Operations | Monitoring | ITSM | DevOps | Cloud

In the traditional finance world, budget variance was a static comparison between actual and budgeted spend. But in the cloud era, where costs scale with usage, experimentation, and engineering decisions, variance tells a much richer story. Done right, budget variance helps you distinguish between healthy growth and margin erosion. It can signal strong feature adoption, rising customer demand, or successful launches. It can also reveal waste, inefficiencies, and weak cost controls.

Why does AWS API Gateway spend rise even when backend infrastructure stays the same? For most teams, the answer isn’t compute. API Gateway pricing is driven by how APIs are used — request volume, retry behavior, traffic patterns, and growth over time — not by provisioned resources. Because AWS reports these costs as aggregated usage totals, it’s often unclear which APIs, environments, or behaviors are responsible for increases.

Think about how airlines assign seats on a plane. Some have extra legroom. Some sit near exits. Some are cheaper, while others cost a premium. Certain passengers also have strict requirements, like families traveling together or travelers who paid for a specific class. Now imagine boarding everyone randomly. A passenger who paid for extra legroom (perhaps for health reasons) ends up squeezed into a middle seat. Families scatter across the cabin. Premium seats sit half empty while the back rows overflow.

Happy New Year, everyone! 2025 was another exciting year filled with impressive AI advancements. As you might expect, some significant cost changes accompanied these new developments. Because reflecting on the past is one of the best ways to prepare for an even stronger future, here’s your end-of-2025 headline round-up, complete with what you can expect going forward into 2026: Get caught up on the details below.

Modern SaaS companies aren’t reporting weaker margins because they forgot to rightsize instances or buy reservations. It’s more because cloud spend now moves at the speed of AI experiments, overnight shifts in customer usage, and automated systems that scale in seconds. That’s why the next generation of cloud cost optimization strategies looks fundamentally different from what worked even two years ago.

“Cut spending!” “Slash costs!” “Stick to the budget!” Poke your head into almost any finance meeting in a SaaS company and you’re likely to hear one or more of the above phrases played on repeat. At first glance it makes sense: Costs are increasing, so we should reduce them. I’d like to challenge that narrative. Mature companies don’t care about cloud costs.

If you are running containers on AWS, you need a secure place to store and share your images. Amazon ECR offers a managed registry that handles image storage, scanning, permissions, and versioning without extra configurations. In this guide, you’ll learn what Amazon ECR is, how it works, its features, real-world benefits, and pricing. We will also introduce you to a cost intelligence approach to keeping ECR costs under control.

Software engineers use engineering performance metrics to make informed decisions about their products, features, processes, and even their dev teams. In addition, measuring lets you know if you’re on track to meet your engineering goals. With so many tasks, data, and other information to monitor, how do you choose the right metrics to track? We’ll share that and more in this guide.

Choosing the right tool to manage your infrastructure can shape how fast your team moves and how reliable your systems become. Two names appear in almost every conversation: Ansible and Terraform. Both help you define, manage, and scale your environment. But they solve different problems and work in very different ways. One focuses on configuration. The other focuses on provisioning. Both are powerful. Both are widely used. And both can work together in the right stack.

Virtual machines often represent the largest line item in a cloud bill. And for Google Cloud users, the Google Compute Engine (GCE) accounts for a large share of overall spend. GCE offers rich flexibility: you can choose specific machine types, scale up or down instantly, and match compute to load. But understanding how the pricing works is critical before you can unlock full value. On the surface, GCE looks simple. You pay for vCPU, memory, storage, and network.