云计算包含的主要技术有哪些(云计算涉及哪些技术)

The main technologies of cloud computing are as follows:

1. Programming model

MapReduce is developed by Google Java, Python, C++ programming model, it is a simplified distributed programming model and efficient task scheduling model, used for parallel operations of large-scale data sets (larger than 1TB). The strict programming model makes programming in a cloud computing environment very simple.

The idea of ​​MapReduce mode is to decompose the problem to be executed into Map (mapping) and Reduce (simplification). First, the data is cut into irrelevant areas through the Map program. Blocks are allocated (scheduled) to a large number of computers for processing to achieve the effect of distributed computing, and then the results are compiled and output through the Reduce program.

2. Massive data distributed storage technology

The cloud computing system is composed of a large number of servers and serves a large number of users at the same time. Therefore, the cloud computing system uses distributed storage. Data uses redundant storage to ensure data reliability. The data storage systems widely used in cloud computing systems are Google's GFS and HDFS, the open source implementation of GFS developed by the Hadoop team.

3. Massive data management technology

Cloud computing requires the processing and analysis of distributed and massive data. Therefore, data management technology must be able to efficiently manage large amounts of data. The data management technology in cloud computing systems is mainly Google's BT (BigTable) data management technology and the open source data management module HBase developed by the Hadoop team.

4. Virtualization Technology

Virtualization technology can isolate software applications from the underlying hardware. It includes a split mode that divides a single resource into multiple virtual resources, and also Including aggregation mode that integrates multiple resources into one virtual resource. Virtualization technology can be divided into storage virtualization, computing virtualization, network virtualization, etc. based on objects. Computing virtualization is further divided into system-level virtualization, application-level virtualization and desktop virtualization.

5. Cloud Computing Platform Management Technology

Cloud computing resources are huge in scale, with numerous servers distributed in different locations, and hundreds of applications running at the same time. How to effectively manage these resources? Server, ensuring that the entire system provides uninterrupted services is a huge challenge. The platform management technology of cloud computing systems can enable a large number of servers to work together, facilitate business deployment and activation, quickly discover and recover system faults, and achieve reliable operation of large-scale systems through automated and intelligent means.

The difference between cloud computing platform and traditional platform

Cloud computing is a brand new computing model. The basic technology of the Internet and the scalable virtual resources are the basis of this new digital technology. main feature. There is an essential difference between cloud computing and traditional platforms. There is a saying that cloud computing is a business model. By renting a virtual digital platform, the value of this business model can be reflected as much as possible.

Traditional platforms are created through their own infrastructure. This platform has certain requirements for corporate fixed assets and business models. Flexibility and sudden traffic changes can effectively save money. Enterprise platform spending. The connection of multiple devices into an organic whole is a characteristic of the cloud computing platform. This platform is created on the basis of digital technology, and continuous improvement and development can ensure the actual application effect of the platform.

Cloud computing covers a wide range of areas, with a data communications background and authoritative certification, which increases the influence in this field. So what are the skills of cloud computing?

Cloud computing systems use many technologies, among which programming models, data management technology, data storage technology, virtualization technology, and cloud computing platform management technology are the most important.

(1 )Programming model

MapReduce is a java, Python, and Chop programming model developed by Google. It is a simplified distributed programming model and an efficient task scheduling model, used for parallel computing of large-scale data sets (more than 1TB) .The strict programming model makes programming in the cloud computing environment very simple. The idea of ​​the MapReduce model is to decompose the problem to be executed into Map (mapping) and Reduce (simplification). First, the data is cut into irrelevant blocks through the Map program , allocate (schedule) a large amount of computer processing to achieve the effect of distributed computing, and then summarize and output the results through the Reduce program.

(2) Massive data distributed storage technology

Cloud The computing system consists of a large number of servers and serves a large number of users at the same time. Therefore, the cloud computing system uses distributed storage to store data and ensure the reliability of the data through redundant storage. A data storage system widely used in cloud computing systems It is an open source implementation of HDFS developed by the Google GFS and Hadoop teams.

GFS is the Google File System.

System) is a scalable distributed file system for large, Distributed and accessing large amounts of data. The design concept of GFS is different from traditional file systems. It is designed for large-scale data processing and Google's application features. It runs on cheap ordinary hardware, but can provide fault tolerance. It can be used for Provide services with high overall performance to a wide range of users.

A GFS cluster consists of a master server and a large number of block servers, and is accessed by many clients. The master server stores the metadata of the file system, including namespace, Access control information, mapping from files to blocks and the current location of blocks. Also controls system-wide activities such as block lease management, orphan block garbage collection, and block transfers between block servers. The master server periodically passes HeartBeat information Communicate with each block server, issue instructions to the block server, and collect its status. Files in GFS are divided into 64MB blocks, with redundant storage, and each data is stored in the system with more than 3 backups.

The replacement of the client and the main server is limited to metadata operations, and all data communications are directly connected to the block server, which greatly improves the efficiency of the system and prevents the main server from being overloaded.

(3 )A large amount of data management technology

Cloud computing needs to process and analyze a large amount of distributed data, so data management technology must be able to effectively manage large amounts of data. The data management technology in cloud computing systems is mainly Google BT (BigTable) Data management technology and the open source data management module HBase developed by the Hadoop team.

The five key technologies of cloud computing are as follows: cloud computing platform management technology, distributed computing programming model, distributed massive data storage, massive data management technology, and virtualization technology.

1. Cloud computing platform management technology: The platform management technology of cloud computing systems can enable a large number of servers to work together, facilitate business deployment and activation, and quickly discover and recover system failures.

2. Distributed computing programming model: Cloud computing adopts a simple distributed parallel programming model Map-Reduce. Map-Reduce is a programming model and task scheduling model. It is mainly used for parallel operations of data sets and scheduling of parallel tasks.

3. Distributed massive data storage: Cloud computing systems use distributed storage to store data and use redundant storage to ensure data reliability. The redundant method ensures low cost through task decomposition and clustering, and uses low-end machines to replace the performance of supercomputers. This method ensures the high availability, high reliability and economy of distributed data, that is, storing multiple copies of the same data. .

4. Massive data management technology: The data management technology in cloud computing systems is mainly Google's BTsT~lO data management technology and the open source data management module HBase developed by the Hadoop team.

5. Virtualization technology: refers to the fact that computing components run on a virtual basis rather than a real basis. It can expand the capacity of hardware, simplify the software reconfiguration process, and reduce the overhead and related costs of software virtual machines. Support a wider range of operating systems.