Operations | Monitoring | ITSM | DevOps | Cloud

FinOps, or the practice of managing a company’s cloud computing costs, and DevOps, the process of efficiently building applications in the cloud, should ideally go hand-in-hand. Engineers with a streamlined development process and a cost-conscious mindset can produce functional products with great margins and a high potential for scalability. However, incorporating FinOps into the DevOps lifecycle, and vice versa, isn’t always easy.

There are almost as many reasons for learning FinOps practices as there are resources available to learn from. Maybe you operate a SaaS company, for example, or you're looking for a job in FinOps. The FinOps field grows in importance every time cloud services and their associated costs become more complex — which can feel like every single day. Regardless of your situation, you’ll need high-quality FinOps resources that offer up-to-date materials and in-depth information.

As technology improves and customer demands change, many companies must provide fast, engaging, and secure services. Developers rely on platforms that support sub-millisecond response times to power these capabilities in their applications. Amazon ElastiCache and Redis are two of the most popular platforms for building fast, highly available, and scalable data stores.

Microsoft Azure was a relative latecomer to the public cloud market: AWS preempted everyone in 2006, and Google GCP came next, in 2008. By the time Azure launched in 2010, the public cloud market had already grown to more than $24 billion. Despite being third to the party, Azure had a key advantage: The Microsoft Office Suite was (and is) a go-to choice for corporate collaboration.

MongoDB has evolved into the database solution of choice for developers looking to build efficient, scalable applications in the cloud. But, as when using any cloud-based infrastructure, using MongoDB introduces an additional layer of complexity to customers’ IT spend. This week, we announced support for MongoDB on the CloudZero Platform.

In the early days of SaaS companies, most engineering and cloud operations teams weren’t tasked with monitoring or optimizing cloud costs. In fact, it would have been unlikely for these teams to care about cloud cost optimization at all, let alone take measures to fix issues and look for opportunities. Today, SaaS companies that want to secure a competitive foothold and ensure long-term success have to care about cloud costs.

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.