Compared to on-premises infrastructure, public cloud computing often reduces enterprise costs. But for many organizations, it's still difficult to make objective cost estimates for public cloud deployments.
Major public cloud providers, including Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform, have tools that allow users to predict monthly cloud costs. However, the use of these cloud cost estimators doesn't guarantee accurate results; they are only as precise as the information that users provide.
Costs of forgotten services
The biggest cause of inaccurate public cloud cost estimates is forgotten resources and services. This occurs when enterprises don't fully consider their workload's deployment requirements. It's simple to estimate the monthly cost of a particular AWS instance or Azure storage bucket, but workload needs generally extend far beyond a single, static instance.
Various resources and services -- such as compute, storage and networks -- form cloud infrastructure. These services show up on your cloud bill as regular monthly costs, such as per-hour or per-month charges for Amazon Elastic Compute Cloud instances and Amazon Simple Storage Service buckets. But organizations need to consider other costs, as well, such as those associated with data migration, API calls and more.
In addition, resource and service costs vary by region, and data duplication efforts across those regions can drive up monthly total costs. Organizations must include these additional storage, management and other costs in the cloud cost estimator tool. If you're not certain about details, like usage, run the estimator several times and use several usage scenarios to bracket the estimate.
Costs versus growth considerations
Another cause of public cloud cost estimator inaccuracies is workload growth over time. Cloud supports dynamic, highly scalable environments, but the cost benefits for long-term, steady-state usage are questionable. In some cases, it's more cost-effective over the long-term to host your workload in a local data center.
When a business' application is popular, its usage rises. The public cloud can then provide additional resources -- but those new resources increase overall costs. Many public cloud cost estimates don't consider the impact of these additional resources or services during times of growth. This means even the most cost-effective application in the public cloud has the potential to become more costly than it would in a local data center.
Remember to make estimates for future cloud usage levels. Develop comparative scenarios to calculate cloud costs against anticipated growth predictions. Also, consider how alternative usage models, such as reserved instances, could reduce your cloud bill.
Costs versus seasonal or periodic considerations
Organizations also overlook the cost of short-term or variable growth when estimating public cloud costs. Workloads that render periodic or regular services, such as accounting or scientific applications, experience sudden usage spikes that increase a cloud bill.
These short-term usage spikes are a challenge to address. Part of the issue lies in a workload's architecture in the public cloud. Operations staff responsible for the workload need to properly configure downward scalability. When a spike passes, the workload should release any excess cloud resources to conserve costs.
The other challenge is to predict when usage spikes will occur, how many additional resources they'll need and how long the additional demand will last. Perform conscientious monitoring and reporting so cloud administrators can spot trends in demand and corresponding costs. Alternative usage models, such as AWS spot instances, could also reduce the cost of temporary usage spikes.
Costs of outages or failures
Outages happen, and they create disruptions that can lead to revenue loss for cloud users. These failures can also negatively affect a business' reputation -- even for weeks or months after resolving the problem.
Although there is no line item in a public cloud cost estimator for outages, weigh the cost of potential disruption against your workload's operating costs. Some organizations find the potential cost of outages too great for a given workload, so will host it in a local data center.
In other cases, the potential cost of an outage drives architectural changes that enhance a workload's resiliency. For example, some organizations might determine that it's more cost-effective to deploy a mission-critical workload across two or more public cloud regions -- despite the additional resource costs -- than to risk a potential outage.
Costs of multicloud strategies
One of the best ways to ensure redundancy and cost-savings is to spread workload components across multiple public clouds. Unfortunately, this model isn't a reality yet for most organizations, and public cloud cost estimators don't factor in multicloud deployments.
Public cloud providers continue to compete for customers, and many of their offerings remain incompatible. Vendor lock-in is still a viable cloud business strategy; consider the lock-in risks of hybrid services, such as Azure Stack. This means that public cloud providers are reluctant to show their cost estimates alongside estimates from competing providers.
Organizations can still compare cost estimates between different providers , but this requires separate use of each provider's calculator. It's also difficult to achieve a complete comparison because of the differences between providers' pricing and services. But if you want reduce your cloud bill, these sorts of comparisons can help in the long term.
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