Misconfiguration of cloud repositories can lead to cost overruns, let alone hinder the performance of data processing. Enterprises can adopt some methods to control the data cost of cloud computing, so that enterprises can improve performance and obtain greater return on investment.

Powerful cloud computing data management functions can bring more advantages to enterprises. It provides greater flexibility in data access, so that enterprises can expand the database faster, and even reduce the total cost of ownership of data management in the long run. For these reasons, cloud platforms are rapidly becoming the preferred location for storing enterprise data. By 2020, about 50% of global enterprise data will be stored on cloud platforms, compared with only 30% in 2015. As a result of the epidemic, enterprises have accelerated cloud adoption and the rise of new data-driven applications.

However, in the initial stage of cloud adoption, data management seems to be a difficult task. In terms of speed, latency and availability, people may not see the same level of performance used in on premises facilities immediately after migrating to the cloud platform. In addition, mismanagement and incorrect database configuration may even increase the cost of cloud computing and consume more resources.

When formulating cloud computing data management strategies to control costs and improve performance, the following six points need to be considered:

1. Optimize the data movement frequency in hybrid cloud or multi Cloud Architecture

The real cost of cloud computing data management comes from mobile data rather than storage. Most cloud computing providers will charge users for moving data out of their cloud platform, but will not charge users for moving data in. Some cloud computing providers charge users according to the time when the data is removed - that is, whether the user deletes it after 30 days, 60 days, 90 days or more. Depending on the supplier selected, early deletion / removal penalties may be involved. Therefore, the data management plan including regular update, backup, cleaning and deactivation will determine the cloud computing cost of the enterprise.

Try to optimize the frequency of data movement to avoid premature movement or deletion, and maintain a minimum capacity threshold to increase cost advantage. Enterprises can also pay close attention to cost saving services or products provided by cloud computing providers. For example, Harish grama, general manager of IBM cloud, said that the company would not charge any export fees for moving data out of the cloud platform.

2. Invest in physical and private cloud connectivity for better performance

In an on premises environment, data performance will be better than the cloud, because enterprises can move data in the same physical location without relying on the availability of external networks or third-party environments. Cloud interconnection can be used to achieve the same performance in the cloud computing environment. Cloud interconnection is essentially the private, direct and high-speed connection of the cloud platform selected by the enterprise. This is particularly desirable for hybrid cloud environments where data may be moved regularly into and out of cloud platforms.

3. Use data compression to reduce the size of cloud computing database

Large cloud computing databases are not only expensive, but also affect performance. For example, the export fee paid by enterprises to move data out of the cloud platform is directly proportional to the amount of data sets stored. In addition, large databases take longer to move, which may affect the performance of business applications and other data-driven tools.

This is where cloud computing data compression technology comes into play. Efficient data compression can help enterprises reduce storage costs and even optimize edge data processing. Enterprises can build custom compression code suitable for their specific data types, or benefit from third-party tools, such as the data compression code library of Intel Integrated Performance primitives.

4. Using cloud computing data backup as a service (baas)

Cloud computing data backup as a service (baas) solves the cost problem from the perspective of resource consumption model. Enterprises can cooperate with cloud computing data backup as a service (baas) providers instead of managing cloud computing data completely in on premises facilities. Cloud computing providers will configure data movement frequency, perform data compression and implement interconnection for enterprises, and pay subscription fees monthly or annually.

For small and medium-sized enterprises with small amount of data but complex configuration, resulting in rapid cost growth, cloud computing data backup as a service (baas) can significantly reduce the cost of cloud computing data management. In this regard, coherence's new data protection baas is a solution worth considering.

5. Create mirror locations using multiple availability zones on the cloud platform

Mirror locations help create redundant copies of data, so the enterprise can ensure availability even during downtime or unpredictable outages. If the enterprise's business is running in a public cloud environment. In this case, it is relatively simple - enterprises can configure multiple cloud computing areas to mirror their data, and choose the availability area away from the original storage site. However, this is slightly more complicated in a hybrid cloud environment because on premises servers cannot be easily mirrored.

6. Focus on increasing the value generated by enterprises from cloud data

The best way to alleviate the performance and cost problems surrounding cloud computing data management is to improve the business value that enterprises can obtain from the data itself. Once it is determined that cloud computing data (for all its complex configuration and maintenance requirements) can promote smarter business decisions, improve daily processes, and have a positive impact on enterprise revenue, enterprise leaders will be more likely to invest in their cloud computing data management capabilities.

To achieve this, you can consider using tools such as atscale to connect cloud computing data to business intelligence platforms, such as power Bi, looker or tableau, without moving data. This key function is very different because enterprises can save export costs while adding scalable business intelligence coverage.

conclusion

Finally, despite the cost and performance problems, cloud computing data management is an inevitable reality for large distributed and digital priority enterprises. Its benefits in terms of business value and it infrastructure cost reduction far outweigh its potential disadvantages. These six strategies will help to build a perfect combination of public cloud, hybrid cloud or multi cloud data systems, avoid performance problems or cost overruns, and bring enterprises closer to data-driven companies.