This is part four of seven in our Frugal Architect blog series. Read the rest of the series here. In case you weren’t as giddy as CloudZero was at re:Invent this past year, we wanted to recount the seven laws outlined by Werner Vogels, Amazon’s CTO, which he’s bundled into a framework called “The Frugal Architect” (check out the whole framework here). What is “The Frugal Architect”?

As per the latest forecast by Gartner, worldwide IT spending is projected to amount to $4.6 trillion in 2023, up by 5.1% from 2022. The demand for IT will be strong in 2023 as enterprises launch digital business initiatives to respond to global economic challenges. In a downward economy, conventional wisdom warrants reducing costs.

Amazon Web Services (AWS) offers the convenience of choosing specific virtual machine combinations to meet your compute needs. Unlike traditional data centers, you can also scale your cloud resources automatically to meet fluctuating workload needs. The best part is that you can rightsize your workload requirements to specific instance types (VM types) offered by AWS. By hand, this takes a lot of time and is prone to errors. This is where AWS Compute Optimizer comes into play.

Datadog is like a Swiss Army knife for observability. Whether it’s cloud, applications, or infrastructure, Datadog can serve all your monitoring needs under one roof. This is with a level of integration that’s akin to having a universal remote for all your digital operations, from on-premises to cloud environments. The thing is, with great power comes a notable concern – cost.

Kubernetes has emerged as a pivotal force in shaping modern cloud infrastructure. Originating as a brainchild of Google, Kubernetes has evolved into an open-source platform that has revolutionized how applications are deployed, scaled, and managed across a vast network of machines. Its ability to orchestrate containerized applications efficiently makes it an indispensable tool within cloud computing. However, with great power comes great responsibility, particularly in the realm of cost management.

As of 2023, 89% of companies are using a multi-cloud approach. The race to the cloud might feel truly like that – a race – but the finish line isn’t hybridization or even a full migration. Even after you’ve made it to the cloud, there’s still more work. Namely, determining cloud costs. Microservices, containers, Kubernetes made resource costs, associated costs and more are near-impossible to sort though.

Cloud cost management and FinOps best practices rely on getting as much meaningful data as possible into decision-makers’ hands. Without the ability to pull data from all your various cost sources, you cannot get 100% visibility into your cloud spend — let alone make decisions to optimize that spend.

In an era where cloud computing has become the backbone of global business operations, its impact on the environment cannot be overlooked. As organizations increasingly migrate to the cloud, data centers’ energy consumption and carbon footprint have surged, highlighting a critical need for sustainable practices. One often underappreciated lever for environmental stewardship within this digital infrastructure is effective cloud cost management.