elemental cloud computing
intentional cloud watching - by brenda michelson
Once again, the day opens with short keynotes.
Starting us off is James Staten of Forrester. James gives us two words to think about in respect to cloudonomics: Down & Off. When the application (resource) isn’t in use, you can turn it off. When you turn it off, you aren’t paying.
James says to write applications in more >>
Session Abstract: In many ways, Big Data is what clouds were made for. Computing problems that are beyond the grasp of a single computer—no matter how huge—are easy for elastic platforms to handle. In this session, big data processing pioneer Colin Clark will discuss how to discover hidden signals and new knowledge within in huge streams of realtime data, applying event processing design patterns to events in real time.
Speaker – Colin Clark, CTO, Cloud Event Processing
Colin opens talking about high velocity, big data. more >>
Speaker – Jinesh Varia, Technology Evangelist, Amazon Web Services
Jinesh is doing a nice job describing the evolution of a fictional (dating) website that is live only 3 hours a week. In telling the story, he is walking through the site’s evolution, the developer’s knowledge of patterns (really good design practices) and the related AWS cloud offerings (patterns of use).
Pattern #1: Design for failure and nothing will fail more >>
Cloudonomics: Private, Public, or Hybrid?
How should one quantify the ROI, costs, and benefits of cloud alternatives? What are the cost drivers of private, public, and hybrid delivery models, and how will they evolve over time? Is pay-per-use good or bad? What are the main cognitive biases in enterprise decision-making?
Speaker – Joe Weinman, Communications, Media, and Entertainment Industry Strategic Programs, HP
I’m starting the tracks with Joe Weinman’s cloudonomics session. Joe’s session last year was a favorite of mine, so I’m back for more insights.
Joe is talking about some common cloud points/arguments that aren’t so clear. A few comments:
How to quantify value?
See Joe’s Meteorology slide, captured & posted by Randy Bias.
Joe referenced his 10 laws of cloudonomics. I also liked his 10 laws of behavioral economics.
Vapor or Cloud: virtualize or defer. Virtualization won’t give you 100% utilization. Defer, is deferring the workload. Not possible in consumer, event-driven workloads (tax filing, holiday shopping, sports event).
Hybrid: “Own the base, rent the spike”.
All other things being equal, if cloud services cost less than enterprise IT, then, use them.
If cloud services cost more than enterprise IT, then, don’t jump to conclusions. Need to consider demand spikes / patterns. Best to see Joe’s papers that demonstrate the math, decision factors.
Some architecture options for Hybrid Clouds:
Caveat: Remember the data. If it costs more to move (network) the data payload than the resource savings, don’t do it.
Next point: Time is money, the value of on-demand. Paper (pdf) & Abtract:
"Cloud computing and related services offer resources and services “on demand.” Examples include access to “video on demand” via IPTV or over-the-top streaming; servers and storage allocated on demand in “infrastructure as a service;” or “software as a service” such as customer relationship management or sales force automation. Services delivered “on demand” certainly sound better than ones provided “after an interminable wait,” but how can we quantify the value of on-demand, and the scenarios in which it creates compelling value?
We show that the benefits of on-demand provisioning depend on the interplay of demand with forecasting, monitoring, and resource provisioning and de-provisioning processes and intervals, as well as likely asymmetries between excess capacity and unserved demand…"
Smooth Operator: the value of demand aggregation Paper (pdf) & abstract:
“In industries such as cloud computing, lodging, and car rental services, demand from multiple customers is aggregated and served out of a common pool of resources managed by an operator. This approach can drive economies of scale and learning curve effects, but such benefits are offset by providers‘ needs to recover SG&A and achieve a return on invested capital. Does aggregation create value or are customers‘ costs just swept under a provider‘s rug and then charged back?
Under many circumstances, service providers—which one might call "smooth" operators—can take advantage of statistical effects that reduce variability in aggregate demand, creating true value vs. fixed, partitioned resources serving that demand.”
I think I’ll download some of Joe’s papers for the flight home.
The conference opens with short keynotes and a panel discussion on private clouds.
First up, fittingly, is Werner Vogels, CTO of Amazon. Werner opens with a riff on “the map isn’t the territory” and “the model isn’t reality”. From there, he goes to the 3-layer SaaS – PaaS – IaaS model. That model, is just a model. It shouldn’t restrict our view or understanding of cloud computing. Everything as a (cloud) Service. You should be able to use any service as if it is a cloud itself. This is thinking behind Elastic Beanstalk. “Let 1000 platforms bloom”.
Via the cloud, enterprises and startups have access to the same software services. Werner calls out security services and big data services. Analytics is typically a domain of enterprise, but the cloud gives access to deep analytics to startups.
Werner’s pitch today, “the ecosystem is what defines the cloud”. He is calling out some ecosystem examples. It should be noted though, that the twitter back channel is mixed positive and negative. There has been a running joke on twitter that “every time Jeff Barr writes a new post, a startup [AWS related service] dies”. On the other hand, Amazon’s expanding offerings, enables many business and software startups. So, it depends on your perspective.
Next, Dr. Lew Tucker, now with Cisco, on “The network is the computer, once again”. Lew is working his way to the Internet of Things, but hasn’t called it that. He sees “a world of many clouds”, media, government, industry etc. But, the underlying technology model will be the same. This brings him to Cisco’s position on the new data center, insulate infrastructure and run it as a service. And you know, the network is king in this new model.
Now, Randy Bias of Cloud Scaling. Randy is talking about enterprise cloud myths. 1. enterprises aren’t using Amazon 2. enterprises want to move legacy to the cloud, not develop greenfield apps.
What he is seeing, working on, is greenfield applications on public clouds for enterprise clients. Enterprises aren’t moving legacy to the cloud. This isn’t an outsourcing exercise.
Randy is walking through Amazon growth trends, “Amazon is winning”. Randy’s takeaways: go commodity, serve greenfield, embrace the change.
Now, Alistair Croll is moderating a mini-panel on private clouds. The panelists are:
This is a contrast to Randy Bias’ talk. Both panelists talking about porting existing applications to the cloud, and the need to port applications between public and private clouds.
Alistair: Data has surface tension, data wants to be together. In respect to the cost of moving data around.
In some cases, public cloud is front-end, data is in the back-end (private cloud). – Matthew Lodge
Matt Thompson brings up public data sets, cloud is the best place to aggregate and process public data sets. [Again, compute where the data lives]
Kevin McEntee, Vice President of Systems Engineering, Netflix
The Netflix story starts in 2008, with the highly publicized systems outage that delayed DVD shipments. “Went to the cloud looking for high-availability, found agility for business and developers. Agility by eliminating complexity”.
Kevin calls out work of Fred Brooks, No Silver Bullet. Need to eliminate accidental complexity. Netflix 2010, 80% of customer transactions running in the cloud.
In the cloud architecture, there is no single point of control over cloud spending. Cloud enables running with this business culture, “responsible individuals, worthy of freedom”.
For more on Netflix, see this interview and the Netflix Technology blog.
Now up is Willy Chiu, Vice President, IBM Cloud Labs. If you’ve followed the Jeopardy! Watson story, then you know what’s being said. If not, here’s a link.
Todd Papaioannou, Vice President, Cloud Architecture, Yahoo. This is an end-user story. Building the Yahoo! cloud to support Yahoo! services. Todd concentrates on elasticity.
What are impediments for delivering truly elastic clouds? Spin-up time is a major issue for ‘spike” events. 15-minutes to spin up a new VM is too long. So, load shedding is the only current option for them.
Derek Chan, Head of Digital Operations, Dreamworks Animation SKG
Derek is responsible for overall compute resources at Dreamworks. Derek is an end-user of cloud computing, not building clouds.
A single film, 4-5 years, 50+ million CPU hours. Imagine having a dozen films in flight. Tremendous peaks and troughs. Paying for only what they need is tremendous benefit.
In 2003, used HP’s utility rendering service. Wasn’t a cloud. Was off-site resource usage.
Need to co-locate compute and data.
In 2010, released 3 CG features in one year. Leveraged cloud to address the peaks. Over 7 million compute hours sent to IaaS.
2011, more movies, more cloud. Increase cloud capacity 10x. Increasing network bandwidth 3x.
Artists don’t know, don’t care about where rendering happens.
Cloud stack: RHEL (O/S), RHEV (virtualization), MRG (message queue), WebLogic, Jboss (middleware), deltaCloud (management)
Upcoming challenges: multi-tenancy, completely flex (payment model), cloud storage
Can see the evidence in Kung Fu Panda 2, 20% done in cloud.
The WSJ published an interesting article on commercial farming advances in Japan. According to the article, “The aim is to bring the concepts of lean manufacturing and continual improvement, or kaizen, to farming.”
The farmers are employing sensors, analytics, real-time location information and cloud computing to optimize planting time, crop rotation, worker productivity and threat (infection) detection.
“…Now the head of a commercial farm in the southern Japanese prefecture of Miyazaki, Mr. Shinpuku is back manning a desk with his eyes glued to a Web browser tracking every movement of his workers who handle 60 different fruits and vegetables across its 100 hectares.
"I don’t want to do this. My eyes will get bad," said Mr. Shinpuku, the 58-year-old president of his commercial farm Shinpuku Seika, which is comprised of 300 different plots of land. "I put up with it, because the benefits are obvious. Without this computer, I can’t do my job."
Shinpuku Seika is among the first farms to implement a Web-based "cloud computing" service developed by Japanese technology firm Fujitsu Ltd. Cloud computing is a loosely defined business term in which companies rent computing power from remote data centers via the Internet instead of buying machines to run software in house.
Shinpuku Seika has placed sensors out in its fields to collect readings on temperature, soil and moisture levels. Fujitsu’s computers then crunch the data and recommend when to start planting or what crops may be well-suited to a specific field.
In the past, farmers would make those decisions based on experience, but Mr. Shinpuku says a data-driven approach prevents younger, less experienced staff from making mistakes that could cost the bottom line.”
The pay-off? Measured in cabbage of course:
“The system is already paying off for Shinpuku Seika, which generates about 1.5 billion yen ($18 million) in annual revenue. Last year, it doubled the size of its carrot harvest and raised its cabbage output by 12%.”
Read the full article.
exploring the opportunities, issues, technologies, offerings and implications of cloud computing from a practitioner perspective
- by brenda michelson
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