Due to the complexity of managing cloud spend, there are a number of software solutions that can help optimize costs, monitor performance, and identify anomalies. However, these solutions are only as good as the data available to them, which is why it’s important to track cloud spend accurately.
In January 2018, Gartner reported that 80 percent of businesses will overshoot their cloud budgets through 2020 due to a lack of cost optimization. To avoid this scenario, Gartner recommended using a Cloud Service Expense Management (CSEM) solution.
Just as businesses and their requirements are not identical, neither are CSEM solutions. Consequently, Gartner suggests evaluating solutions against eleven core CSEM functions in the context of the business’s cloud operations. The eleven core CSEM functions are divided into three categories representing set up, monitoring, and optimization capabilities:
The accuracy of all five functions in the Monitoring category and two functions in the Optimization category are dependent on accurate cloud spend tracking. If assets are not tagged, or they’re misallocated to the wrong business unit, or a Shadow IT environment exists, then budgets, reports, anomalies, forecasts, and notifications produced by the CSEM solution are going to be wrong.
Similarly, cost optimization measures and Reserved Instance purchases are going to be recommended by CSEM solutions with only partial knowledge. So, how do you ensure you are tracking your cloud spend accurately in order for CSEMs to produce accurate data?
The golden rule of tracking cloud spend is “you can’t track what you can’t see”. This is why it’s necessary to have a single-pane view of all your assets. This is especially true if you operate in a multicloud environment or hybrid cloud environment where data comes from multiple sources, which then has to be correlated and analyzed as in the context of a single environment.
If a Shadow IT environment exists in your business, this not only has implications for tracking cloud spend, but also for efficiency and security. Therefore consider what caused the need for Shadow IT in the first place, and then—rather than try to enforce central IT as the sole gatekeeper of technology—develop relationships with users to create a unified IT roadmap going forward.
Tagging assets enables cloud spend to be allocated to business units in a manner that’s transparent, understandable, accurate, and controllable. However, in order to track cloud spend accurately, tags should be uniform. If one business unit is using one tagging policy, and another using a second tagging policy, it can be time-consuming to allocate cloud spend accurately—if at all.
A global tagging strategy takes on even greater importance in multicloud environments because of the different tagging parameters allowed by different cloud service providers. For example, AWS tags are case sensitive, whereas Azure tags aren’t, and Google allows only lowercase tags. Each provider also has different limits for how many tags can be assigned to each asset and the tag length.
A best practice recommended by AWS is to use an automation solution to apply a global tagging strategy throughout the business. The automation solution should be capable of identifying untagged assets and correcting misconfigured tag names to comply with the tagging strategy, so the cost of each asset is accurately tracked, recorded, and allocated. An automated tagging solution will also have benefits in terms of regulating access controls, and enforcing security and compliance policies.
Without total visibility, a global tagging strategy, and the means to execute it, data fed into CSEMs will likely be incomplete and possibly result in a misrepresentation of your business’s cloud spend. This can have consequences for your business’s forecasting and budgeting, and potentially derail the business’s cloud journey and its objectives of operating in the cloud.