For IT and EUC teams, reducing costs is easier said than done. You can’t just blindly reduce headcount, delay transformation projects, or extend hardware lifecycles in the hopes of appeasing your CFO’s demands for short-term cost reduction. The reality is, rushed cost-cutting will put your service desk under pressure. In turn, such self-inflicted inefficiencies will only result in performance degradations, additional tickets, and escalations.

With organizations across industries facing inflationary pressures and the threat of recession, CFOs are forced to impose cost-cutting measures to improve cost efficiency across teams to tide through these tough times. This has resulted in IT teams being faced with a dilemma. How to improve the cost-effectiveness of the team without impacting employee satisfaction and service desk productivity?

“Perfect tagging” is a little bit like perfectly tuning a piano. It takes an enormous amount of manual effort to get right, it’s never truly perfect, and the slightest change in the surrounding environment can throw it out of harmony. The closer an organization wants to get to perfect tagging, the more engineering resources they have to invest in it — frequently at the expense of more impactful, innovation- and product-oriented projects.

Yet, the same flexibility that makes EC2 so appealing can also make it complex, confusing, and unnecessarily costly. A good way to understand the compute service is to familiarize yourself with EC2 instance types, and what the best use cases are for each. This guide will cover that and more.

While cloud solutions can give you greater flexibility as you scale your infrastructure, limited visibility into resource utilization makes provisioning the right amount of compute resources challenging. To ensure that every workload is fully supported, many organizations may opt to over-provision, which leads to overspending. Or, in an attempt to maximize cost savings, organizations may under-provision, leaving workloads unsupported and risking serious performance impacts.

Conventional wisdom states that SaaS engineers don’t care about costs. They care about building an optimal product, regardless of the dollar signs associated with it. As a result, the finance team feels they must corral the engineers’ efforts and constrain them to work within an agreed budget. In fact, the FinOps Foundation’s annual survey consistently ranks “getting engineers to take action on cost optimization” as the number one challenge experienced by FinOps specialists.

Earlier, before the advent of cloud computing, businesses used to have their data centers. These data centers were expensive to set up and maintain. They required a lot of expertise to manage. As a result, only large enterprises could afford them. However, with cloud computing, even small and medium businesses can now take advantage of this emerging and forward-thinking technology. Data shows that businesses that use cloud technologies tend to grow faster, be more profitable, and generate more jobs.

As a cloud product manager, much of our jobs center around creating KPIs (or OKRs, if you prefer) such as sales revenue, freemium conversions, or customer stickiness, and encouraging development teams to hit product performance goals. But what happens after those goals have been met? Do we create new KPIs and push forward, or do we take a step back and evaluate whether each indicator actually translates to higher profit for the business?

A good chunk of your Amazon Web Services (AWS) public cloud spending goes to the Amazon Elastic Compute Cloud (Amazon EC2) service. Because it is the default compute service on AWS, Amazon EC2 is key to building, running, and scaling your AWS-based applications. That also means Amazon EC2 pricing has a tremendous impact on your AWS budget. Understanding how the EC2 billing model works will help you control and optimize your AWS spending.