Category: IoT

Business · CIO · Cloud · IoT

The five most popular posts of 2016

Tim Crawford1 Comment

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While 2016 is quickly coming to a close, it offers plenty to reflect on. For the CIO, IT organizations and leaders who work with technology, 2016 offered a glimpse into the future and the cadence in which it takes. We learned how different industries, behaviors and technologies are impacting business decisions, societal norms and economic drivers.

Looking back on 2016, here is a list of the top-5 posts on AVOA.com.

#5: Understanding the five tiers of IoT core architecture

In this July post, I suggest an architecture to model IoT design and thinking.

#4: Changing the language of IT: 3 things that start with the CIO

This May post attracted a ton of attention from CIOs (and non-CIOs) as part of their transformation journey.

#3: IT transformation is difficult, if not impossible, without cloud

Another May post on the importance of the intersection between transformation and cloud.

#2: Microsoft Azure Stack fills a major gap for enterprise hybrid cloud

Only one of two top-five vendor-related posts digs into the importance of Microsoft’s hybrid cloud play.

And the #1 post…

#1: Is HPE headed toward extinction

This provocative post looks at business decisions by HPE and how they impact the enterprise buyer.

2017 is already shaping up nicely with plenty of change coming. And with that, I close out 2016 wishing you a very Happy New Year and an even better 2017!

Business · CIO · Cloud · IoT

Three things to look for at Amazon’s upcoming AWS re:Invent conference

Tim CrawfordLeave a comment

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As folks in the US prepare for the Thanksgiving holiday, those of us in technology are looking to Amazon’s annual cloud confab AWS re:Invent the week after Thanksgiving in Las Vegas. In preparation for the sold-out conference, there are a few things to look for at the conference.

ENTERPRISE ENGAGEMENT

Amazon has done a good job of attracting the Webscale and Startup markets. One could go so far as to say that Amazon has cornered these markets. For these folks, the options are wide open to address their specific and scaling requirements. The requirements for enterprises, however, are vastly different from their webscale and startup counterparts.

Look for indications that Amazon is starting to learn how to engage enterprises and is moving in that direction. The method, language and solutions vary greatly when considering a prospective customer that has an existing footprint over those that are looking to build their first.

INTELLIGENCE: AI & MACHINE LEARNING

Amazon already has a Machine Learning solution in their portfolio today. Look for further expansion beyond just tools and into the realm of intelligence. Amazon has done a great job of create a bevy of infrastructure tools. However, moving into the intelligence space is both necessary and the logical next step in maturing Amazon’s position in this market. Also, look for Amazon’s response to the growing interest in AI solutions. In addition, the combination of AI & Machine Learning is paramount to more mature IoT solutions.

MOVING UP THE STACK

To date, most of Amazon’s portfolio targets the infrastructure end of the stack. There are a few solutions that move up the stack, but not many. Even so, Amazon has done a stellar job of their existing efforts. If, however, Amazon is intending to capture more of the enterprise market and move beyond being simply a tool provider, it needs to move up the stack into the application realm. To date, it is not clear if Amazon has both the capability and strong interest to do so.

Across the board, Amazon’s competition may not have the depth in IaaS cloud that Amazon has today. Nor do they have the ecosystem that Amazon has worked hard to build over the past 10 years. However, what they lack in IaaS depth is countered by their breadth up and down the stack. And while they may lack the breadth of features in the IaaS space compared with AWS, each are quickly catching up and are posting impressive growth rates.

Next week should provide another exciting event for Amazon and those working in the Cloud space. Whether coming from the startup, webscale or enterprise space, all eyes are on Amazon and their next move.

Cloud · IoT

Understanding the five tiers of IoT core architecture

Tim Crawford3 Comments

Internet of Things (IoT) is all the rage today. Just tagging something as belonging to the IoT family brings quite a bit of attention. However, this tagging has also created quite a bit of noise in the industry for organizations trying to sort through how best to leverage IoT. Call it IoT marketing overload. Or IoT-washing.

That being said, just about every single industry can leverage IoT in a meaningful way today. But where does one begin? There are many ways to consider where to start your IoT journey. The first is to understand the basic fundamentals of how IoT solutions are architected. The five tiers of IoT core architecture are: Applications, Analytics, Data, Gateway and Devices. Using this architecture, one can determine where any given IoT solution fits…and the adjacent components required to compete the solution.

THE FIVE TIERS OF IOT CORE ARCHITECTURE

  • DEVICE TIER

The device tier is the physical device that collects data. The device is a piece of hardware that collects telemetry (data) about a given situation. Devices can range from small sensors to wearables to large machines. The data itself may be presented in many forms from electrical signals to IP-data.

The device may also display information (see Application tier).

  • GATEWAY TIER

The sheer number of devices and interconnection options creates a web of complexity to connect the different devices and their data streams. Depending on the streams, they may come in such diverse forms as mechanical signals or IP-based data streams. On the surface, these streams are completely incompatible. However, when correlating data, a common denominator is needed. Hence, the need for a gateway to collect and homogenize the streams into manageable data.

  • DATA TIER

The data tier is where data from gateways is collected and managed. Depending on the type of data, different structures may be called for. The management, hygiene and physical storage of data is a whole classification onto itself simply due to the four V’s of data (Volume, Variety, Velocity, Veracity).

  • ANALYTICS TIER

Simply managing the sheer amount of data coming from IoT devices creates a significant hurdle when converting data into information. Analytics are used to automate the process for two reasons: Manageability and Speed. The combination of these two present insights to the varied complexity of data coming from devices. As the number and type of devices vary and become increasingly more complex, so will the demand for analytics.

  • APPLICATION TIER

Applications may come in multiple forms. In many cases, the application is the user interface that leverages information coming from the analytics tier and presented to the user in a meaningful way. In other cases, the application may be an automation routine that interfaces with other applications as part of a larger function.

Interestingly, the application may reside on the device itself (ie: wearable).

IoT Architecture

 

Today, many IoT solutions cover one or more of the tiers outlined above. It is important to understand which tiers are covered by any given IoT solution.

CLOUD-BASED IOT SOLUTIONS

Several major cloud providers are developing IoT solutions that leverage their core cloud offering. One thing that is great about these solutions is that they help shorten the IoT development time by providing fundamental offerings that cover many of the tiers outlined above. Most of the solutions focus on the upper tiers to manage the data coming from devices. Three such platforms are: Amazon AWS IoT, IBM Watson IoT, and Microsoft Azure IoT Suite. Each of these emphasize on a different suite of ancillary solutions. All three allow a developer to shorten the development time for and IoT solution by eliminating the need to develop for all five tiers.

THE SECURITY CONUNDRUM

One would be remiss to discuss IoT without mentioning security. Security of devices, data elements and data flows are an issue today that needs greater attention. Instead of a one-off project or add-on solution, security needs to be part of the DNA infused in each tier of a given solution. Based on the current solutions today, there is a long way to go with this aspect.

That being said, IoT has a promising and significant future.

Data · IoT

The intimacy of Internet of Things along with security and privacy

Tim CrawfordLeave a comment

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Internet of Things (IoT) is hot. Really hot! Every single industry from buildings to healthcare to financial services is looking at IoT. As more and more organizations look to capitalize on the blistering IoT market, they…and consumers risk the equivalent of ‘running with scissors’ when it comes to security and privacy.

PERSONALIZING MECHANICAL DATA

IoT presents a number of new sources of data. Some of that data is mechanical and non-personal in nature. A good example is machine data from sensors in a data center. The sensors tell a story about how the data center is performing. Those sensors may include electrical equipment, temperature sensors, airflow and water consumption.

However, some machine data can be personalized to provide insights to a person’s behaviors. An example in the Retail industry might be sensing how many times a person enters a store, the path they take within the store and ultimately what they purchase. In an office building, it may be telemetry around movements of people in/ out of the building, use of the restroom, meeting rooms and the like. At home, it might be temperature settings, entering through the garage door, turning on/ off lights.

The fact is: sensors are everywhere and organizations are starting to correlate the data from those sensors to people behaviors. Now, while most have the best intentions on integrating this data (creating better work environments, automating efficiencies, understanding purchase decisions, etc), it does bring up the question of how data is used.

THE INTIMACY OF WEARABLES

Adding to the data streams from machine data, there is a large source of IoT data is coming from personal devices including those we wear or wearables. And in some cases, this data is being correlated with machine data to provide even more personal automation.

The data coming from wearable devices is interesting…and personal. How personal? Very personal. Sure, wearable devices can register your exercise, activity patterns and sleep patterns. They can also tell when you have elevated heartrates and swift movements. It essentially starts to identify patterns…even intimate patterns. Start to marry this data with other data around location, purchase habits and you start to see how the data streams can be very telling. For example, one could surmise with accuracy what products were purchased before and after certain activities which in turn could provide a very personal perspective on the person.

Now imagine if that data or those patterns were made public. One starts to see how the privacy concerns about our behaviors (intimate or otherwise) quickly become apparent. That is not to say that we should avoid IoT and wearables.

SHIFTING FROM AN AFTERTHOUGHT TO CORE

The obvious solution is to take care with the data and understand how it is used. As with many technology solutions, the security of the device and the data often comes as an afterthought. Unfortunately, IoT is following in those well-understood footsteps.

Security often flies in the wind to avoid constricting innovation and speed to delivery. This is true across the strata for IoT from devices through gateways and all the way to applications. It seems that privacy and security is a routine subject for IoT. Privacy and IoT are not new challenges for innovation in its infancy. The level and intensity of interest in privacy is starting to reach a feverish pitch as device users start to consider the implications.

The issues are not just around wearables either. The same issues reside for corporate IoT solutions that start to understand and react to user behaviors. Even the historically most mundane things, like a building, are starting to get a personality. The personality of the building is starting to understand the behaviors of its users. No longer is security and privacy relegated to only newer solutions.

Now is the time to stop thinking of security and privacy as an afterthought. It is possible to infuse both into each step of the process. It requires a change in the culture and way that solutions are developed. Consumers can help drive these changes through their buying habits. Look for solutions that take security and privacy seriously. End-users, whether corporate or consumer have the best opportunity to impact change.

Business · Cloud · Data · IoT

The role of Open Source and Foundations in Enterprises

Tim CrawfordLeave a comment

I had the pleasure of joining a panel discussion that included several instrumental folks including Duncan Johnston-Watt, Sam Ramji & Monty Taylor on the role of the foundation. Without getting too far into the nitty gritty, there were some very interesting themes that came up…of which I will try to summarize here.

MATURITY OF ENGAGEMENT

Many of the foundations are working with Open Source Software as a means to bring collaboration and organization to a collective of like-minded folks. In many ways, the role of the foundation is to bring organization to chaos.

During the conversation, a core conversation topic is the maturity model of engagement for customers. The model encompasses a number of different attributes. One of which is the relationship between individuals, foundations and commercial organizations.

Software Maturity Spectrum

 

One of the big misnomers with Open Source Software is that it is free. Open Source Software is not free. As one panelist equated: taking software without paying (or contributing back) is theft. At the opposite end of the spectrum is commercial software where a commercial agreement outlines the exchange of software for money. And, of course, there are a myriad of different attributes in between.

While this is only one way to slice the conversation, there are many ways in which one could look at how individuals engage with Open Source Software and how it, in turn, relates to foundations.

THREE COMPLEXITIES TO FOUNDATIONS

Each foundation follows a varied mission. However, there are three facets that often cover the core aspects of the foundation’s mission: Political, Economic and Technical. Many foundations will focus on the technical attributes without consideration of the economic nor political components. Unfortunately, only focusing on one facet leads to challenges that will manifest in a number of ways.

Not all foundations will, or need to, serve each of these dynamics. However, there is a reality setting in that the majority of foundations will need to address each of them in order. To ignore one or two (ie: political or economic) provides a significant, if not unsurmountable challenge.

FOCUS ON THE VALUE

In the end, foundations are complex. For the enterprise, it is important to understand the role of the foundation and how it aligns with your own vision and needs. It is important to find the appropriate ways to engage in a collaborative fashion.

CIO · Cloud · Data · IoT

2016 is the year of data and relevance

Tim Crawford2 Comments

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Over the past few years, I have outlined my thoughts for the upcoming year. You can read those from past years here:

Cloud Predictions for 2013 (12/14/12)

CIO Predictions for 2014 (12/20/13)

5 things a CIO wishes for this holiday season (12/26/14)

In 2016, data and relevance will play the leading role across the industry. Data and relevance are not necessarily new, but are providing something new to each of the hot technology areas.

THE YEAR OF DATA AND RELEVANCE

Two core trends came to light during the latter half of 2015; data and relevance. While innovation and experimentation are hallmark components to growth, data and relevance lead to one clear message for 2016: Focus. And it is this very focus that will provide opportunity to buyers and providers alike.

In the past couple of years, we saw new solutions and methods to collect data. In 2016, organizations will hone their craft in how data is collected and used. This is easier said than done as there are still technological and cultural boundaries to overcome. However, 2016 brings a renewed focus on the importance of data from all aspects.

Over the same past few years, a myriad of novel and clever solutions overwhelmed us. 2016 brings forth a drive to focus on those most relevant to our needs; both today and in the future. As part of this focus, look for continued consolation.

2016 SIDENOTES

There are two areas that I suspect will influence activity among buyers and providers alike in 2016. One of those is the economic impact of changes in economies, industries and geopolitical areas. The second has more to do with the specific matchups, consolidations, mergers, acquisitions and folds that take place. The early half of 2016 should be interesting as many were already teed up in the latter half of 2015.

The hot areas for 2016 continue to be Cloud, Data, IoT, Software, Infrastructure and Security.

  • Cloud: Look for enterprises to continue their adoption of cloud as they 1) get out of the data center business and 2) provide leverage to do things not otherwise possible.
  • Data: As mentioned above, the drive for greater data consumption will continue. Look for enterprises to start to understand the relevance of data as it pertains to their business (today and in the future).
  • IoT: Enterprises across a wide range of industries are looking to capitalize on the Internet of Things movement. The value and interest in IoT will only continue to grow through 2016 as enterprises find novel ways to leverage IoT to grow their business.
  • Software: The world of enterprise software continues to evolve. Enterprises continue to move away from large, monolithic applications to applications more directly focused on their industry or area of need. This presents a great opportunity for incumbent enterprise players as much as new entrants.
  • Infrastructure: The infrastructure world is being turned on its head and for good reason. Look for changes in the paradigm of how infrastructure is leveraged. The need for infrastructure is not going away…but how it is consumed is completely changing.
  • Security: While a perennial subject, look for security to weave a path through each of the areas above as organizations begin to focus on how to best leverage (and protect) their assets. For many, their core asset is data.

HAPPY NEW YEAR! HERE’S TO A PROSPEROUS 2016!!!

We all have quite a bit to look forward to in 2016! Change is in the wind and it will continue to provide us with opportunity. Here’s to it bringing great tidings in 2016!

Cloud · Data · IoT · Mobile

Intel playing a key role with Cloud, Mobile, IoT & Analytics

Tim CrawfordLeave a comment

In the past couple of weeks, I spent time with the Intel team in Oregon to see their work in leading areas including Cloud, Mobile, Internet of Things (IoT) and Analytics. Before I get too far down the path, one may be asking what Intel, a chip manufacturer, is doing in some of these areas. As it turns out, Intel is actually one of the largest software developers today. Intel also plays a leadership role in driving adoption and bridging the gaps in these leading areas.

SUPPORTING THE MOVE TO CLOUD

Today, 75% of current cloud demand comes from consumer services. By 2020, 65-85% of applications will be delivered via cloud infrastructure. The key for Intel (and others) is to move from consumer applications to enterprise applications. Intel’s approach is to leverage Jevon’s Paradox. The easier computing is to access, the faster the adoption. One of the key areas Intel is working on is orchestration software that is transparent vs. opaque.

Simply put, the industry is simply not moving fast enough. Friction exists in several key areas with adoption:

  • Fragmented solution stacks
  • Complexity in deploying solutions
  • Lack of key features

While these may seem straight forward, the path is not always the most direct. Intel IT is a great test bed of methodology, technology and culture. Today, any developer in Intel IT can go request their own instance for compute & storage.

One of the areas related to cloud is Intel IT’s move to Software Defined Networking (SDN). Prior to SDN, the process of Landing, Security Setup (ACL), Load Balancing and Auto IP Provisioning took an average of 31.99 days(!). After SDN, the process is nearly instant. The biggest challenges were Immature Technology (71%), Existing Network/ Processes (64%), Lack of Knowledge/ Training (29% and Cost (25%).

To Intel, cloud is not the end-game and does not see enterprises completely divesting of data centers. Intel’s perspective is that every CIO wants to get to a hybrid cloud scenario.

ENGAGING IN THE MOBILE ECOSYSTEM

Today, there are 1.9 billion smartphones. Each smartphone has an average of 26 applications. Each application has (on average) 20 transactions with a data center every day. That turns into 1 trillion data center transactions…every day!

Imagine the challenges of scale using traditional data center technologies. The sheer amount of data, let along transactions, is massive. And this is just what we see from the mobile endpoints.

THE INTERNET OF THINGS (IoT)

There is a significant opportunity for any of the IoT players by turning data into value. With 50 billion ‘things’ and 35 zettabytes of data, there is quite a bit of upside for even the most narrowly focused of companies. Intel is working with companies to enable the two categories of the IoT.

THE DATA AND ANALYTICS OF CANCER RESEARCH

One example is Intel’s partnership with Oregon Health & Science University (OHSU) to assist with their cancer research programs. OHSU is one of the country’s leading cancer research institutions. Intel has engaged with OHSU on multiple levels. However, one of the core activities when doing cancer research is genome sequencing.

Today, a single patient genome generates more than 1 terrabyte of data. That’s 1TB+ per patient. With 1.65 million cancer patients in the US alone, that equates to 4 exabytes of data for genome sequencing. Today, <1% of cancer patients are actually sequenced due to a number of issues including costs. Imagine if all cancer patients were sequenced. Now imagine if patients for other diseases were sequenced. One can quickly see that we are just scratching the surface on data analytics in healthcare and have a long way to go!

SUPPORTING THE OVERALL EFFORT

As the scale for workloads moves from rack-scale to larger, specialized implementation, Intel is ready with custom silicon. Cloud providers, such as Amazon AWS, have already taken this approach to leverage a myriad of features that best support their service offering. Expect others to follow suit as their scale increases.

 

Today, the breakdown of Intel’s market by workload is as follows:

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It is impressive to see how much of the workload pie is squarely focused on technical computing today. Consider how this will change as the adoption rate of cloud and analytics increases.

All that being said, Intel’s core is still building infrastructure technology. Their new 3D xPoint memory technology is about to turn the industry on its head. Consider that xPoint addresses many of the concerns with NAND memory today and presents significant opportunities for applications in need of low latency, fast system recovery and high-endurance. Large in-memory databases, gaming and genomics analysis are just a few of the leading contenders that will benefit from 3D xPoint memory technology.

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In summary, Intel is far from just a ‘chip manufacturer’. They are constantly innovating their silicon expertise while taking a leadership role in many of the hot technology areas. While many still struggle with basic block-and-tackling of cloud adoption, there are many significant opportunities that lie ahead of us both commercially and personally.