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Accelerating the Next 10,000 Clouds
The document discusses the evolution and growth of cloud computing, particularly focusing on OpenStack's development from its inception in 2009 to its current status in 2015. It highlights the shift from traditional deployment methods to self-service configurations and increased enterprise adoption, along with the need for scalable and efficient cloud solutions. Additionally, it emphasizes the importance of collaboration and innovation in enhancing cloud technologies for widespread use.
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Accelerating the Next 10,000 Clouds
- 1. OpenStack Silicon Valley| 2015 Accelerating the Next 10,000 Clouds Diane Bryant Senior Vice President & General Manager Data Center Group Intel
- 2. OpenStack Silicon Valley| 2015 Cloud Hype Cycle TECHNOLOGY TRIGGER PEAK OF INFLATED EXPECTATIONS TROUGH OF DISILLUSIONMENT SLOPE OF ENLIGHTENMENT PLATEAU OF PRODUCTIVITY VISIBILITY MATURITY “The cloud is for everyone. The cloud is a democracy.” Marc Benioff (2010) CEO, Salesforce.com “Cloud computing: how computing services will be delivered in the future.” Tim O’Reilly (2009) CEO, O’Reilly Media “The interesting thing is that we’ve redefined cloud computing to include everything that we already do.” Larry Ellison (2008) CEO, Oracle "It's stupidity. It's worse than stupidity: it's a marketing hype campaign.” Richard Stallman (2008) Creator,GNU “Cloud computing's primary innovation is its name..” Glen Morris (2009) Technology Editor “...utilities give us access to clean water... cloud computing works in a similar fashion.” Vivek Kundra (2010) Former federalCIO of the United States YOU ARE HERE 2009
- 3. OpenStack Silicon Valley| 2015 HPC for Design Engineering SELF SERVE CONFIGURATIO N80% UTILIZATION INSTANT DEPLOYMENT
- 4. OpenStack Silicon Valley| 2015 Bringing Cloud to the Enterprise MANUAL <10% UTILIZATION 90 DAYS Traditional Pre-2009
- 5. OpenStack Silicon Valley| 2015 Bringing Cloud to the Enterprise MANUAL 20% UTILIZATION 14 DAYS Virtualized MANUAL <10% UTILIZATION 90 DAYS Traditional 2009Pre-2009
- 6. OpenStack Silicon Valley| 2015 Bringing Cloud to the Enterprise SELF-SERVE 40% UTILIZATION <3 HOURS Cloud MANUAL 20% UTILIZATION 14 DAYS Virtualized MANUAL <10% UTILIZATION 90 DAYS Traditional 20112009Pre-2009
- 7. OpenStack Silicon Valley| 2015 Built on Open Source 2011 124K lines of code 3 projects <100 contributors TODAY 2.65M lines of code 41 projects 4,000 contributors OpenStack
- 8. OpenStack Silicon Valley| 2015 OpenStack Today 2009 2010 2011 2012 2013 2014 <10% of enterprises have deployed cloud Cloud Market Growth IntelCPUSales Private Cloud 8% Public Cloud 92%
- 9. OpenStack Silicon Valley| 2015 OpenStack Today 2009 2010 2011 2012 2013 2014 <10% of enterprises have deployed cloud Cloud Market Growth IntelCPUSales Private Cloud 8% Public Cloud 92% FRAGMENTED solution stacks COMPLEXITY in deploying solutions LACK of key features Gaps Remain
- 10. OpenStack Silicon Valley| 2015 Jevons Paradox Leads to NEW USAGES Increase in TECHNOLOGY EFFICIENCY Increases rate of CONSUMPTION
- 11. OpenStack Silicon Valley| 2015 Intel® Cloud For All Unleash Tens of Thousands of New Clouds in creating enterprise ready, easy to deploy cloud solutions for high efficiency clouds across workloads the industry to accelerate cloud deployments Invest Optimize Align
- 12. OpenStack Silicon Valley| 2015 Deliver enterprise ready OpenStack to scale to 1000’s of nodes Build largest joint developer team to accelerate upstream contributions Create largest developer cloud to build and validate solutions at scale Other names and brands may be claimed as the property of others.
- 13. OpenStack Silicon Valley| 2015 Enhance enterprise readiness to ease adoption and operations Deliver performance at scale to ensure efficient and effective OpenStack deployments Implement network & storage stack improvements to enable scalable & resilient solutions Other names and brands may be claimed as the property of others.
- 14. OpenStack Silicon Valley| 2015 Boris Renski Co-Founder & Chief Marketing Officer Paul Voccio Vice President Software Development Other names and brands may be claimed as the property of others.
- 15. OpenStack Silicon Valley| 2015 Boris Renski Co-Founder & Chief Marketing Officer Paul Voccio Vice President Software Development Other names and brands may be claimed as the property of others.
- 16. OpenStack Silicon Valley| 2015 Building upon existing collaborations Rackscale Architecture Open Container Initiative Clear Linux Project Cloud Native Computing Foundation Standards & Initiatives Recent Collaboration Announcements Other names and brands may be claimed as the property of others.
- 17. OpenStack Silicon Valley| 2015 Future Clouds Traditional System 1 App System 2 App Virtualized App Virtualization System 1 System 2 Virtualization App App App Cloud Orchestration System 1 System N Virtualization Virtualization App App App App App App Hyperscale Cloud Orchestration App App App App App App Containers / Processes Containers / Processes Resource Pool Resource Pool = Resource Utilization Bringing hyperscale to the masses
- 18. OpenStack Silicon Valley| 2015 Future Clouds Bringing hyperscale to the masses EFFICIENT application development EFFICIENT hardware EFFICIENT schedulers: bare metal to VM to containers EFFICIENT execution across all clouds Hyperscale Cloud Orchestration App App App App App App Containers / Processes Containers / Processes Resource Pool Resource Pool
- 19. OpenStack Silicon Valley| 2015 Summary Enable the INNOVATION cycle Deliver greater EFFICIENCY through cloud computing
- 20. OpenStack Silicon Valley| 2015 Thank You
Editor's Notes
- #3 http://www.forbes.com/sites/joemckendrick/2013/03/24/10-quotes-on-cloud-computing-that-really-say-it-all/ “The interesting thing about cloud computing is that we’ve redefined cloud computing to include everything that we already do. I can’t think of anything that isn’t cloud computing with all of these announcements. The computer industry is the only industry that is more fashion-driven than women’s fashion. Maybe I’m an idiot, but I have no idea what anyone is talking about. What is it? It’s complete gibberish. It’s insane. When is this idiocy going to stop?” – Larry Ellison, chairman, Oracle, referring to the term "cloud computing" in his Oracle OpenWorld 2008 speech “I don’t need a hard disk in my computer if I can get to the server faster… carrying around these non-connected computers is byzantine by comparison.” – Steve Jobs, late chairman of Apple (1997) “If you think you’ve seen this movie before, you are right. Cloud computing is based on the time-sharing model we leveraged years ago before we could afford our own computers. The idea is to share computing power among many companies and people, thereby reducing the cost of that computing power to those who leverage it. The value of time share and the core value of cloud computing are pretty much the same, only the resources these days are much better and more cost effective.” – David Linthicum, author, Cloud Computing and SOA Convergence in Your Enterprise: A Step-by-Step Guide “Ultimately, the cloud is the latest example of Schumpeterian creative destruction: creating wealth for those who exploit it; and leading to the demise of those that don’t.” - Joe Weinman, Senior VP at Telx and author of Cloudonomics: The Business Value of Cloud Computing it’s worth keeping in mind that in the cloud we’re all guinea pigs, and that means we’re all dispensable. Caveat cloudster.” – Nick Carr, author of Does IT Matter?, The Big Switch and The Shallows “Cloud computing is often far more secure than traditional computing, because companies like Google and Amazon can attract and retain cyber-security personnel of a higher quality than many governmental agencies.” - Vivek Kundra, former federal CIO of the United States
- #4 She asked the team to start in 2009, but I think it might be useful to know that we had a running Grid in 1997, and we had it globally connected around 2005. Resource pools (ways to make pools larger & larger -> easier to share when the lake is larger) The better we got at sharing capacity, the better we were at driving up capacity Small team that had to scale quickly, so HAD to automate everything Enterprise had just a couple pools
- #5 Lets move Automation after Virtualization… for IT Virtualization put 14 days for Time to Deploy, with Automation drop it to 5 days (and the key here is that the automation was actually pretty quick, the issue was the time waiting in the ticket queue for IT)… Then Gen 1 IT Private Cloud is <3hrs, Gen 2 which you can’t fit is basically instantaneous. Utilization first went up from <10% to 20% when we virtualized... Then up to 40% when we made it a private cloud.
- #6 Lets move Automation after Virtualization… for IT Virtualization put 14 days for Time to Deploy, with Automation drop it to 5 days (and the key here is that the automation was actually pretty quick, the issue was the time waiting in the ticket queue for IT)… Then Gen 1 IT Private Cloud is <3hrs, Gen 2 which you can’t fit is basically instantaneous. Utilization first went up from <10% to 20% when we virtualized... Then up to 40% when we made it a private cloud.
- #7 Do you know what the $$ value of private cloud deployment has been for Intel? I am pretty sure it is $25M NPV, I will close on the validity on Monday.
- #8 7
- #9 Fragmentation of solution stacks: End user required to navigate too many and complex API; Limited standard (open) interfaces between legacy/traditional & software defined infrastructure Complexity of deploying solutions: Requires too high a technical acumen to design & implement (Network overlays, authorization & authentication); Integration of legacy/traditional infrastructure & applications with next generation infrastructure into brownfield datacenters; Existing enterprise infrastructure & applications and operations is not well documented Lack of mature enterprise features: Rolling upgrades (version upgrades without downtime); Metric driven resource elasticity (auto scaling up and down); High availability of tenants & services (hardware or service failures trigger automatic failover); Overarching management tool for compute, storage, network & services (Ecosystem maturity like VMware and AWS) High efficiency and scale difficult to achieve: The complexity of manually “bin packing” to achieve optimal efficiency requires the characterization off every workload factored with the memory, CPU and cache capacity size of a heterogeneous set of server; Operational productivity is hampered by the lack of the necessary telemetry data and automated management; Today’s scale in measured thousands of physical hosts (Everything has maximum limits memory, storage, vCPUs, network connections) where cloud native applications require scale to 10s of thousands of hosts in multiple data centers. http://www.vmware.com/pdf/vsphere6/r60/vsphere-60-configuration-maximums.pdf
- #10 Fragmentation of solution stacks: End user required to navigate too many and complex API; Limited standard (open) interfaces between legacy/traditional & software defined infrastructure Complexity of deploying solutions: Requires too high a technical acumen to design & implement (Network overlays, authorization & authentication); Integration of legacy/traditional infrastructure & applications with next generation infrastructure into brownfield datacenters; Existing enterprise infrastructure & applications and operations is not well documented Lack of mature enterprise features: Rolling upgrades (version upgrades without downtime); Metric driven resource elasticity (auto scaling up and down); High availability of tenants & services (hardware or service failures trigger automatic failover); Overarching management tool for compute, storage, network & services (Ecosystem maturity like VMware and AWS) High efficiency and scale difficult to achieve: The complexity of manually “bin packing” to achieve optimal efficiency requires the characterization off every workload factored with the memory, CPU and cache capacity size of a heterogeneous set of server; Operational productivity is hampered by the lack of the necessary telemetry data and automated management; Today’s scale in measured thousands of physical hosts (Everything has maximum limits memory, storage, vCPUs, network connections) where cloud native applications require scale to 10s of thousands of hosts in multiple data centers. http://www.vmware.com/pdf/vsphere6/r60/vsphere-60-configuration-maximums.pdf
- #14 Put context to the Mirantis deal as it pertains to Rackspace (Rackspace focuses on upstream maturity and scale, Mirantis focuses on specific areas of need for enterprise adoption) Talk about the opportunities for enhancing enterprise readiness to ease adoption and operations As part of the Intel Cloud for All announcement on July 24, Intel is increasing our investment in Mirantis via a Series B infusion. The total round was ~100M and included investors such as Goldman Sachs, August Capital, Insight Venture Partners, Ericsson, Sapphire Ventures (formerly SAP Ventures) and WestSummit Capital. This investment was based on the intent to mature downstream distributions of OpenStack, focusing on the following technical aspects: o Performance at scale o Bare metal provisioning o Ceph storage improvements o Enterprise readiness acceleration o Network stack improvements o Big data optimized OpenStack solution delivery
- #18 Cloud Integrity Technology – TXT Bringing hyperscale technologies to mainstream environments (concepts born on hyperscale) Cloud Native Computing Foundation – enabling software developers to easily deploy containers give me a server {VM, OS, etc} give me a container Why would an app developer want to use a container?? – AR: Das to highlight pros/cons
- #19 Cloud Integrity Technology – TXT Bringing hyperscale technologies to mainstream environments (concepts born on hyperscale) Cloud Native Computing Foundation – enabling software developers to easily deploy containers give me a server {VM, OS, etc} give me a container Why would an app developer want to use a container?? – AR: Das to highlight pros/cons
- #20 Build hyperscale efficiency to the masses – the ability to rapidly deploy apps at scale, enable more apps to be containerized, address network and storage limitations, etc. Enable schedulers that support from bare metal to VM to container - rather than independent fiefdoms, allow all apps and resources to be scheduled with common view Drive cloud efficiency via rapid hardware innovation – clouds that can support heterogenous computing across microservers to Xeon phi, that can support FPGAs, Next generation memory technology and manage the hardware innovation seamlessly Integrate cross- cloud – deploy on prem / in cloud / different service providers with a common view based on where it makes the most sense to deploy