Evolving Clouds in the Enterprise Space

"When we feel stuck, we look at the sky. The clouds remind us that everything changes." But we have no control over the cloud evolution and we pay serious attention only after it gets darker and thicker. We show either interest or concern depending on how it affects us. Gentle drizzles or Torrential rains.

Now let's imagine we drive these cloud changes, we anticipate the evolution and be prepared to receive the outcomes for our benefits. Yes, I am talking about Public Clouds like AWS (Amazon Web Services), MS Azure, etc in IT space (Information Technology).

These public clouds are literally in our control with several data centers in different geographical regions to deliver what, when and how much we need. They are quickly evolving too. To be precise there are 66 availability zones in 21 geographical regions for AWS whereas MS Azure has 46 regions.

While we have to go up in the sky to reach real clouds, we need internet access to reach the public cloud. Without internet access, it cannot be called a public cloud by definition. With 5G speeds it can inundate us with a host of technical possibilities like real-time cloud computing, decision science, etc.

So the intention of this article is to explore the public cloud evolution and what it means to enterprises and users at large. 

What is IT Public Cloud?

Let's revisit a few cloud definitions or acronyms (mainly of AWS) to describe them and you may refer to internet sources for further information as it is difficult to cover all of them comprehensively here.

The premise for public cloud relevance is the “Pay as you go” model for data storage, computation and other services available in the cloud data centers. “

So enterprises can do away with upfront capital expenditure for IT infrastructure that includes savings in servers, power, networking, and space.

In AWS the storage is managed through an API (application programming interface) known as S3 (Simple Storage Service) which is object storage and which is accessed through HTTP requests with high reliability, scalability and redundancy protection. 

For the data computation, AWS has EC2 (Elastic Compute Cloud) API for servers instantiation that is scalable with processing demand but also for attached EBS (Elastic Block Storage) API that is Block level storage with SAN (Storage Area Network) using RAID ( Redundant Array of Independent Disks) configuration.

Beyond storage and computing, there are a host of other microservices and technology modules provided by public cloud vendors that include features like AI/ML, IoT, Blockchain, satellite data reception services, etc.

While we discuss public cloud here there are other variations such as Hybrid Cloud, Community Cloud, and Multi-Cloud. 

The Hybrid model is Private (on /off-premise) + Public cloud hosting by retaining some data and applications at their local data centers. Some enterprises follow this model for some concerns which may include three key points.

1.   Impact on organization due to all in one go movement to public cloud possibly disrupting customer service.

2.   Not well trained to leverage strong cloud security practices, to retain some critical applications at local servers.

3.   Real-time performance needs of some applications that could be compromised due to bad network access.

The multi-cloud model represents the use of 2 or more public cloud vendors and another lesser-known model is Community Cloud that is dedicated to a specific community of enterprises. These are not discussed here.

Cloud influence on Enterprises

I see 3 phases for the Enterprise solutions vis a vis leveraging clouds that influence rapid commercialization as well as commoditization, that it appears to be an elliptical cycle than circular. These 3 phases are,

(1) Creative Phase,

(2) Sustaining Phase and

(3) Disruption Phase

The creative phase is when work moves to public cloud space so that organization innovation efforts are optimized.

The sustaining phase is when some of those ideas can be materialized and also at a large scale to sustain the enterprise RoI (Return on Investment).

The disruption phase is when significant price erosion takes place for the products/services due to intense competition and the technology to be considered commoditized.

We also discuss the stages within these three phases in detail.

The diagram shows the cyclical enterprise solutions and the stages that get influenced by cloud-based solutions.

Let's see each of these stages;

Exploration stage:

Exploration has an equation. Exploration Initiative = Benefits of exploring – Cost of Misadventure. A probable positive metric will prompt exploration, otherwise not. While migrating to the cloud for the first time is an exploration in itself, the proof of concepts with cloud possibilities is the real integral step. In AWS or MS Azure, they have templates for TCO (Total Cost of Ownership).

Metaphorically speaking some of us does get jitters when our flight gets turbulence entering into think clouds. So it's fair to have apprehensions before public cloud migration activity is undertaken as well. A methodical approach always helps to take into account organization capabilities and business strategy. One part of this outcome is a cloud strategy to clarify the “As Is” state to “To Be” state for the Enterprise.

This may include some basic elements to start like

-> Which applications, database to be migrated as “Re Host” or “Refactor or “Re platform” or “Retain in local server” or “Remove” or “Repurchase”,

-> To be delivered as SaaS, PaaS or IaaS,

-> Hosting model to be Hybrid or Full Cloud or Multi-cloud etc.

Adaptation stage:

This stage depends on the cloud strategy to re-architect and leverage cloud-native capabilities and micro-services.

Here the business strategy is revisited to take advantage of the newfound cloud capabilities.

AWS Services like Autoscaling, Lambda, Cloud trail, Cloud framework, etc can influence computing instances that are aligned to peak business periods, market expansion with cloud edge services to remotest clients, database changes like from my SQL to Amazon Aurora Or serverless computing for short, simple, periodic needs.

Depending on the delivery strategy, code build, integration, validation, security partitions, etc could change. SaaS and PaaS influence the scope partitioning.

SaaS (Software as a Service) based solutions are primarily B2C markets with client-server architecture and desktop/Mobile web app projects, while PaaS (Platform as a Service) has more appeal to B2B solution and also for embedded platforms for customization.

Below is the Statista Reference on SaaS and PaaS market cap forecast till 2020 which is ~ $150 billion for SaaS and ~ $60 billion for PaaS.

-      IDG sample survey indicates that 80% of enterprises are exposed to the public cloud.

-      A study from Forbes indicates the SaaS+PaaS market to reach $200 billion by 2020.

Innovation stage:

Here the enterprises are well adapted to cloud and try to pivot to new opportunities that stem from the cloud space which is a conduit for technological advances.

1.   Gartner predicts that by 2022, 40% of new application projects will have artificial intelligence components, 70% of enterprises will deal with immersive technologies and 25% of enterprises deploy immersive technologies

2.   Adroid Market Corporation research predicts that by 2025 Cloud Computing Market will grow to hit $696.25 billion

Looking at (1) And (2) it is clear that cloud-based innovation is going to be a significant component of the $696 billion market capitalization from the current $200 billion market cap.

So the anticipation of the next new is key. For example, Cloud-based Gig economy, IoT healthcare, Advanced AI/ML, Social sector Blockchain, Data Science Decisions, Space research, Commercial drones, are few to mention. 

Commercialization stage:

It takes about 100 research ideas to generate about 10 development projects of which two will usually make it through to commercialization and only one will actually make money when launched – Research Gate in early 2000

 Let us revisit the standard technology adoption cycle as shown in the diagram below which traverses from

Innovators -> Early Adopters -> Early majority -> Late majority -> Laggards

This standard convention has a problem. The curve is getting more and more acute with lead time from early adopters to the late majority that is shrinking. With the window of opportunity to gain market share is short, the way the projects are executed needs to be redefined to avoid commercial failures.

How does public cloud help this commercialization riddle? By Integrating Project realities to Cloud realities? yes.

I would like to mention a few issues here for cloud advantages for a higher probability of commercial success.

1.   Initiate concurrent projects with resource constraints stretched to the limit with priority assertion reviewed from time to time. It is best done with cloud capabilities leveraged

a.Choose low-cost options from the cloud with no upfront capital expenditure

b.Align enterprise project commerce to cloud “pay as you go” model

c.Use serverless computation from the cloud for repeated builds

2.   Anticipate partner ecosystem through the cloud to bring early integration activities. It avoids commercial failure due to the late discovery of bottlenecks for supporting subsystems, components, supply chain networks, etc.

3.   Reach a larger worldwide customer base quickly. AWS has a Market Place portal to discover new customers, streamlined deliveries, simplified billing, and payments, etc supported by Marketing Analytics Dashboard.

4.   Leverage device farms in the cloud to ensure no critical testing is left out prior to rolling out to the market. Otherwise, roll out starts and ends at the stage of early adapters.

5.   Last but not least, there shall be somebody in charge of the commercialization project. Not having somebody to address this multi-disciplinary and collaborative activity is a recipe for failure in all its probability.

 Commoditization stage:

This phase starts with the onset of commoditization of products/services. Price erosion occurs due to intense competition. Market consolidation happens to sustain volumes and survive for a given competitive price. Alternative value-added solutions are sought after at this stage. Cutting costs or differentiation does not benefit but only extends the eventual extinction.

This stage ends with products/services having outlived their life and the solutions are either repackaged or bundled or cannibalized by new products/services

Anticipating and working on the next new, such as Cloud-based Gig economy, IoT healthcare, Advanced AI/ML, Social sector Blockchain, Decision Data Science, Space research, Geo tagged drones, etc could start the next cycle.

Conclusion:

• Public cloud is here to stay, growing year on year at a double-digit rate and becoming a conduit for technology convergence. Enterprises have little choice but to evolve in the cloud space
• The enterprise product/service cycle is more of an elliptical shape than a circular one due to shrinking commercialization windows and rapid disruptions. So align commercialization projects accordingly to maximize revenue in a short market window by leveraging cloud capabilities.
• Enterprises that leverage cloud technologies, anticipate the next new and run concurrent R&D projects at the innovation stage to increase their chances of being relevant in the market and to be the only one and not among many.