The high-tech-savvy United States is a pioneer in cloud computing, and its enterprises have launched cloud services to lead the industry. Amazon AWS Cloud Services is just a niche service for small developers and startups, and it has now become a force in the cloud services industry with annual revenues of $7 billion. Microsoft and IBM have always had the advantage of working with large companies. Google Cloud Services Platform, under the leadership of industry veteran Diane Greene, is redoubled efforts to build its enterprise cloud service platform. Compare the leading companies in the cloud computing services industry such as Google, Microsoft and Amazon. Chinese companies such as Alibaba, Tencent, and Huawei are also in the field of cloud computing.
Cloud computing technology is currently the biggest change in the IT industry. Everything will move to the cloud, and users will share everything through cloud services, which will be an unprecedented service shift. Cloud computing technology is not new, and with the continuous maturity and rapid development of cloud computing technology in recent years, the changes brought by cloud computing have been seen in many industries. Friends who are familiar with cloud computing may not be unfamiliar. Cloud computing is a product of large-scale distributed computing technology and supporting business model evolution. Its development mainly relies on virtualization, distributed storage, data management, programming mode, Information security and other technologies.
In recent years, the evolution of business models such as hosting, backward charging, and on-demand delivery has also accelerated the turning point in the cloud computing market. Cloud computing not only changes the way information is provided, but also subverts the delivery model of traditional ICT systems. Rather than saying that cloud computing is a technological innovation, it is better to say that cloud computing is a shift in thinking and business models. In this issue, let's take a look at what are the core technologies in cloud computing technology.
Virtualization technology
Virtualization is one of the most important core technologies of cloud computing. It provides infrastructure-level support for cloud computing services and is the main driving force for ICT services to move toward cloud computing. It can be said that without virtualization technology, there is no landing and success of cloud computing services. As cloud computing applications continue to heat up, the industry's emphasis on virtualization technology has also reached a new level.
Virtualization is a form of computing that simulates computer hardware in software and provides services to users with virtual resources. Designed to rationally allocate computer resources to provide services more efficiently. It breaks the physical division between the hardware of the application system, thereby realizing the dynamic of the architecture and realizing the centralized management and use of physical resources. The biggest benefit of virtualization is to increase the flexibility and flexibility of the system, reduce costs, improve services, and improve resource utilization efficiency.
From the perspective of performance, virtualization is divided into two application modes. One is to virtualize a powerful server into multiple independent small servers to serve different users. The second is to virtualize multiple servers into a powerful server to perform specific functions. The core of these two modes is unified management, dynamically allocate resources and improve resource utilization. In cloud computing, both modes have more applications.
Distributed storage technology
We all know that cloud computing is characterized by very fast storage and processing of data. In order to ensure high reliability of data, cloud computing usually uses distributed storage technology to store data in different physical devices. This model not only gets rid of the limitations of hardware devices, but also has better scalability and can respond quickly to changes in user needs.
Distributed storage is not exactly the same as traditional network storage. The traditional network storage system uses a centralized storage server to store all data. The storage server becomes a bottleneck of system performance and cannot meet the needs of large-scale storage applications. The distributed network storage system adopts a scalable system structure, uses multiple storage servers to share the storage load, and uses the location server to locate the storage information, which not only improves the reliability, availability and access efficiency of the system, but also is easy to expand.
Programming Mode The distributed parallel programming model was originally created to make more efficient use of hardware and software resources, allowing users to use applications or services faster and easier. In the distributed parallel programming mode, complex task processing and resource scheduling in the background are transparent to the user, so that the user experience can be greatly improved.
For example, MapReduce is a Java, Python, and C++ programming model developed by Google. It is mainly used for parallel operations on large-scale data sets (greater than 1TB). The idea of ​​MapReduce mode is to decompose the problem to be executed into Map (Map) and Reduce (Simplify). First, the data is cut into unrelated blocks by Map program, and distributed (scheduled) to a large number of computers for processing. The effect of the operation, and then the result is aggregated and output through the Reduce program.
Large-scale data management
Nowadays, in the era of big data, dealing with massive data has become a very important task of cloud computing services. Cloud computing not only guarantees the storage and access of data, but also enables specific retrieval and analysis of massive data. Because cloud computing needs to process and analyze massive amounts of distributed data, data management technologies must be able to efficiently manage large amounts of data.
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Google's BT (BigTable) data management technology and the open source data management module HBase developed by the Hadoop team are typical large-scale data management technologies in the industry. BigTable is a non-relational database. It is a distributed, persistent storage multi-dimensional sorting Map. BigTable is built on GFS, Scheduler, Lock Service and MapReduce. Unlike traditional relational databases, it uses all data as objects. Processing, forming a huge table for distributing large-scale structured data.
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