Cutting your cloud spend? Consider sharing your bill data internally

As budgets tighten, leaders are feeling the pressure to temper spending, and tech teams are no exception. Many companies invested heavily in the cloud during the pandemic and are now looking at ways to optimize resources.

According to a recent report, as many as 81% of IT leaders have been directed by their C-suite to reduce or halt cloud spending, which represents 30% of IT budgets. It’s a critical moment for CIOs and other technical leaders to take stock of their cloud and IT budget and usage.

While it is not advisable to abandon cloud-first strategies in favor of on-prem or hybrid infrastructure, it is possible to reduce cloud spending significantly. Databricks recently cut our total cloud spend by 25%, and we’re tracking to reduce total SaaS IT spending by 30%. We accomplished this by democratizing the cloud spend data: by providing visibility into where and how the team was spending, we were able to bend the cost curve.

Here is the framework we used for successfully cutting cloud spend, what the team learned and how leaders can incorporate data democratization into their cloud spend strategies.

Step 1: Understand the bill

On cloud spend, the first step is to get a clear picture of what you’re paying for through cost allocation tagging. This is easier said than done — tagging one cloud vendor bill is a significant undertaking alone, so multicloud organizations will find this step can be twice or three times more complicated and time consuming. But the output is valuable: This approach — and the data you’re able to garner with it — offers three significant benefits.

First, it provides visibility into who the owner of each resource, which function it supports and how much the team is using and spending. Second, it enables you to view your spend in different ways, such as organizing the data by service type, cloud, database, network, or department, or viewing month-over-month trends, to understand patterns.

Third, investing time in cost allocation tagging makes it possible to build infrastructure to auto-tag future expenses and easily understand bills on an ongoing basis.

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Step 2: Leverage your new field of vision for discounts

Now that you have adequate and reliable visibility into your cloud bills, look into where you can cut and leverage vendors’ native tools to do so.

The goal here is to strike the balance between compute time horizons, high utilization and discount offers. This methodology hinges on economies of scale or ensuring that the team is truly getting the most out of their tool choices.

Next, identify the cheapest option that meets your needs. Whether it’s adjusting timing (scaling up during cheaper timeframes, like weekends) or geography (cloud providers often charge a premium for certain regions), there are several ways to go about this, but there may be hidden challenges based on your roadmap or workflow. For example, you may want to utilize more cost-effective regions for testing, but it’s essential that your product works in the region where you’re going to deploy it — so do this methodically.

Or, consider utilizing spot instances for computing (as opposed to relying solely on reserves), which can offer ephemeral savings if the team has the appropriate workload and infrastructure to utilize them. In some instances, an upgrade can be a surprising avenue for savings — for example, AWS Graviton 2 can provide up to 35% price performance by switching to these faster chips.

This approach should be applied to every aspect of IT — computing, storage, databases and networks — in order to enable the team to automatically manage spend according to the needs of the business.

Step 3: Maintain your spending cuts through a culture shift that democratizes data

A culture shift is critical if you want to effectively maintain the downward curve you’ve laid out for cutting your cloud or IT spend. Engineers should feel a sense of collective ownership of your bill but often don’t because they don’t have visibility into it.

At Databricks, we focused on democratizing our cloud spend data to address this. We developed auto-refreshing visibility dashboards for each of our 22 engineering teams and made all of the raw data available centrally too. The steady and accessible flow of information helps them utilize cloud infrastructure more efficiently and economically — for example, it’s easier to see what existing platforms or tools can meet teams’ new needs as they come up rather than continuously spinning up new environments.

Moreover, engineers can better understand how their work contributes to the cloud spend bill directly, and certain teams even incorporated a notification for budget spend directly into their workflows (similar to an alarm for an outage).

This isn’t just for technology companies, either. It’s common for IT and cloud spending to be almost as significant on companies’ balance sheets as wages, even in “nontechnical” industries like retail or construction. Companies should not have to compromise their digital transformation progress to weather the economic headwinds, and this sense of ownership can help engineers understand their role in this undertaking.

Ultimately, bending and maintaining the cloud cost curve cannot occur in a silo. It can’t be a task force or only a priority for the FinOps team, or else it’s tough to maintain as the team builds more solutions. It’s up to us as IT leaders to facilitate a culture shift and to bake efficiency projects like these into our product roadmaps, the same way we do for technical debt or products for customers.

With Gartner estimating that most organizations overspend on cloud costs by 70%, it’s possible to find spaces to cut. But don’t do it flippantly: Reducing cloud spend must be more about optimizing the budget for long-term ROI than cutting costs. While the tactical process looks different for each organization, putting data democratization at the core of the initiative is the best way to create an enduring and transparent budget framework and optimize costs.