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Cloud data storage needs to help solve data cost dilemmas
The high cost of cloud data storage shatters the dream of a corporate public cloud business case. Some companies say they can purchase hard drives at the same cost as monthly cloud storage and use case fees. But for cloud consumers, it may be difficult to figure out where the price difference is. In order to fully understand this content, it is necessary to look at what you actually got when you purchased cloud storage.
Disk capacity alone is relatively inexpensive, especially for large-scale applications. You can spend more than $100 to buy a terabyte of external hard drive. For example, if you want a large server with 100TB capacity, you can store 10GB on this server for 10,000 end users. Of course we assume their I/O activity is limited.
On the other hand, a single user with 10GB of storage and high transaction processing rates can easily consume the entire server or upload a cloud provider's data center router and storage area network (SAN). Cloud data storage costs are higher when data is accessed on a regular basis, especially when accessed outside of the cloud. The cost burden reflected by the data usage fee is imposed on the cloud administrator. Businesses believe that accessing cloud data forces them to extend the connection speed in order to avoid congestion. This in turn leads to an increase in network costs.
Cloud consumers need to help manage data costs, and four strategies have been formed to help them address these cost dilemmas.
Discover data storage and usage levels. When designing an application and associating it with data, consider creating a storage hierarchy. At the same time, the in-memory data cache may seem stupid in the cloud, but by keeping most of the memory element access, it is possible to reduce data access rates and thus reduce costs. Study how to combine the different classes of cloud storage into one level – from real-time to archiving, all can affect data prices.
Consider a local storage as a service to support cloud applications. Although block or file system I/O between local resources and the cloud may not be cost effective or smooth performance, it may be practical for storing data locally and presented to the cloud in the form of an RDBS query level interface (DBaaS). Hosted app. This can reduce the cost of cloud data, help cloud-hosted applications access local data faster, and companies can move more applications to the cloud. This strategy is most effective for large database queries that produce relatively small result sets.
Use a summary database for cloud data storage. Cloud analysis is especially capable of operating on summary data, rather than on business/transactional detailed documentation. Go to the store to find product sales, not registration details, and reduce the number of records by several orders of magnitude. Doing so can reduce data storage costs.
Business-critical applications are the hardest to deploy in the cloud because they often use large databases to record transactions. In retail applications, for example, these databases contain markets and changed inventory. Although many companies deploy web front ends for business-critical applications in the cloud, we want cloud backup application components. In this case, the key is to control the cost of data and possibly create multi-level applications.
Consider the Web retail system. These systems typically generate most transactions for very little data. If the front end has an idle "deposit" item that represents a quantity that is actually less than this amount, the company can safely accept orders without checking inventory. This takes the inventory project out of cloud storage. So the company can afford to access the cloud storage database every time, this system is to save money.
The application can then send updates to the local database at a certain frequency and receive an additional "allotment" that they can revoke when the order is placed. This allows most orders to be processed and even a brief downtime in the data center. Similar to the process of caching, data can be used for other online activities as well as saving corporate money.
Save the backup copy. Consider saving a copy of some data on some cheap backup network sites and then "recovering" it to a more expensive cloud storage when needed. Data is not available during recovery, but the impact of power outages is minimized. For databases with low-level activities, this strategy may be the most optimal way to manage costs, while also capturing offline processing options for events after data center failures.
Because cloud computing has changed all aspects of IT planning, database software and architecture have changed. Companies must focus on how these changes affect them, whether they are virtual or private, but also their public cloud choices and prices. Storing data in the cloud can never be cheaper than storing data on a hard disk, but the advantages of using cloud storage technology may give buyers a good cost and a high input-output ratio.