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云计算的基础架构平台(云计算的功能和架构)

云计算
2023-12-22 01:02:28
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What are the main components of the Microsoft cloud computing platform?

Microsoft cloud computing platform includes three major components: WindowsAzure, SQLAzure, and WindowsAzurePlatformAppFabric. WindowsAzure can be regarded as an operating system for cloud computing services and the basic service layer of cloud computing. It is mainly engaged in virtualized computing resource management and intelligent task allocation; SQLAzure is a database in the cloud. SQLAzure runs the relational database service of cloud computing and is It is an implementation of cloud storage and provides network-based application data storage services. Its foundation is SQLServer2008; AppFabric is a Web-based development service that can connect and interoperate existing applications and services with the cloud platform. It becomes even simpler. As a middleware layer, AppFabric will serve as a bridge between non-cloud programs and cloud programs. It provides two major services, service bus and access control. AppFabric allows developers to focus on their application logic instead of deploying and managing the infrastructure of cloud services.

What are the main technologies of public cloud computing infrastructure?

Cloud computing system China uses many technologies, among which programming models, data management technology, data storage technology, virtualization technology, and cloud computing platform management technology are more critical.

(1) Programming model

MapReduce is a java, Python, and C++ programming model developed by Google. It is a simplified distributed programming model and efficient task scheduling model, using Parallel operations on 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 blocks through the Map program, and then allocated (scheduled) to a large number of computers for processing to achieve distributed The results of the operation are then summarized and output through the Reduce program.

(2) Massive data distributed storage technology

The cloud 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, using Redundant storage ensures 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 underlying hardware. It includes a split mode that divides a single resource into multiple virtual resources. It also includes an 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 a large number of servers distributed in different locations, and hundreds of applications running at the same time. How to manage them effectively? For these servers, it is a huge challenge to ensure that the entire system provides uninterrupted services.

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 the reliability of large-scale systems through automated and intelligent means. operations.

Analysis of advantages of shared infrastructure platform

Small and medium-sized enterprises initially start by deploying one server, and then slowly expand to three or four servers of different models, generations, and even different brands. . In the process, they also install network switches to connect these servers, as well as different storage platforms to retain their growing data. Eventually, there were interoperability issues, and a variety of devices taking up a lot of space that were not only cluttered with connections, but also extremely difficult to maintain. Such a chaotic IT environment makes it difficult for enterprises to promote business growth and improve work efficiency.
In recent years, with the convergence trend brought about by big data and cloud computing, various manufacturers have launched integrated product solutions. The idea behind this approach is to integrate multiple information technology (IT) components into a single, optimized computing solution. Among them, Dell proposed the concept of shared infrastructure platform.
As the name suggests, this is an infrastructure platform that integrates servers, data storage devices, network equipment and IT infrastructure management, as well as software for automation and business processes. For example, Dell's PowerEdge VRTX is specially designed for small offices.
From the perspective of small and medium-sized enterprises, shared infrastructure platforms first reduce costs, which is the biggest boon for small and medium-sized enterprises with limited budgets. Using a shared infrastructure resource pool, computing, storage, power, and cooling resources can all be shared, allowing enterprises to reduce total cost of ownership in terms of energy efficiency, system expansion efficiency, and computing density.
Secondly, it eliminates hardware complexity and sprawl problems. Since the shared infrastructure platform has integrated resources such as servers, storage, and networks, there are no hardware compatibility issues, and there will be no server spread due to physical expansion.
Management is more convenient. Shared infrastructure platforms consolidate server, storage and network management functions into a single management console, making management easy and reducing the learning curve, eliminating the need to spend time learning a whole new set of tools to manage all your resources.
The biggest highlight is shared storage. Small and medium-sized businesses can get SAN (storage area network)-like functionality and can take full advantage of virtualization and high availability. Shared storage can be configured through tools for managing servers and I/O, allowing for more efficient management of the system's life cycle.
Obviously, the past era of "providing enterprises with a lot of parts and us assembling them ourselves. System complexity, high cost and difficulty in management are not problems" has passed. Today's enterprises want to organize all their devices in a unified manner and place them on a unified platform.