Assuming all key availability and performance metrics need to be collected and processed regularly to keep the cloud infrastructure running within the agreed performance service levels and to identify the trends of demand for the cloud services there is an absolute need for the predictive analytics on the collected metrics data.
As the data centers gradually turn into private clouds with a lot of virtualization, it becomes increasingly important to manage the underlying grid of resources efficiently by allocating the best possible resources to the high priority jobs. The integrated infrastructure monitoring and analytics framework running on the grid itself can optimize the resource allocation dynamically to fit the workload characteristics could make the data center more efficient and green.
Taking the same approach to the business services across the organizational boundaries, there could be an automated market place where the available computing resources could be traded by the public cloud providers and the consumers can “buy” needed computing resources in the market and get their processing executed by probably combining multiple providers’ resources on an extended hybrid cloud in a highly dynamic configuration.
The data and processing have to be encapsulated at a micro or nano scale objects, taking the computing out of current storage – processor architecture into a more connected neuron like architecture with billions of nodes connected in a really BIG bigdata.
OR
If all the computing needed on this tiny globe can be unified into a single harmonic process, the amount of data that needs moving comes to a minimum and a “single cloud” serves the purpose.
Conclusion: Cloud management using bigdata, and big data running on cloud infrastructure complement each other to improve the future of computing!
Question: If I have a $1 today, where should I invest for better future? In big data? Or in Cloud startup??
Have a fabulous Friday!
As the data centers gradually turn into private clouds with a lot of virtualization, it becomes increasingly important to manage the underlying grid of resources efficiently by allocating the best possible resources to the high priority jobs. The integrated infrastructure monitoring and analytics framework running on the grid itself can optimize the resource allocation dynamically to fit the workload characteristics could make the data center more efficient and green.
Taking the same approach to the business services across the organizational boundaries, there could be an automated market place where the available computing resources could be traded by the public cloud providers and the consumers can “buy” needed computing resources in the market and get their processing executed by probably combining multiple providers’ resources on an extended hybrid cloud in a highly dynamic configuration.
The data and processing have to be encapsulated at a micro or nano scale objects, taking the computing out of current storage – processor architecture into a more connected neuron like architecture with billions of nodes connected in a really BIG bigdata.
OR
If all the computing needed on this tiny globe can be unified into a single harmonic process, the amount of data that needs moving comes to a minimum and a “single cloud” serves the purpose.
Conclusion: Cloud management using bigdata, and big data running on cloud infrastructure complement each other to improve the future of computing!
Question: If I have a $1 today, where should I invest for better future? In big data? Or in Cloud startup??
Have a fabulous Friday!
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