The Changing & Evolving Cycles Of Cloud & Internet Of Things
Headquartered in Washington, Compute Next is a Cloud Marketplace Platform offering an array of cloud services that enable businesses to internally control,manage,and orchestrate cloud service procurement and delivery in a cost-effective way.
Cloud Brokerage Marketplaces will play a fundamental role from the Internet to Cloud to IoT to Machine Learning. After years of evolving from the hype cycle, Cloud has evolved as the mainstream business model and adoption is seen across the industry spectrum. It has disintermediated the entire IT industry and is in the adoption cycle. Whether it is for consumer and/or Enterprise usage, Cloud is seen as a cost-effective model of procuring and using IT services.
Cloud has also blurred the lines between consumer & enterprise adoption, payment & subscription models, enhanced roles for IT resellers & distributors, differentiated roles for System Integrators. This has been brought by new creative business models, price transparency, automation and real-time deployment/provisioning and has created disruption and waves on where exactly the technology meets the transactional value, who takes the margins and where the value really is in the whole cycle.
Automation and real-time access to the IT resources have either streamlined or eliminated few of the IT processes. We have a different view today at price vs value,long term contracts, support and managed services model. As in most industries where automation sets in, marketplaces became mainstream. Today,a Brokerage Marketplace can bring together Independent Software Vendors (ISVs), Enterprises, Resellers, System Integrators and Managed Service Provider in a single ecosystem. We can bundle, manage life-cycles and support an entire suite of services.
We can create the workflow and extract business value between the disparate set of solutions in a single marketplace. We can orchestrate workloads between two different ISVs(from two different vendors). We can monitor and manage the workload from a single dashboard. We can also make changes to the workload while components are still live. Most importantly, we can make choices based on price discrimination all in a single framework.
How that disintermediation led to the growth of Internet-of-Things?
We can all feel the tremendous potential and value of IoT in our daily lives. It ranges from managing the temperature in our homes to checking for faulty devices in the manufacturing assembly lines. It’s now in the hype cycle, marking its presence in Machine Learning and Artificial Intelligence. The concept of sensors (industrial or otherwise) is not a new or a novel idea. The problem was practicality if they can work? Can cars actually talk to each other? Can a refrigerator automate temperature based on the items in it and can a faulty device in an assembly line be pulled out without stopping the manufacturing process?
We will first need a seamless data stream of course, whether it's in-house or the internet. We need models in which the devices are authenticating and sending crucial data. We need a platform for the authentication, storing of data, and then working with other sensors and applications to make sure that the decision-making process is aligned. This platform will be a blend of Cloud Brokerage and other IoT components which also sets the stage for machine learning. There will be a real-time decision-making process that will enable the optimization of the environment whether it be home or a manufacturing unit. Once machine learning sets in place, we have a decision-making process that kicks in. Now two cars can interact and evaluate if there is going to be a collision or if a self-driving car can park on its own.
There must be a model to bring these pieces together in a single framework, so they can seamlessly communicate. From Cloud to IoT to Machine Learning to AI, the platform must then also make this into a provisional,trackable and manageable model. I believe this is where Brokerage and Marketplace platforms play a bigger role, eventually leading to the ease of usage and monetization of the platform.
Cloud Brokerage Marketplaces will play a fundamental role from the Internet to Cloud to IoT to Machine Learning. After years of evolving from the hype cycle, Cloud has evolved as the mainstream business model and adoption is seen across the industry spectrum. It has disintermediated the entire IT industry and is in the adoption cycle. Whether it is for consumer and/or Enterprise usage, Cloud is seen as a cost-effective model of procuring and using IT services.
Cloud has also blurred the lines between consumer & enterprise adoption, payment & subscription models, enhanced roles for IT resellers & distributors, differentiated roles for System Integrators. This has been brought by new creative business models, price transparency, automation and real-time deployment/provisioning and has created disruption and waves on where exactly the technology meets the transactional value, who takes the margins and where the value really is in the whole cycle.
Automation and real-time access to the IT resources have either streamlined or eliminated few of the IT processes. We have a different view today at price vs value,long term contracts, support and managed services model. As in most industries where automation sets in, marketplaces became mainstream. Today,a Brokerage Marketplace can bring together Independent Software Vendors (ISVs), Enterprises, Resellers, System Integrators and Managed Service Provider in a single ecosystem. We can bundle, manage life-cycles and support an entire suite of services.
We can create the workflow and extract business value between the disparate set of solutions in a single marketplace. We can orchestrate workloads between two different ISVs(from two different vendors). We can monitor and manage the workload from a single dashboard. We can also make changes to the workload while components are still live. Most importantly, we can make choices based on price discrimination all in a single framework.
How that disintermediation led to the growth of Internet-of-Things?
We can all feel the tremendous potential and value of IoT in our daily lives. It ranges from managing the temperature in our homes to checking for faulty devices in the manufacturing assembly lines. It’s now in the hype cycle, marking its presence in Machine Learning and Artificial Intelligence. The concept of sensors (industrial or otherwise) is not a new or a novel idea. The problem was practicality if they can work? Can cars actually talk to each other? Can a refrigerator automate temperature based on the items in it and can a faulty device in an assembly line be pulled out without stopping the manufacturing process?
We will first need a seamless data stream of course, whether it's in-house or the internet. We need models in which the devices are authenticating and sending crucial data. We need a platform for the authentication, storing of data, and then working with other sensors and applications to make sure that the decision-making process is aligned. This platform will be a blend of Cloud Brokerage and other IoT components which also sets the stage for machine learning. There will be a real-time decision-making process that will enable the optimization of the environment whether it be home or a manufacturing unit. Once machine learning sets in place, we have a decision-making process that kicks in. Now two cars can interact and evaluate if there is going to be a collision or if a self-driving car can park on its own.
There must be a model to bring these pieces together in a single framework, so they can seamlessly communicate. From Cloud to IoT to Machine Learning to AI, the platform must then also make this into a provisional,trackable and manageable model. I believe this is where Brokerage and Marketplace platforms play a bigger role, eventually leading to the ease of usage and monetization of the platform.
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