It’s safe to say that cost per tenant (also known as cost per customer) on AWS has been a challenging metric to obtain. Until now, your best bet has usually been to either make a best guess or build some sort of homegrown system. As of November 4, 2020, when you google “cost per tenant,” you get a few things at the top of the page. The first is a couple of blogs by AWS, where they describe an extraordinarily complex system, which you can build yourself.

Do you know how much it costs to operate your software per customer, at each pricing tier? The past six months have been highly unusual to say the least. For some companies, the disruption and shift to work from home meant 100x in usage almost overnight; for others usage completely collapsed in the same time period. These sharp swings in utilization have been disruptive to cloud unit economics. Both scenarios are risky and require extreme elasticity from the technical infrastructure.

Cloud is a driving force that is reshaping organizations to adapt their people and processes in embracing this game-changing technology. Recently, Mike Fonseca of HashiCorp published a Guide to Cloud Cost Optimization with HashiCorp Terraform, in which he details how Densify can seamlessly integrate with Terraform in to help ensure your enterprise infrastructure is always cost optimized.

Amazon Web Services (AWS) is a comprehensive cloud computing platform, providing an array of services to manage a business’s data infrastructure to help it grow and expand. With the wide range of services provided, it has multiple options to provide you with an elastic approach to optimize your costs. However, many users struggle with controlling their expenditure due to a variety of factors. Getting a complete understanding of how to reduce your AWS operational costs may be a daunting task.

If you’re a SaaS business — especially B2B — you know that your profitability can vary significantly from customer to customer. We all have a sense of our “expensive customers,” who use the product heavily and push things to the limit. That also means there are more profitable customers. Who are they? And how do they use the product?

At CloudZero, we talk to leadership teams at SaaS and companies every day. When it comes to individual customer profitability, the vast majority of them fall into two camps: they’re either taking their best guess — or they have no idea. Typically only the largest companies - those with the resources to dedicate a 5-10 person engineering team to calculating cost - have this level of insight. And you can be sure they yield that knowledge to their competitive advantage!

Amazon Web Services (AWS) is pretty much ubiquitous these days, with everyone from tiny startups to large enterprises using the cloud service to run their apps, websites, and processes. For small businesses, being able to predict your budgets is paramount. Unfortunately, AWS costs can be very difficult to forecast. In this blog, we’ll go over the pros and cons of the tools available to help you estimate your AWS costs.

Every decision that an engineer makes in the cloud impacts cost. Yet we know that engineers aren’t cost experts, and many worry that asking them to care about cloud cost will slow them down and distract them from delivering customer value. Top cloud-native companies dedicate entire teams of engineers to build custom tools to measure unit cost and deliver cloud cost to engineering teams. But I’m guessing you don’t have eight engineers you can spare to build internal cost tools?

If you are looking to account for your container costs and understand how your AWS Kubernetes or EKS cluster spend maps onto your workloads, this guide was made for you! In this post we will walk through the steps to get up and running with CloudZero and Amazon Container Insights fast. CloudZero has integrated with Amazon CloudWatch Container Insights for its strength as a secure and automated solution for sharing container metrics within AWS.

One of the mistakes organizations make related to Kubernetes costs is addressing them primarily after-the-fact, once the application is running successfully. There are certainly changes that can be made to improve efficiency once the application is running, but cost-control measures are best considered at the beginning, not middle or end, of the application lifecycle.