Access to critical business data, such as cloud cost data, is both incredibly important for finance, engineering, and DevOps teams, but also a privilege that should be managed carefully. This month, our engineering teams put a major focus on developing industry-leading capabilities related to access control, while also making it easier for people who require certain kinds of data to get it where it needs to be.

Many often wonder, “Is there a difference between observability and monitoring?” The thing is as IT environments have become more complex, monitoring alone has become increasingly less effective. That’s because while monitoring is crucial, it isn’t particularly suited to tracking unforeseen or unexpected turns of events. That’s what observability is meant for. This guide will clarify what observability and monitoring are – and how they differ.

If you’ve recently migrated your data from one major cloud provider to another, you may have already noticed one of our top stories from last month. If not, we’ve got good news, so keep reading! And there’s even better news if you’re the type to get excited over the chance to learn more about FinOps and hone your craft.

Research firm, IDC, published a study in early February 2024 predicting that Google Cloud Platform (GCP) customers break even after just 10 months. Moreover, the study, The Business Value of Google Cloud IaaS, reported that after migrating to GCP, the participants were on track to achieve a 318% ROI in five years. Here’s the thing. Achieving these milestones requires a robust GCP cost monitoring and optimization plan.

The first installment of our FinOps Automation Tips and Best Practices series focused on what FinOps is and why automating it can be a game-changer for your business. Now we’re back for part two, which will guide you on how to choose your optimal outcome and select the best automation options to suit your needs. Enjoy the full video for an in-depth explanation, or see the brief summary below if you’re just here for the highlights.

Whether you are a developer, an IT professional, or a tech leader in your organization, AWS Fargate promises to make provisioning, configuring, and managing your containers’ servers easier. AWS Fargate is like that cool gadget you didn’t know you needed – it’s nifty, powerful, and a bit mysterious. In this post, we’re unraveling the mystery, including what Fargate is, its key features, and how it stacks up in terms of pricing and performance for serverless computing.

Over the past decade, the cloud computing landscape has transformed remarkably, evolving from a nascent technology into a fundamental component of modern digital infrastructure. As the technology has evolved, so too has the need to develop complex cost optimization strategies. A decade ago, businesses grappled with the complexities of brand-new cloud services, often facing challenges in managing costs due to opaque pricing models and a limited understanding of cloud economics.

While many of us have already heard of Kubernetes, or may even be leveraging it within our technology stacks, it’s still important to remember that the platform is undergoing massive adoption and evolvement. Due to its relative infancy, Kubernetes is ripe to allow for integrating new technologies, like Artificial Intelligence (AI) and Machine Learning (ML). As an open-source platform, Kubernetes orchestrates containerized applications, ensuring they run efficiently and resiliently.

We get it. FinOps can be challenging to understand, implement, and optimize, whether you’ve done it before or are just getting started. Everybody needs help from time to time. If this describes you right now, then check out the following FinOps services companies to get started. But first, a quick background.

If you’ve spent any time poking around our blog, you’ve noticed one thing: At CloudZero, we are passionate about FinOps. More than that, we’re passionate about bringing the most useful and up-to-date information on FinOps to our customers to help them better navigate their journeys toward cloud cost optimization.