Cloud economics: Managing the cost challenges of cloud
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Cloud economics: Managing the cost challenges of cloud

Cloud storage is frequently presented as a cost-effective option. According to the narrative, businesses can reduce costs by leveraging the public cloud to replace employees, infrastructure, and data centers. However, cost savings may be challenging to obtain. The cloud's capacity to scale up quickly is one of its appealing characteristics, but it can also make cost management more challenging. As more businesses choose a multi-cloud or hybrid cloud approach, CIOs must ensure operational flexibility doesn't come at a high cost.

According to the Enterprise Cloud Index research report, 64% of businesses anticipate using multi-cloud systems within the next three years. In addition, 43% of respondents indicated it is difficult to manage expenditures across contexts. Those polled also anticipated rising expenses due to transferring workloads between clouds.

The cloud provides nearly infinite capacity and the freedom for businesses to pay for the required resources. These are the cloud's main advantages. Businesses are not restricted by the requirement to construct data centers and are not required to pay for the capacity they do not use.

The cost of flexibility

There is a cost for flexibility, just like any other rental arrangement. Additionally, cloud service providers provide discounts to clients who can commit upfront or for an extended time. According to some experts, this complicates pricing forecasting for IT departments and undermines the pay-as-you-go cloud model.

The larger cloud providers tend to promote exclusive technologies that lock customers in. Businesses are less likely to be able to consolidate their needs with a single provider or utilize the fear of moving to reduce costs if transferring between suppliers is more difficult for them.

The many designs and methods that cloud providers use serve to support this. It is more difficult to switch between clouds and design a solution that functions equally well across different clouds because suppliers each have their own opinions on what constitutes best practice.

Because practically anybody can launch cloud services, it is challenging for IT teams to keep control, making the situation worse. Having visibility into how cloud services are used and used presents the main problem in cloud cost control. Decentralized use of cloud services is the norm for many organizations.

Understanding bills is challenging, if not impossible, in most organizations due to the decentralized nature of cloud consumption. The underlying pricing itself is another problem. Pricing for the cloud is hardly obvious.

Amazon's cloud pricing information is a 2GB JSON file. As a result, comparing the offerings is challenging. This explains why you'll often find three or four data scientists sitting on the cloud management teams of big businesses. This is no longer a task for MS Excel.

Right-sizing and forecasting

Accurate demand forecasting and ensuring that what is purchased is used are arguably the two main issues facing businesses employing the cloud.

The main difficulty in the cloud is cost predictability. How much will shifting to the cloud cost us annually, over two years, and other pertinent questions are the main ones that CIOs are asked when attempting to make a financial case for it? Does a scalable solution imply that our costs will change from one month to the next and from one year to the next?

Purchasing more capacity than a project or corporation requires is a major cause of spending too much money. Although it is not a precise science, forecasting is helpful in this situation because one of the benefits of the cloud is its ability to add capacity swiftly.

You can pick a cloud plan based on how often you anticipate using the platform, but the problem is that capacity can be added far too easily. In the past, if someone required more computing power, they would ask the IT department, which could determine it wasn't worth the money. Without explicit purchase guidelines, it is too simple for developers and users to add computation, memory, or storage to the cloud.

Scaling down

Waste can also result from failing to leverage the cloud platform's scalability features or from continuing to use capacity after an activity has been completed. Close down or reduce the size of inefficient resources. This entails locating redundant test and development servers and shutting them off. Businesses should consider reducing system capacity after hours or during less busy times. Organizations can migrate less often accessed data to less expensive storage tiers or specific archiving products, which also applies to storage. On-premise technology places hardware restrictions on business units. Increasing the cloud's capacity without considering the cost is too simple.