- Partitioning strategies for worloads to cloud operations
- Clone strategies for backup, replication, intelligence extensions e.g. RT language translation and multiple process services for multiple parallel temporial services
- Applicance strategies for application extentions via API
- PaaS and IaaS integration e.g. GoogleApps and Force.com integration
- Adoption of mainstream Service Management challenges with Social media systems e.g. the Twitter / Facebook as a "remedy channel" effect
Friday, 29 May 2009
Wednesday, 6 May 2009
Exploiting cloud clone augmentation
The paper explores a research topic of how to deploy workload intensive operations from a Smartphone platform into the cloud and return the results to exploit bursting to augment the mobile services. The project title is CloneCloud.
What is particularly interesting is the way a number of virtualization topics and augmented processes for workloads can be split between the cell phone and the cloud. The key point here is the separation and spread of workloads between different local and virtual platforms such that the computational and storage capabilities are leveraged as "one networked computer" service. Add to this augmented application services not covered in the article and you start to see a number of added value services in a business context. This approach is evident when in a recent analysis I completed of the types of cloud burst services, it is clearly not constrained to excess volume or low volume workload management but also the redirection of specific types of work loads to cloud facilities.
Another very interesting statement in the white paper has been "multiplicity" a feature that has been in the scope of virtualization to optimize workloads but in the case of cloud computing services starts to create a number of very interesting possibilities hitherto considered as capacity resource constrained.
To quote the article:
–Use multiple copies of the system image executed in different ways. This can help run data parallel applications. E.g. indexing for disjoint sets of images. This can also help the application “see the future”, by exhaustively exploring all possible next steps within some small horizon. To enable for scenario model checking such as in monte carlo simulation.
This is a different way of of not only considering the virtualized device cloned into the cloud but in replicating the machine image it is possible to create multiple parallel tasks and from there a range of new service augmentation possibility not envisioned by the initial invocation. As previously suggested, if you add augmented application services into this you start to see a wider set of added value services.
What this says to me is that the on premise and off premise geographical distinction is wrong in the sense it is the device and the machine specific locations that are the real on and off premise locations. It also supports the view that temporal transformation as seen in batch to near real time processing in traditional timeframes may now evolve into new temporal transgformations that operate beyond immediate time and create multiple versions of "parallel time services". In a sense there are multiple arrows of time.What it does also suggest is that the concept of a cloud switch may involve a number of second level and higher tiers of event interaction and types of VM patterns than just the Hypervisor workload management.
A summary of the cloud workload distribution patterns described in the article are: