation references)

So, if you're talking about Artificial Intelligence (AI), consider refining your definition and talking points to if there is (or is not) a neural network being trained in support of the mymicing of "cognitive" functions.

If not, call it what it really is rather what someone is marketing.

Wednesday, July 3, 2019

The IT Toolbox #003 - It is only a little off

IT is complicated ...

Here are some sensors:

Primary Adoption Strategy of Digital Transformation 1 
    (surveyed IT departments)

     34% - heterogeneous IT integration (basically picking parts that work for a particular purpose)
     27% - entirely public cloud
     24% - entirely private cloud
     16% - hybrid cloud

     Less than half of enterprises (surveyed) have a mature cloud adoption strategy

     12% - self report as mature
     37% - self report as somewhat mature

84% 2  of public cloud customers will repatriate some workloads to private infrastructure in 2019

Between 40% and 80% of enterprises will fail to deliver traditional workload on public cloud 3,1 

Enterprise Data Centers are closing - incorrect 4 

     Enterprise Data Center spending continues 5,6

x.86 Market growing at 19% 7 

Major x.86 vendors are growing market share and revenue 8 

There's a massive misunderstanding about the definition of the Digital Transformation end state. 9 

--  Publically available references --

Tuesday, June 25, 2019

The IT Toolbox #002 - Edge and Central

We often hear a reference to the ‘IT Pendulum’ but we should forget the idea that it is an all or nothing fight between good and evil.

The first point, it’s definitely NOT an all or nothing fight.  Each one of these technologies continues to exist today.

The more interesting thing that happens to make each of these relevant in their time is the abstraction and evolution pattern that occurs.

Consider this pattern:

Mainframes becoming remotely administered.                                                    Central -> Edge
Distributed computing replacing Remote Terminal (from mainframes)        Edge -> Edge
Client-Server replacing Distributed Computing                                                    Edge -> Central
Cloud Computing replacing Client-Server                                                              Central -> Central
Distributed Edge replacing Cloud Computing                                                       Central -> Edge

The Pattern consists of computing at the edge or in a central location.  Nothing really magical about that, but when a NEW technology comes in it’s almost always because we’ve either abstracted complexity away from the solution OR an evolution step in capability was enabled.

Take the case of Client-Server replacing Distributed Computing.  The effect was to move computing to a central location, this made possible largely by a significant increase in network bandwidth in the mid 1990s.  An example of an evolution pattern.

Cloud computing replacing Client-Server happened through an abstraction pattern.  Virtualization of computing systems allowed substantial recovery of compute investment.  It is also making smaller abstractions possible, think containers and serverless.  (also supporting one of my favorite quotes, from Rick Wilhelm @rickwilhelm, "Containers allow creation and destruction of application environments without drama or remorse.")

Effectively making the next evolution transition possible, moving workloads to the Distributed Edge, because … why should a programmer care where the program runs.

So, the IT Pendulum is only a pendulum if you look at it in two very myopic dimensions.  

The fight between good and evil, it isn't. It's evolution.

Tuesday, June 18, 2019

The IT Toolbox #001 - Definitions

It is vital that IT people communicate with the same lexicon.  This helps to establish definition which provides the specificity necessary to discuss complex topics.

The marketing engine, not to mention the general media, does little to correct ambiguity.  It can be argued that ambiguity in the marketing engine suffers ignorance in the hopes of capturing the next big headline.

This isn’t new.  Key terms do matter.  They are refined over time.

What makes matters worse, we often don’t know ~exactly~ what these terms mean until they are ingrained in a pattern that everyone comes to accept.

One of the best examples is Cloud Computing, “The Cloud” or just simply ‘Cloud.’

The problem with ‘Cloud’ is it doesn’t fit the definition of what everyone believes it to be.

The various definitions I’ve come across include:

Cloud is hosting on the internet.  (True-ish, but not very meaningful.)
Cloud is Infrastructure as a Service.  (It’s not only, but that’s OK.)
Cloud is Platform as a Service.  (A better definition, but also incomplete.)
Cloud is Cloud Native applications.  (This is about as ill fitting as Infrastructure as a Service.)
Cloud is Serverless.  (No, it’s not.  Never was, never will be.)
Cloud is where I’m moving all of our Enterprise Applications.  (That’ll be fun)
            Cloud is Digital.  (as in Digital Transformation, everyone talks about it, but few know how to                                           do it.)

If you’d like to read a thoughtful description of Cloud, have a look at this Wikipedia article: https://en.wikipedia.org/wiki/Cloud_computing  (16 pages and 125 references, 7 deployment models and 6 service models AND 23 disambiguation references)

What I’m getting at is that calling anything ‘Cloud’ lacks definition, its meaning has no precision what-so-ever.

Please make sure others know what you mean, when you say Cloud.

Monday, May 20, 2019

XXXX-as-a-Service aaS

The context of the utility to an as-a-Service capability in IT relies heavily on where the demarcation of use resolves.

It's much easier to see it in a graphical depiction.

In general, Infrastructure and a portion of the virtualization/abstraction are what will be acted upon by nearly all use cases (if we forgo the licensing issues with respect to those things more appropriately economical on bare metal).

On top of that you'd build out the as-a-Service for Infrastructure, which at the base level is virtualization/abstraction/operating system automation and management. 

Then you walk up the technology chain, including the management of constructs necessary for applications to be automated in build / test and delivery.

The last step on the technology chain is the delivery of what should be the most important element (though even today, we've people worried about HOW the underlying physical elements are doing), the Application delivery.

Delivery, SaaS, IaaS, PaaS, aaS
Tiers of 'as-a-Service' delivery

Friday, May 10, 2019

The Internet meme vs Cynefin

Stumbling across an interesting relationship can be interesting.  Was looking at a blog by Kees van der Ent on linked.in and realized that the header graphic could be related to Cynefin.

cynefin, meme, internet, strategy

Thanks to Dawn ONeil presentation on checkup.org.au, I was rapidly able to mock up the concept, meme to the Cynefin graphic, and it became apparent that there is a relationship.

In Cynefin, Complex Collaboration is all about "putting thoughts into words."  It has to be described to work with complexity.  Consider how absolutely wide the fields of Information Technology have become, things as simple as definitions and TLAs may not mean the same things to different technology backgrounds.

Without this specific step in the framework, it's is nearly impossible except through experimentation to achieve anything remotely close to education.

This lends itself heavily to cooperation, taking complex concepts and reducing them to something relatable.  Quite literally "what I say to other people."

Reducing disorder even further, is were understanding really takes hold.  Concepts are extracted, reduced and put in overlay or contrast in such at way that it becomes "what people actually understand."