Cloud computing trends and strategies are evolving at increasing speeds nowadays, spearheaded by the adoption of multi-cloud models. To illustrate, the market size for public cloud is expected to reach $675 billion this year and is projected to exceed $800 billion by 2025 as enterprises see the many benefits of cloud computing from scalability to efficiency. Its cost-efficiency advantage, in particular, is a major factor for enterprises.

It is important to emphasize that using the cloud does not automatically translate to cost efficiency. Organizations need to watch out for potential hidden costs or unnecessary expenses associated with cloud services. Also, it is crucial to carefully evaluate costs to see which ones might be reduced or even avoided altogether.

Many organizations tend to overlook or pay insufficient attention to these costs and end up having issues with their cloud infrastructure spending. Here are a few types of infrastructure costs that enterprise teams should keep in mind as their cloud computing strategies mature. 

Compute Costs for Idle Resources

Compute costs are the charges related to the use of computing resources such as virtual machines, containers, and servers. These costs are based on a number of factors – specifically the duration of use, instance type, the location of the user, operating system, and the use of additional features such as load balancers and managed databases.

The changes to Terraform Cloud’s pricing model that were announced in June 2023 largely involve compute costs, for instance. Terraform’s hosted service tier shifted to a Resources Under Management (RUM) basis for pricing, which entails billing based on the number of resource connections, not the number of users. The company now imposes charges according to the number of load balancers, buckets, clusters, and instances that connect to Terraform, prompting many organizations to look into other options.

A significant number of enterprises usually do not account for idle resources and the merits of rightsizing when they examine their compute costs. Having several idle resources that continue to connect to the cloud service entails unnecessary costs. Similarly, having instances that are not sized relative to workload requirements leads to cost inefficiency. These unnecessary costs can be particularly onerous when left unmanaged.

Data Transfer Costs

Data transfer costs refer to the charges related to the movement of data in the cloud environment. They apply to data movement in and out of the cloud. 

Data transfer costs are influenced by the volume of data being moved, direction, distance, and the pricing models imposed by a given cloud provider. Organizations need to optimize their data storage, use data compression, and design efficient data transfer protocols to minimize data transfer costs.

However, some data transfer costs can be avoided altogether by choosing cloud providers that do not charge for ingress and egress transfers. Ingress refers to the data uploaded to the cloud from an external source, while egress involves the downloading of data from the cloud to an external destination. 

Many cloud providers charge for data movements involving external origins and destinations, particularly when it comes to egress traffic. Also, additional costs may be incurred for regional data transfers or the movement of data across distant geographic locations.

Data Retention Costs

Generally, storing more data equates to higher data storage costs. Likewise, storing data longer entails higher storage costs. As such, enterprises need to optimize their data storage, especially if they are maintaining large datasets. It is important to ensure that they are only keeping the data that they actually need.

It is also worth noting that unnecessary data storage can adversely impact the performance of applications and services. This translates to unwanted user experiences that will affect an organization’s bottom line in the long run. Additionally, it is an added burden to cloud data security processes.

To achieve data retention cost efficiency, it is vital to carefully evaluate data retention needs to ensure that storage allocation matches the needs, avoiding unnecessary storage expenses. It helps to implement data classification to make it easier to identify data that may already be removed. It’s also worth noting that the benefits of systematic data lifecycle management extend well beyond retention costs.

Excessive Network Traffic

Some cloud providers may demand additional costs for excessive network traffic. This excess or unexpected surge in usage can happen among organizations that run high-bandwidth applications and those with inefficient network designs. 

Excessive network traffic can mean higher cloud costs. Also, it can result in lost sales or customer dissatisfaction because of network congestion and the degraded performance of apps and services. 

It is a must to optimize and regularly monitor apps to address unnecessary traffic. Apps with bugs or configuration issues can generate unnecessary network activity that contributes to excessive network traffic that leads to greater costs. Also, they can be targeted by cyber-attacks that can turn them into bots used in Distributed Denial-of-Service attacks.

Migration Costs

Migration costs refer to the expenses associated with the movement of data, applications, or infrastructure. They can be incurred during the transfer from an existing environment to the cloud or from one cloud to another. Migration is not as simple as it sounds. The costs can vary depending on the amount of data to be migrated and the complexity of the applications or infrastructure. These expenses can also be affected by the migration strategy such as the phased approach or big bang migration. 

To reduce migration costs, it is important to evaluate requirements closely and come up with a detailed migration plan. Data transfers should be optimized, and the apps and infrastructure being moved should be tested and validated. Sometimes, enterprises need to hire consultants to assist them in the process. It requires great attention to detail, as mistakes can create serious consequences such as data loss, corruption, or the exposure of data and other resources to cyber threats.

Organizations that are locked in to their vendors are likely to experience difficulties extracting and transferring data saved in a vendor’s proprietary format. Applications require re-architecting or re-platforming, which can be expensive and time-consuming. When it comes to infrastructure migration, having components that are tightly integrated with a specific vendor makes the process complicated. There are often compatibility issues, differences in APIs, and the possibility of data losses and corruption.

Smooth cloud migration is an important aspect of adoption. It is important to ascertain that there will be minimal friction if ever an organization has to migrate to a new cloud. That’s why many organizations prefer open-source technologies, using a hybrid cloud approach, and ensuring data portability. Organizations should avoid becoming too dependent on a single cloud provider.

In Summary

It is important to look beyond the tiered costs indicated by cloud providers. There are other expenses that many teams fail to take into account as their stacks and infrastructures begin to sprawl. It is important to get acquainted with the compute costs attributed to idle resources, the costs of data transfer and retention, excessive and unexpected network traffic costs, as well as the costs of migrating data, apps, and environments.