May 23-May 25, 2012 cloud base of China Cloud Computing Conference opened the curtain, show cloud practice, explore cloud trend, share cloud future. The cloud base shows the latest technologies and new products in the field of cloud computing, and discusses the development trend of cloud computing, the great value of large data, the energy-saving of data center in cloud times and so on. Reitao, vice president of cloud technology, said that there are three ways to apply large data to the ground. The first is the data service itself, the data service is more to provide some resources services, as well as some traditional data capabilities of the services, such as the preservation of data, long-term data preservation, as well as some professional maintenance for large enterprises, disaster tolerance capacity. The second block is more information, this piece uses a lot of cloud machine loss of some of the core technology changes, such as the preservation of traditional data, the original way, file system or block data, is not retrieved, we are in the cloud through a number of new data packaging methods can achieve long-term preservation. Third knowledge service, one by one to introduce you. From data to information to knowledge, the content of big data.
Cloud Technology Vice President Reitao Reitao: This afternoon's theme is the cloud in the key two, from the cloud platform to large data, basically from the cloud to come through a great two key processes, you know the end of 2011, The Wall Street times comments on the post-PC era's Big four Giants to show the current cloud industry era, Amazon, Facebook, Google and Apple each have their own image and characteristics, Amazon is a book-selling internet company, it covers every use, the stock of IT assets packaged out, As a form of service submission, Amazon is also the cloud's most dominant and more explicit form of cloud appearance. The other two Facebook, Google is not selling resources, selling is the ability to sell it to the data itself processing and analysis, and ultimately to reflect the value. Just as Facebook and Google are the second ability we explore today, the big numbers need to be mastered. Apple is looking more at it for consumption, is also a hot topic in the 2011, so that the whole market pie expanded, service it in the end of the traditional enterprise, affordable file server, mail server high-end enterprise also extended to our SMB market, extended to each individual consumer, This afternoon's topic will take two hours to share the top three types, cloud platforms, and large data of the four giants through the availability of an intelligent terminal network at any time.
Let's start with big data and discuss what's going to be discussed when we talk about great What do you think most people are looking at? The market is hot enough, from the first major initiative McKinsey released last year, the 150-page big data monitors, by the U.S. government this year to adopt the research report, to invest nearly more than 40 billion dollars in the big data, it has gone from the market to the landing process.
we hear more about big data in the marketplace? Or Marvell itself, more and more platform-level vendors to do a lot of the preach, that is, the tool level. In fact, what we're going to talk about today is going to span these, we're not just talking about products and technology, it's about what the big data is driving, and it's evolving from it as a supporting role to it as a driving force for business innovation, This is what we want to share with you one hours later. So we're going to share more with you from the pattern of business patterns and the value of the data itself.
these numbers, 35.2ZB, what does that mean behind this number? means bigger market, bigger pie waiting for all it practitioners to dig and explore. This data itself I do not speak more, through this information itself I give you describe the market.
This market has more than tens of billions of dollars in investment, this market with the traditional bi, a lot of people talk about big data is not you do based on data analysis, this and the traditional system has a very large difference, the difference between bi and da data? We can see from a Google data that the following yellow, pink and blue lines are bi, which is basically not much change in the market, and does not attract too many investors and technology enthusiasts, on the contrary, the big data from 2005 to continue to receive market attention, Because it has a very significant difference in the technical architecture and resolution of the problem with BI, where is the difference? I believe it may not be clear within one hours today, we have a book outside, the solution itself for the value of the data how to reflect in the production of life.
many new Big Data winner are distinguishing between bi and DA data, both from the technical level and the data value level, the difference is very large. Manufacturers are also very keen to invest in this, from the capital sector to now, from 2005 to date, the big investment in this field, IBM, EMC, have spent more than 10 billion U.S. dollars invested in this area.
I also share a report from the Wall Street times this February, it describes a future of the core competitiveness of enterprises, we are talking about the market from the perspective of why this market is so hot, this report tells a core concept, what is the core value assets of the enterprise, which listed the level of IT structure, From underlying infrastructure to proprietary it architectures, servers, data centers, applications to businesses, and analytics. We analyze the most profitable software of the year, and the report sets out the idea of focusing on the back-line market, behind office, focusing more on trading, on the process itself, how I do better IT support, and the ability to make this job more efficient and agile.
when you reach a certain level of performance, what is the most reasonable use of my object, and when all the efficiency is highest, where is your core competitive power? This describes the data itself, and the enterprise's data will be the core of your ability to differentiate yourself from the rest of the enterprise, and it will not be a Huo in the next tier of assets. Infrastructure we can also with the operators high-end enterprises, selling the server is already a very low product, what is you in the enterprise can lay their own core values of content? is the data.
traditional businesses need a transformation, back office to the front, the front is the market, how to guide your business through your IT ability, this is the core value of the future software companies.
just mentioned the market, 70 from the technical framework we also see a big challenge, which analyzes a traditional business structure, such as using Java EE, Database,web can be extended horizontally, Java EE.
What is the problem that
distributed computing solves in the technical architecture? We don't talk much about technology itself, we have a macro concept to give you a solution, before we look at SOA, in order to ensure that a business can be a good SOA request can return, I was to make my application more and more, but the application to process data, I have to continue to input and huff and puff, IO is a big bottleneck for me, the big idea of distributed computing is that I no longer transfer data, the data distributed on the structure of the put, the scheduling is the application, cut an application into hundreds, thousands of satisfied calculations, data is an opposing design concept, With this approach, more data-sensitive business operations can be implemented later.
What benefits does this architecture bring? To share Facebook apps, I can care about the second level my friends can see that it supports 20 billion processing every day, 200,000 times per second Click Processing, the whole is less than 30 seconds delay, 30 seconds is generated from the client, in the backend implementation processing, and then dynamic of other services, The entire service is used in the case of 820 million users. Objectively speaking, we can see that the Stream data 處理 is similar to Java EE when applied to traditional ideas.
(Responsible editor: The good of the Legacy)
