Tag Archives: patents

Seven Cloud Success Criteria to consider before you pick a platform

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From my desk at Dell, I have a unique perspective.   In addition to a constant stream of deep customer interactions about our many cloud solutions (even going back pre-OpenStack to Joyent & Eucalyptus), I have been an active advocate for OpenStack, involved in many discussions with and about CloudStack and regularly talk shop with Dell’s VIS Creator (our enterprise focused virtualization products) teams.  And, if you go back ten years to 2002, patented the concept of hybrid clouds with Dave McCrory.

Rather than offering opinions in the Cloud v. Cloud fray, I’m suggesting that cloud success means taking a system view.

Platform choice is only part of the decision: operational readiness, application types and organization culture are critical foundations before platform.

Over the last two years at Dell, I found seven points outweigh customers’ choice of platform.

  1. Running clouds requires building operational expertise both at the application and infrastructure layers.  CloudOps is real.
  2. Application architectures matter for cloud deployment because they can redefine the SLA requirements and API expectations
  3. Development community and collaboration is a significant value because sharing around open operations offers significant returns.
  4. We need to build an accelerating pace of innovation into our core operating principles
  5. There are still significant technology gaps to fill (networking & storage) and we will discover new gaps as we go
  6. We can no longer discuss public and private clouds as distinct concepts.   True hybrid clouds are not here yet, but everyone can already see their massive shadow.
  7. There is always more than one right technological answer.  Avoid analysis paralysis by making incrementally correct decisions (committing, moving forward, learning and then re-evaluating).

Are Clouds using Dark Cycles?

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Or “Darth Vader vs Godzilla”

Way way back in January, I’d heard loud and clear that companies where not expecting to mix cloud computing loads.  I was treated like a three-eyed Japanese tree slug for suggesting that we could mixing HPC and Analytics loads with business applications in the same clouds.  The consensus was that companies would stand up independent clouds for each workload.  The analysis work was too important to interrupt and the business applications too critical to risk.

It has always rankled me that all those unused compute cycles (“the dark cycles”) could be put to good use.  It’s appeals to my eco-geek side to make best possible use of all those idle servers.   Dave McCrory and I even wrote some cloud patents around this.

However, I succumbed to the scorn and accepted the separation.

Now all of a sudden, this idea seems to be playing Godzilla to a Tokyo shaped cloud data center.  I see several forces merging together to resurrect mixing workloads.

  1. Hadoop (and other map-reduce Analytics) are becoming required business tools
  2. Public clouds are making it possible to quickly (if not cheaply) setup analytic clouds
  3. Governance of virtualization is getting better
  4. Companies want to save some $$$

This trend will only continue as Moore’s Law improves the compute density for hardware.  Since our designs are leading towards scale out designs that distribute applications over multiple nodes; it is not practical to expect an application to consume all the power of a single computer.

That leaves a lot of lonely dark cycles looking for work.

Now all of a sudden, this idea seems to be playing Godzilla to a Tokyo shaped cloud data center.  I see several forces merging together to resurrect mixing workloads.

  1. Hadoop (and other map-reduce Analytics) are becoming required business tools
  2. Public clouds are making it possible to quickly (if not cheaply) setup analytic clouds
  3. Governance of virtualization is getting better
  4. Companies want to save some $$$

This trend will only continue as Moore’s Law improves the compute density for hardware.  Since our designs are leading towards scale out designs that distribute applications over multiple nodes; it is not practical to expect an application to consume all the power of a single computer.

That leaves a lot of lonely dark cycles looking for work.