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CTOvision Experts Know The Cloud And How It Can Help You

In many ways the megatrend of Cloud Computing is driving all the other megatrends.
Cloud-Computing-Service
Cloud computing refers to the on-demand provision of computational resources (data, software) via a computer network, rather than from a local computer. In general this is a pay-as-you-go approach delivered via the Internet, but private clouds and other enterprise approaches are also key.

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When it it time to research the great providers of cloud computing capabilities, kick off your search in the CTOvision Disruptive Technology Finder, where you will find a special section devoted to incredibly functional Cloud Computing companies.
For help putting all this information into context for your business, consider tapping into Crucial Point's CTO-as-a-Service or Technology Due Diligence offerings, both are ways to quickly leverage the technical talents of experienced enterprise technology professionals.

Bill Vass Presents On The Extended Cloud, AWS powers edge-to-cloud applications

Bill Vass is someone I regard as “The CTO’s CTO.” He is a business and technology leader who creates visions and marshals resources to turn those visions into reality. He is also a good explainer and is known for providing helpful insights that end user CTOs and CIOs can use to drive their decisions.

The video here is a presentation by Bill that provides an high level overview of AWS edge computing solutions and how these connect to and leverage AWS Cloud.

AWS edge computing solutions provide infrastructure and software that move data processing and analysis as close to the endpoint where data is generated as required by customers. In this session, learn about new edge computing capabilities announced at re:Invent and how customers are using purpose-built edge solutions to extend the cloud to the edge.

For more see: Amazon

 

Latest CTOvision Assessments on Cloud Computing, Artificial Intelligence, Mobility, Big Data, Robotics, Internet of Things and Cybersecurity

One of the enjoyable things about estimating the future is there is always a new consideration. It is a dynamic task that is never done. This is especially true in analyzing the future of enterprise technology, where things are always moving fast.

We try to find balance in tracking the future of technology by focusing on the metatrends, those very powerful forces that sweep over us all (whether we want them to or not). Megatrends change, but not as fast as the rapidly changing offerings of the tech ecosystem. This allows us to make predictions with a bit more certainty than trying to predict which product or solution or company will dominate. This approach enables a degree of certainty supportive of most strategic planning efforts, even if it does not provide precision around timing or exact manifestation of solutions.

Find our Reports on the Business of Technology at:

As you leverage our special reports keep in mind that we focus on the business impact of technology, and that very often leads us to discussion about the high tech firms bringing technology to enterprises. There are two other big concepts we want you to think about as you consider high tech firms, both come from the world of biology.

The two constructs from biology to think about regarding enterprise tech are: The Cambrian Explosion and a Malthusian Problem.

The Cambrian Explosion is was a period of rapid evolution and an explosion of life. The Cambrian Explosion began around 542 million years ago. Every living plant or animal today can trace its roots to the startups that began then.

A Malthusian Problem is when a population has outpaced the amount of resources required to support the population, resulting in catastrophe for most. The Malthusian Problem was articulated by Thomas Malthus in 1779 based on observation of famine, and, although Malthus never seems to have had an accurate prediction regarding human population growth and sustainment, he made a pretty clear case that if a population grows too large the result can be catastrophe.

In enterprise IT we have seen the Cambrian Explosion part of this equation, with 1,000’s of companies existing to address enterprise tech needs.

Will the Malthusian Problem part of this equation kick in? If it hits, which tech providers will thrive and which will perish? And what should the enterprise CTO do about it?

These are open questions of course. But if you ever have any context you can share on their answers or what we should do about it please let us all know!

As we track these topics we will continue providing our context here and in our tech directory. Be sure you are signed up to our daily and monthly reports for updates. Do that at: https://ctovision.com/newsletter-subscriptions/

 

Other Insights and Reporting for the Enterprise Technologist:

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And for assistance in applying these trends to your business see:

Track the most disruptive technologies by diving into our categorized index:

Artificial Intelligence Companies – A fast overview of Artificial Intelligence companies we believe are poised to cause the most positive disruption in the enterprise.

Big Data Companies – Reference to the greatest, most disruptive Big Data companies in the tech ecosystem.

Business Intelligence Companies – We assess these to be the Business Intelligence Companies most impactful for delivering real decision advantage.

Cybersecurity Companies – We apply our deep expertise in cybersecurity to assessing the best across multiple categories including:

Cloud Computing Companies – We include both platform and software as a service providers, capturing only the most innovative and disruptive.

Collaborative Tool Companies – These are the firms that help humans connect to humans to create, manage and lead.

Infrastructure Companies – Critical enterprise foundations for business agility.

IoT Companies – Internet of Things and Industrial Internet of Things are here. How do you manage them?

Mobile Companies – Help manage, configure, secure and optimize these very powerful capabilities.

Robotics Companies – Including innovations in Robotic Process Automation, Drones, and industrial robotics.

Services Companies – We only track a few, the ones we really know well.

Tech Titans – These are the big players. We track the tech titans closely since their capabilities change continuously.

VC, PE and Finance Companies – Keeping an eye on the investors can give indications of coming developments.

You can also use our topical pages to get up to speed quickly on the current status of the major megatrends. See our pages on Cloud Computing, Artificial Intelligence, Mobility, Big Data, Robotics, Internet of Things, Cybersecurity and Blockchain and Cryptocurrencies.

We also provide special pages focused on high interest topics, including Science Fiction, Entertainment, Cyber War, Tech Careers, Training and Education and Tech Tips.

CTO Guide To The Business of Cloud Computing

This is the CTOvision guide on the megatrend of Cloud Computing. This report gives a high level overview of the most important factors of the trend, gives updated insights into the activities of the major Cloud Computing companies, and succinct descriptions of Cloud tech. It also points to key CTOvision reporting to help readers dive deeper into the topic.

What Is Cloud Computing?

We succinctly describe Cloud Computing as the scalable delivery of computational resources. Models of cloud compute include public clouds, private clouds and blends in between. Architectures are in place now that leverage tiers of clouds that can exist in multiple sizes and locations, including homes, businesses and datacenters.

Key Observations:

  • Although it can cost additional resources to embark on a cloud transition effort, in most cases after initial outlays there are significant cost savings. Commercial Cloud Computing providers are know widely known for their revising costs down and we see that trend continuing.
  • A new consensus is forming regarding security and cloud capabilities. Well engineered clouds can be far more secure than the typical Internet connected enterprise. A favored technique for enhancing enterprise security in a way that supports cloud computing models is a Software Defined Perimeter (SDP).
  • Agility of the Cloud Computing model is helping innovators innovate and developers develop, and in many cases this is the greatest benefit of the approach. Agility in service to mission and business needs is far more important than cost savings.
  • New forms of Cloud Computing include ultra-small data centers which can function as internal clouds. Versatile small form-factor data centers can be bought in containers and put anywhere.
  • Cloud plus IoT = Fog Computing, an architecture of multiple collaborative end compute devices. The term Fog Computing might never take off the way Cloud Computing will, but consider the new model regardless of what you call it.
  • Interesting observation: Over the last decade it seems the edge was moving to the datacenter then the cloud. Now the cloud is moving to the edge. It is doing so by devices like Amazon’s Snowball Edge, which brings the power of EC2 compute to remote locations.
  • Amazon can be rightly credited with kicking off the current wave of business focused cloud computing with Jeff Bezo’s Risky Bet.

Open questions decision-makers should track include:

  • Will the big cloud providers be monopolies?
  • Will the future Internet be “walled gardens?
  • How will nations settle data retention disputes?
  • How do we move compute across tiers?
  • How do we transition from legacy compute to new cloud models?
  • How can we reduce the ability of adversaries to use cloud computing capabilities?

Due Diligence Assessments and Cloud Computing

The trend of Cloud Computing is an increasingly important element of corporate Due Diligence since it is so disruptive business models.

  • On the sell side: Firms should ensure their use of cloud services is done securely and that mitigation strategies are in place for issues. Doing this before sale can make a big difference in how well a firm will be valued.
  • On the buy side: Buyers should pay particular attention to the use of cloud services to ensure a well thought out architecture that mitigates risks. External and independent verification and validation of security policies and practices should include a review of the cloud architecture, as well as the degree that the target is complying with appropriate compliance regimes.

Strategically, the acquisition of technology firms is an art requiring assessment of how unique the capability is and how much in demand it will be in the market. We provide due diligence consulting via our parent company, OODA LLC.

And additional resources:

Cloud Computing Companies in the CTOvision Disruptive Technologies Directory

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There are seven key megatrends driving the future of enterprise IT. You can remember them all with the mnemonic acronym CAMBRIC, which stands for Cloud Computing, Artificial Intelligence, Mobility, Big Data, Robotics, Internet of Things, CyberSecurity.

AWS Snowball Edge And Hyper Converged Infrastructure Will Revolutionize Global Enterprises

The recent announcement by Amazon AWS of a portable Snowball EC2 compute platform represents a significant advance in hybrid cloud/data center computing. When combined with a Hyper Converged Infrastructure  (HCI) super computer and Zero Trust Network, enterprises across a broad range of vertical markets can transform their operational model.1st Generation Hybrid: Two-Stack Architecture

The 1st generation of hybrid cloud/data center was characterized by a two-stack design with legacy apps in the data center and new apps in AWS. Application developers loved the idea of experimenting with AWS Marketplace but the IT department didn’t like the fact that apps could not be ported back into their data center. Additionally the two-stack architecture suffered from disaster recovery and security issues if there was a cloud outage.

VMware noticed the issues IT departments were having with 1st generation hybrid environments and offered vSphere in AWS. VMware’s solution improved load balancing and disaster recovery for legacy applications but it didn’t address the problem of AWS app portability.  Thus many global-scale enterprises waited on the sidelines for something better.

2nd Generation Hybrid Infrastructure: AWS Snowball Edge + HCI Super Computer 

The recent announcement of Snowball Edge by AWS represents a significant advance in hybrid infrastructure. For the first time enterprises can run apps using AWS software logic on a “physical” EC2 instance inside their data center. When combined with a Petaflop-scale Hyper Converged Infrastructure (HCI) super computer enterprises can operate a common application environment for legacy and new AWS apps across the data center and cloud infrastructure.

Looking at the image below we have a high level architecture of a 2nd generation hybrid compute architecture. The Snowball Edge in the data center allows enterprises to run software with embedded AWS logic outside the cloud. To allow enterprises to run legacy as well as compute intensive applications like machine learning there is a high performance Hyper Converged Infrastructure (HCI) super computer paired with the Snowball Edge. In the AWS cloud we have the enterprise’s VPC as well as vSphere environment. Connecting the Data Center and AWS environments we can have any combination of broadband satellite, SDWAN or VXLAN/MLPS.

One of the challenges with such a fluid architecture is routing users to the correct Secure Enclave and blocking self-propagating malware. A SDP-based Zero Trust Network ensures that users are only connected to authorized applications irrespective of where the workload sits.  Unlike standard VPNs, SDP blocks self-propagating malware from moving thru the hybrid compute environment by locking down physical and virtual network interfaces.

Some of the new technical capabilities of a 2nd generation hybrid cloud include:

Workload optimization: While EC2 is great for the majority of workloads sometimes a super computer is better for applications needing millions I/O operations per second. A 2nd generation infrastructure allows hyper-scale computing across super computing and cloud fabric for large data set machine learning or Smart Cities IoT management applications.

Partitioned Compute: The partitioning features of Snowball Edge and a Hyper Converged Infrastructure (HCI) allow for the creation of Secure Enclaves that can only be accessed by authorized users after their compute device has been remotely attested by a Zero Trust Network.  Lateral movement within the hybrid environment is blocked using encrypted APIs.

Disaster Recovery: A pure cloud-centric enterprise is a great idea except if one loses access to the cloud or it’s down. The Snowball-HCI combination allows enterprises to have true active:active redundancy that is synchronized in real time.

Micro Data Center: One interesting aspect of the Snowball-HCI super computer combination is that you can have a two box data center! The small footprint of a Micro Data Center opens the door to edge computing in a broad range of vertical market applications where installing racks of gear is impossible.

Vertical Market Applications

In addition to improving cost structure and functionality for enterprises, 2nd generation hybrid computing holds the promise to revolutionize vertical markets:

Finance & Healthcare: Financial and medical institutions have strict requirements on encryption and access control for regulated data that make it difficult to utilize a public cloud. The 2nd generation hybrid infrastructure provides regulated entities a way to develop business logic in AWS marketplace while processing sensitive data on a Hyper Converged Infrastructure (HCI) at their data center.

Energy & Transportation: Energy and transportation companies build expensive satellite networks to backhaul telemetry to centralized data centers. 2nd generation hybrid compute can reduce the need for expensive satellite communications by processing data in Micro Data Centers. Moreover the integrated security and intelligence of a Micro Data Center edge node allows for load balancing across multiple satellite providers to improve redundancy and cost structure.

Emergency Services: A hurricane, flood or earthquake can easily destroy the communications and compute infrastructure of a whole region. The autonomous operational capabilities of a Micro Data Center combined with 4G coverage and broadband satellite allows emergency personnel to “light up” impacted areas within 48 hours of an event. Moreover the ability to ingest live video feeds from drones and helicopters and fuze them provides on-site personnel improved situational awareness.

Smart Cities: Looking to the near future, the collection and processing of IoT sensor Petabyte-scale data is the single biggest challenge to Smart Cities. The massive data that energy, transportation and environmental sensors generate will overload any compute or network infrastructure. In contrast, 2nd generation architectures provide a high performance distributed compute model where IoT sensor data is first processed at Micro Data Centers and then transferred to centralized management systems. Additionally the Secure Enclave features of 2nd generation  infrastructure can be used to remove personal identifiable information while maintaining relevant data to ensure Smart Cities don’t become a giant surveillance system.

The ability to mix and match applications in a 2nd generation hybrid infrastructure frees enterprises to provision the optimal combination for each project thereby reducing cost and improving agility.  Moreover the ability to operate in a completely disconnected autonomous mode simplifies disaster recovery.

Related topics:

 

Amazon Snowball Edge Even More Functional: Imagine your own cloud in a box that works in the field

Amazon’s Snowball and Snowball Edge have both proven to be very capable in support to industries and government missions (see: Remarkable Engineering and Assessments Confirmed).  Snowball was created to fill a critical gap and still helps organizations move large quantities of data securely to the cloud. Snowball Edge provided more features but also enabled users to conduct some simple pre-processing tasks on their data.

The evolution of these capabilities continues. Amazon has just announced even more functionality for Snowball Edge. Snowball Edge can now run Amazon EC2 instances, and multiple Snowball Edge devices can be connected to form local clusters centrally managed by an AWS console.

Now that Snowball Edge can run full-blown virtual machines it can run enterprise workloads over data in places where that could never be done before. Imagine running workloads you once had to have a cloud or private data center for, but now you can run them in environments where there is limited bandwidth. This can include field locations in support of industries like mining, oil/gas/energy, disaster response and scientific research. It can also include deployment of incredible cloud computing capabilities in support of military missions. The device is lightweight and is now an option for many airborne platforms including military UAVs as well as spacecraft. Shipborne use cases and use cases on submarines are now possible.

This new announcement should get your mind going with potential use cases. Some of the most interesting will include using the device to make smart decisions on what data to keep to move to the cloud and generate alerts and recommendations when certain criteria are met while data is being collected.

For more see: Snowball Edge. And for more on a one of many critical use cases, disaster response, see: Fast, Powerful and Practical: New Technology for Aerial Imagery in Disaster Response

Smart Cities Cybersecurity Challenge

Smart Cities will become a full-scale cyber war battleground unless Congress mandates cybersecurity.

The biggest danger in Smart Cities is the assumption that IoT sensors communicating over a 5G fabric to Machine Learning and Blockchain systems will be safe from cyberattacks. To the contrary Smart Cities suffer from all the cyber vulnerabilities we have today (like phishing password attacks, server exploitation and self-propagating malware (especially ransomware)) plus a new generation of attack vectors due to the hyper-connected state of everything.

State-Sponsored Infiltration: We haven’t even built our first Smart City but we’ve already had our first geo-political incident. DHS recently banned Huawei’s 5G equipment when it was discovered that the Chinese government could remotely listen to any communication in the USA. The loss of domestic American telecom manufacturing makes Smart Cities vulnerable to equipment imported from hostile states. In addition to direct infiltration, the global supply chain provides ample opportunity to modify software and slip in via domestic suppliers.

Personal Targeting: Currently there are no guidelines to limit what IoT sensors can see inside your home or on the street. Self-driving cars see and hear everything while moving (even at high speed). Facial recognition software can track you as well as determine your social connections (people you talk and who they talk to). The vast amount of personal data makes personal targeting a reality. Take for example ransom (not ransomware but real ransom) from being locked in your self-driving car or smart elevator until you make a big crypto-currency payment.

Market Theft: One of the highly promoted aspects of a Smart City is a Blockchain-based market to buy and sell items like energy. While Blockchain provides a tamper proof record of a transaction it doesn’t guarantee the input data is valid. For example, one could trick Smart air conditioners that it’s very hot and have them buy expensive power from a high priced supplier. The ability to hijack a market creates many new opportunities to steal money. Subsequently all the business logic and financial systems in a Blockchain-based market require significant protections against tampering.

The Proposal: Smart City Cybersecurity Framework

To address Smart Cities cyber risks we require a new framework to mitigate state-sponsored infiltration, protect personal privacy and enable an efficient market. However Smart Cities are so complex that the conventional compliance model isn’t going to work.  We need a new approach that defines clear roles and responsibilities for every vendor and service provider.  To start the process, it’s useful to divide a Smart City into the First Mile, Management and Market sections. We can then look at each section to explore their cybersecurity responsibilities.

First Mile: The First Mile is plagued with IoT and 5G vulnerabilities. IoT sensors are extremely vulnerable to tampering leading to DDoS and malware attacks on management systems. Additionally the lack of trusted 5G infrastructure opens the door to foreign surveillance. A solution to both problems is to build an IoT overlay network using a Zero Trust Network (ZTN). ZTN’s validate the identity and software of IoT devices before provisioning connectivity.  Moreover connectivity would not rely on the 5G network for encryption as the ZTN would utilize its own certificates to establish a mutual TLS VPN.

Privacy Gateway: The First Mile is that is where Smart City citizens are the most vulnerable to personal data mining. Subsequently a Privacy Gateway that strips away Personally Identifiable Information (PII) before data is sent to Management systems is critical. A Privacy Gateway is similar to a GDPR database except that is reads the contents of packet streams and removes facial details (from HD cameras) and human speech (from home appliances) in real time.

Management: Given the mission critical nature of guiding vehicles and power generation systems Management systems should run on a Trusted Computing platform. Software processes like machine learning and administrative control should all run in their own Secure Enclave to mitigate self-propagating malware and inside attacks.  Another issue with machine learning systems is their ability to determine data which has been purposely remove. For example traffic systems could easily determine who the owner of a vehicle is and their travel patterns even after the Privacy Gateway removed the driver’s image and license plate from the HD camera feed.  Thus all analytics will need to be stored in a separate Secure Enclave the PII stripped off (again).

Data Validation: To ensure that corrupted data does not makes its way into a Blockchain market a Data Validation Gateway is required. This would be similar to the monitoring system stock markets now use to detect unusual trading activity however their logic would have to be expanded to handle the wide array of products and services in a Smart City exchange. Thus homes with Smart Appliances that like to buy expensive services will need to have their activity monitored by a Data Validation Gateway.

Market: Bitcoin made it’s mark as an anonymous cryptocurrency. Unfortunately anonymous trading is not what we want when it comes to managing energy and transportation trading. Thus secure digital wallets with strong authentication (ideally implemented in a Trusted Computing platform) combined with authorized trading limits will be critical for efficient market operation.

Whether we utilize a framework like the one presented or develop a new one, a comprehensive cybersecurity strategy is critical. Congress must mandate a minimum cybersecurity standards for Smart Cities before large scale deployment happens.

Additional Resources:

What You Need To Know About Bitcoin: Including potential new business models to consider

OODAloop nails it again with reporting on Bitcoin price manipulation

From Crowdsourced Militias to Dread Bitcoin Pirates

Today Every Company Buys Electricity, Tomorrow Every Company Will Buy Ethereum

Smart Cities Cybersecurity Challenge

Blockchain Templates: Amazon Making Technology Mainstream

How Cryptocurrencies will go from The Technologically Savvy, into the Everyday Transactions of Consumers

What Executives Should Know About Ethereum

What Should Executives Know About How Blockchain, Smart Contracts and Cryptocurrencies Are Disrupting Business?

Cryptocurrencies and their promise for enterprise technology professionals

Secure Enclaves: Foundation For The Cloud-Based Enterprise

This is the first in a series of blog posts examining a cloud-based enterprise. In this post we’ll introduce how a Secure Enclave can help enterprises migrate to a cloud-based model.

The two dominant themes in enterprise architecture today is the desire to save money by utilizing cloud services and threat of state-sponsored cyberattacks. The goal of a Secure Enclave is to help enterprises meet both objectives by implementing a trusted access control solution in the cloud.

All IaaS and SaaS providers utilize a shared security model in which they take responsibility for the data inside their boundary but expect the enterprise to be responsible for everything outside their perimeter. For example, enterprises are responsible for all damage due to stolen passwords or unauthorized access to compute instances. Thus the security challenge for cloud-based enterprises to how to enable perimeter security when all they have is the cloud?

A Secure Enclave utilizes a Software Defined Perimeter (SDP) security model to create a protected IaaS instance inside which role-based access control,  trust assessment, certificate management and addressing functions can be deployed. Additionally a Secure Enclave can also protect IaaS and SaaS applications from network-based cyberattacks including self-propagating malware.

Looking at the high level architecture below we see Secure Enclaves supporting trusted access control functions for IaaS and SaaS applications.

Secure Enclave Vidder Junaid Islam

 

The first task of a Secure Enclave is to implement trusted access control to IaaS and SaaS applications. Trusted access control combines role-based access control with device trust assessment. Trust assessment allows enterprises to conduct a remote posture check on user devices before granting access to cloud services. For example, enterprises can verify if a device has updated software and is running endpoint protection. If the device is acceptable then one or more SAML assertions are generated based on the role of the individual.

Secure Enclaves can also be used protect IaaS instances from network-based cyberattacks. Only authorized users and their devices are granted TCP connectivity to IaaS compute instances.  Moreover to block the new generation of self-propagating malware, only application layer connectivity is granted to authorized devices.

One of the unique features of a Secure Enclave is how it protects SaaS applications from stolen passwords. Enterprises can utilize the federation capabilities to SaaS apps to re-direct sign-in requests to their SAML IdP. However only users who have access to the protected IdP can get the SAML assertion. Thus Secure Enclaves can be used to provide transparent multi-factor authentication to SaaS.

In the next post we’ll take a deeper look at the trusted access control functions of the Secure Enclave.

Enterprise Security and Functionality Benefits of the new Software Defined Perimeter (SDP) Approach

The dynamic nature of today’s IT Operations has eroded the network perimeter in ways we have all been watching and even cheering on! This is a new world of mobility, cloud computing and rapid partnering for success.

But the erosion of the network perimeter is making traditional security a roadblock to efficiency. No one wants to allow holes to be poked in the security system but no one wants to shut down connectivity to partners either.

The Software Defined Perimeter uses software techniques to render the internal environment invisible to all outsiders, unless trust is granted. Secure connectivity is provided only to trusted users and devices. The SDP approach was pioneered by proven enterprise IT, cloud computing and security experts working collaboratively together under the Cloud Security Alliance (CSA).

SDP Combines:

  • On-device authentication
  • Identity-based access
  • Dynamically provisioned connectivity

Key benefits of this approach include the following unique security properties:

1) Information Hiding

No DNS information or visible ports of protected application infrastructure. SDP protected assets are considered “dark” as it is impossible to port scan for their presence.

2) Pre-authentication

Device identity (of the requesting host) is verified before connectivity is granted. Device identity is determined via a MFA token that is embedded in the TCP or TLS set up.

3) Pre-authorization

Users are provisioned access only to application servers that are appropriate for their role. The identity system utilizes a SAML assertion to inform the SDP Controller of the hosts’ privileges.

4) Application Layer Access

Users are only granted access at an application layer (not network). Additionally SDP typically whitelists the applications on the user’s device – thus provisioned connections are app-to-app.

5) Extensibility

SDP is built on proven, standards-based components such as mutual TLS, SAML and X.509 Certificates. Standards based technology ensures that SDP can be integrated with other security systems such as data encryption or remote attestation systems.

For more information on this approach contact us

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