The analysis of the need and application of cloud computing strengthening management

Economic development leads to the emergence of a service infrastructure that provides software and computing capabilities, commonly known as cloud services or cloud computing. It is a new way of sharing infrastructure that allows users to access their applications from anywhere connected by a device. Large system pools can be connected to provide various IT services. Many factors drive the need for such environments, including connectivity devices, real-time data streams, adoption of SOA, and rapid growth in Web 2.0 applications such as search, open collaboration, social networking, and mobile commerce. In addition, the improvement of the performance of digital components has greatly increased the size of the IT environment, thus further strengthening the need for a unified cloud management. There is no doubt that cloud computing has a bright future.

Example Analysis of cloud computing

Finally, the paper makes a simple analysis of the cloud computing platform of Google and IBM, the two companies that lead the cloud computing trend.

Google's position in the cloud is still not shaken in a short time, and its open platform embodies the essence of the cloud computing model. The vast majority of the basic software required by Google's cloud computing services is open source, meaning that users are free to get the code and modify it. Since 2003, Google has published papers in the top-tier conferences and magazines in computer systems research for several years, revealing its internal distributed data-processing methods and demonstrating its core technologies for cloud computing. Google's cloud computing technology is actually tailored to Google's specific Web applications. In view of the large scale of the internal network data, Google proposes a set of infrastructure based on distributed parallel clustering, and utilizes the ability of software to deal with the frequent node failure problems in the cluster. The cloud computing infrastructure that Google uses includes four separate, tightly knit systems. Including Google file system, which is built on the cluster, and the Map/reduce mode (mapping/simplifying programming mode) for Google application features. Distributed lock mechanism Chubby and the model simplified by Google developed a large-scale distributed database bigtable.

GFS (Google File system) is designed for the Google application itself. A GFS cluster contains a master server and multiple block servers that can be accessed by multiple clients.

In order to give people unfamiliar with distributed systems the opportunity to build applications on a large cluster basis, Google has also designed and implemented a large scale data processing programming specification Map/reduce system. In this way, non-distributed professional program writers can write applications for large-scale clusters without worrying about the reliability and scalability of clusters. Application writers only need to focus on the application itself, while the handling of the cluster is referred to the platform for processing. Map/reduce provides reliability by distributing large-scale operations of the dataset to each node on the network; Each node periodically reports back the completed work and status updates. If a node remains silent for more than a preset interval, the master node (similar to the master server in Google File system) records the node state as dead and sends the data assigned to the node to another node. Each operation uses the atomic operation of the named file to ensure that no parallel threads are in conflict; When the file is renamed, the system may copy them to a different name than the task name.

The third cloud computing platform is Google's bigtable system for extending database systems to distributed platforms. To handle a large amount of formatting and semi-structured data within Google, Google has built a large database system bigtable with weak consistency requirements. In addition to these three parts, Google also established a distributed program scheduler, distributed lock services, such as a series of related cloud computing services platform.

IBM, the blue giant, also cast a heavy bet on it, and named it "Blue Cloud". IBM has all the benefits of developing a cloud computing business: Application servers, storage, management software, middleware, and so on, so IBM will naturally not miss a chance to become a celebrity. The idea of a new enterprise data center has recently been introduced, combining the Web-centric cloud computing model with the benefits of the current enterprise data center. An article in China's Cloud computing network gives the new enterprise data center model and its infrastructure services framework.

The new enterprise data Center will be the center of virtualization, efficient management that will use some of the tools and technologies used by the WEB-centric cloud and be generalized to be adopted by a wider range of customers, as well as enhancements to support secure transactional workloads. With an efficient and shared infrastructure, organizations can react quickly to new business requirements, parse large amounts of information in real time, and make informed business decisions based on real-time data. The new enterprise Data Center is a new evolving model that delivers efficient and dynamic new approaches that help align IT and business goals. As shown in Figure 3, the infrastructure services of the new Enterprise data Center can be logically divided into different tiers from a high-level architectural perspective. The physical hardware layer is virtualized to provide a flexible and adaptable platform to improve resource utilization. The next two tiers are virtualized environment layers and management, which are key to the new Enterprise data Center infrastructure services. By combining these two tiers, you can ensure that resources within the datacenter are managed efficiently and quickly deployed and configured. In addition, the new Enterprise data Center is designed to handle mixed-mode workloads.