Discover the power of cloud cost intelligence
Give your team a better cost platform
Give engineering a cloud cost coach
Learn more about CloudZero and who we are
Learn more about CloudZero's pricing
Take a customized tour of CloudZero
Understand your cloud unit economics and measure cost per customer on AWS
Discover and monitor your real Kubernetes and container costs
Measure and monitor the unit metrics that matter most to your business
Allocate cost and gain cost visibility even if your tagging isn’t perfect
Identify and measure your software COGS
Decentralize cost decisions to your engineering teams
Automatically identify wasted spend, then proactively build cost-effective infrastructure
Monitor your AWS cost and track progress in real-time as you move to the cloud
Discover the best cloud cost intelligence resources
Browse helpful webinars, ebooks, and other useful resourcesBlog
Discover the best cloud cost intelligence contentCase Studies
Learn how we’ve helped happy customers like SeatGeek, Drift, Remitly, and moreEvents
Check out our best upcoming and past eventsFree Cloud Cost Assessment
Gauge the health and maturity level of your cost management and optimization efforts
Discover how SeatGeek decoded its AWS bill and measures cost per customerRead customer story
Learn how Skyscanner decentralized cloud cost to their engineering teamsRead customer story
Learn how Malwarebytes measures cloud cost per productRead customer story
Learn how Remitly built an engineering culture of cost autonomyRead customer story
Discover how Ninjacat uses cloud cost intelligence to inform business decisionsRead customer story
Learn Smartbear optimized engineering use and inform go-to-market strategiesRead customer story
Cloud cost optimization is often reactive, where finance asks DevOps why the AWS bill is so high. We show you another way.
If you’re a cloud architect or engineering lead, chances are you’ve had a defensive conversation with finance about the AWS bill. Maybe it looked a little something like this:
Unfortunately, this scenario is all too familiar, yet understandable from Finance Frank’s point of view. He’s just trying to do his job, but has zero context into which engineering activities are costing the organization so much (or why these costs are variable on a month-to-month basis). That makes the conversation between App Owner Amy and Frank adversarial, when it doesn’t have to be. Frank should be thinking about profit margins and capital allocation, rather than learning about reserved instance (RI) distribution, or the nuances of AWS Fargate pricing. The responsibility of cloud cost optimization should not fall on finance alone. Here’s why:
The public cloud model has made buyers out of engineers, whether or not they’ve realized it. Traditional tactics for IT budgeting and cost management are antithetical to building on AWS. Think about it: With AWS, the ability to scale is infinite, so the old server-bound parameters on engineers have been removed. It’s like going to a restaurant and choosing a meal from a menu with no prices. Engineers will pick the filet mignon of AWS services every time (and are sometimes being charged by the bite). They historically haven’t had the data to make a better, cost-informed choice.
Here’s an all too common scenario: Finance consults an outdated cloud cost management solution or monthly invoice, and asks DevOps leadership to login to AWS to investigate the root cause of a cost spike. Often DevOps leaders don’t have direct answers to finance’s questions, so have to ask the engineering product owner what’s happening within their application. Cloud cost anomalies could be a result of any number of engineering actions or simple mistakes. The process of tracing these actions today is inefficient at best, and extraordinarily wasteful at worst.
Rather than a reactive approach, the script should be completely flipped. DevOps should have complete, real-time visibility into the cost of engineering and infrastructure decisions. Cost should be a first-class operational metric and major part of the day-to-day engineering workflow. Instead of playing detective, DevOps leadership can proactively report costs to finance, justify the cost of actions, and project the long-term cost of applications and projects in the pipeline. That way, instead of defensively approaching DevOps teams about spend, finance and executives can focus on setting the right incentives to innovate, while reducing waste.
Too much information (TMI) is a very real cloud cost optimization problem. Cloud bills and billing tools are loaded with data that isn’t necessarily relevant to the person trying to interpret what actually went down in any given month. In some cases, a cloud manager is attempting to control costs by adopting AWS budgeting features, but in reality is taking educated guesses around unpredictable expenses like bandwidth, support, RIs, and more. Right now, there’s TMI for anyone to make an informed decision, and not enough targeted information for specific levels of decision-makers.
Instead, different decision-makers should only be able to see cost data that’s relevant to their jobs. For example:
Few people understand that access to real-time cost data can actually increase the pace of development. There’s a common misperception among developers that building with cost in mind will slow them down. Instead, retroactively chasing down issues when finance raises the alarm on cloud costs is one of the single biggest (yet rarely discussed) operational inefficiencies today.
Development organizations that embrace cost as an operational metric can innovate faster and build more efficient systems. By siphoning cost data into tools DevOps teams already use, like Slack and OpsGenie, developers can observe their applications and fix potentially costly mistakes in real time. Rather than building within nearly unlimited parameters of cloud scalability, developers can learn to use just the capacity they need (and curb unnecessary waste). In time, efficient systems can create found money for the engineering budget that can be reinvested elsewhere (like hiring engineers for serverless transformations).
Giving the right data, to the right people, at the right time can help DevOps teams avoid defensive conversations with finance, and give finance the information they need to do their jobs. Instead of the buck stopping with finance (pun intended), the responsibility for cloud cost optimization should also fall into the hands of cloud architects and DevOps leaders. All they need are the right tools. To learn more about CloudZero’s cloud cost optimization capabilities, get started here.
CloudZero is the only solution that enables you to allocate 100% of your spend in hours — so you can align everyone around cost dimensions that matter to your business.