Operations | Monitoring | ITSM | DevOps | Cloud

AWS Direct Connect pricing looks simple until you’re staring at an unexpected bill. Understanding how AWS Direct Connect costs work, such as port hours, data transfer, and the charges that don’t appear on the AWS pricing page, is the first step to managing them. The model has no setup charges and no minimums, but it has enough moving parts that costs can compound quickly if you’re not watching closely.

This guide walks through practical ways to embed cost awareness directly into CI/CD workflows so development teams can make cost-informed decisions before deployment. You’ll learn how to implement automated cost feedback loops, introduce pipeline budget guardrails, and use Harness Cloud Cost Management to align DevOps velocity with FinOps accountability.

To reduce cloud costs, organizations need to address three root causes: over-provisioned resources, shared infrastructure without clear owners, and cloud bills that can’t be explained at the feature or customer level. The most effective programs combine rightsizing, commitment-based discounts, idle resource elimination, and unit economics — and deliver 20–30% reductions in monthly spend without impacting performance. CloudZero customers average 22% savings in year one.

Open source software is an essential component of business operations. According to Harvard Business School, 96% of commercial software includes open source code. If companies were to build these tools from scratch, it would cost an estimated $8.8 trillion — roughly 3.5 times what companies currently spend on software. That’s not great for the bottom line. Many open source solutions are also available as standalone tools. Consider Kubernetes.

Kubernetes (K8s) adoption has exploded over the past few years. But it hasn’t been easy to monitor, manage, and optimize K8s costs. To provide greater cost visibility into Kubernetes clusters and environments, Kubecost launched in 2019 and was acquired by IBM in 2024, while OpenCost debuted in 2022. OpenCost has several founding contributors. But Kubecost developed the cost allocation engine that the OpenCost implementation uses.

If you work in FinOps, you know the feeling. You open your recommendations queue on a Monday morning. There are 47 items. You worked through 12 of them last week. You’re back up to 47 again. All represent real money leaving the building, but not all are “bad money” – of those 47, a significant share will be “this is ok, expected, we got value”. That’s what really kills FinOps enthusiasm (and is why the engineer is skeptical towards the FinOps person).

At SaaS Metrics Palooza 2025, CloudZero CEO Phil Pergola delivered a keynote on the software industry’s most pressing question: can SaaS survive the AI revolution, or will AI rewrite the SaaS playbook outright? Phil’s answer wasn’t doom and gloom, but he didn’t sugarcoat the challenges. “Churn rates are up,” he told moderator Ray Rike of Benchmarkit on Oct. 9, 2025. “The payback from a customer acquisition cost perspective is taking longer.

I’ve been an engineering leader for over a decade, and I’ve spent most of those years in private Slack groups with other engineering leaders, comparing strategies and kvetching about Kubernetes. Of the hundreds of threads I’ve taken part in, the one that got the most engagement the fastest was a recent one around AI adoption. “Where are you on this continuum?”, it read. “A. You don’t really care how people use AI; B. You push people to use AI; or C.

AI cost management is the practice of tracking, allocating, and optimizing the cloud infrastructure costs tied to building, running, and scaling AI workloads. It differs from traditional cloud cost optimization because AI infrastructure behaves differently at every layer of the stack. The biggest problem isn’t overspending. It’s that most organizations can’t see where their AI spending is going.