The volume of applications deployed in the cloud continues to increase steadily. More organizations are looking to contain costs but are finding they lack the skills and expertise needed. A survey of over 400 cloud and data decision-makers conducted by Forrester Consulting on behalf of Boomi, finds nearly three quarters (72 percent) exceeded their cloud budgets last fiscal year, with 22 percent now making reducing cloud spending a priority.
Overall, respondents admit they can’t account for 40 percent of spending on cloud services. Primary reasons for being over budget include excessive storage (52 percent), the lack of integration (44 percent), overconsumption of network bandwidth (42 percent), and insufficient cloud architecture (40 percent).
Only 10 percent said their existing cloud cost management and optimization tool allows them to fully maximize cloud savings. This includes 57 percent noting they cannot consider cost when defining their cloud architectures. That lack of visibility is also the number one challenge organizations face when adopting the best financial operation practices to control cloud costs (46 percent).
Data management challenges top the list
The survey also identifies data management as the number one challenge when it comes to controlling costs.
Despite these issues, well over a third (37 percent) plan to increase the number of workloads deployed in the cloud by more than 20 percent over the next two years. Just over a quarter (27 percent) are expecting costs to increase by more than 20 percent, the survey finds.
Managed service providers (MSPs) typically have a lot more experience when it comes to optimizing cloud costs. Unfortunately, the bulk of workloads deployed in the cloud are managed by internal IT teams. However, as more organizations become sensitive to costs, there should be additional consulting opportunities for MSPs to help organizations take better advantage of, for example, discounts offered by cloud service providers. Those engagements could then lead to more opportunities to manage cloud workloads in a way that ensures costs never exceed a set of pre-defined targets.
The future of cloud optimization includes AI
There will come a day when artificial intelligence (AI) is more widely applied to cloud optimization. The challenge is that an AI model needs access to data to surface cloud optimization opportunities. Correlating this will become even more challenging in multicloud computing environments.
Even if the AI model has access to data, it surfaces recommendations that are probabilistic rather than deterministic. This means someone with cloud computing expertise still needs to verify that any change to the cloud computing environment will provide the anticipated cost reduction.
Most IT leaders are going to be a little reticent to concede they need help controlling cloud costs. MSPs may want to initiate this conversation with finance leaders who are trying to better understand how much of their spending on cloud services is being wasted. They may not know precisely why spending on cloud services keeps growing. However, they are keenly aware of unexpected costs incurred. For example: the monthly bill for cloud service increases because someone in the organization invoked a service without understanding the cost implications.
One way or another, organizations are eventually going to reduce those costs. They need to decide whether to resolve the issue themselves or rely on an MSP that has the expertise.
Photo: sommart sombutwanitkul / Shutterstock
