Operations | Monitoring | ITSM | DevOps | Cloud

Amazon’s Elastic Compute Cloud (EC2) service provides a variety of virtual machines (instances) for compute workloads. Among those, Amazon EC2 M5 instances are among the most versatile. In addition, there are different types of M5 instances available. Each of these has its own best use case. In this guide, we share an in-depth look at M5 instance types, sizes, and when to use them.

“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.

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.

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.

Amid the first bear market in over a decade, the world’s largest companies are facing intense pressure to cut back. Layoffs have made headlines, but cutting workforce is not a silver-bullet solution to surviving in a down market. True, companies tend to spend the most on personnel, but using layoffs as a first line of recession defense has myriad negative consequences for survivors, including reduced job satisfaction, reduced organizational commitment, and declining job performance.

In Part I of this two-part series, I talked about the key benefits of top-down cost allocation: It starts at the provider level, incorporates every penny of your cloud spend, and lets you break it down at as granular a level as is useful for your business.

High-quality cloud cost allocation has become an existential issue for businesses. In order to get as much out of their (mounting) cloud investments as possible, business leaders need to know how much they’re spending in the cloud, what/who they’re spending it on, and whether there’s a good reason for it. In its ideal form, cost allocation answers all these questions.

Just as there are a handful of stages to describe the financial journey from startup to established company — pre-seed and seed funding, followed by series A, B, and C funding — there are also stages to the process of achieving a healthy understanding of your costs.