Operations | Monitoring | ITSM | DevOps | Cloud

The integration of Amazon Kiro and Harness’s MCP server enables developers to manage, troubleshoot, and optimize CI/CD pipelines directly from their IDE using natural language, dramatically reducing manual effort and accelerating software delivery from code generation to production.

A SaaS team once spotted their first breach not in a SIEM dashboard, but in their AWS bill. Their compute costs spiked by 400% overnight. Turns out, an attacker had spun up dozens of high-powered instances for crypto mining. Logs eventually confirmed the intrusion, but the cost anomaly was the first signal that something was wrong. This incident isn’t unusual. Cloud costs often reflect consumption, but they can also reflect compromise.

<span data-mce-type="bookmark" style="display: inline-block; width: 0px; overflow: hidden; line-height: 0;" class="mce_SELRES_start"></span> Andrew Hillier sits down with Dan Ciruli, who leads the cloud native product management team at Nutanix.

Cloud costs are no longer just an engineering problem or a finance problem. It’s now an everyone problem. That was the central message from the FinOps Training At Scale webinar that took place on Sept. 25, 2025, where CloudZero’s Larry Advey (a.k.a. “Fred FinOps”) and Director of Tech Enablement Umesh Rao walked through the realities of building FinOps practices that work in the real world.

The world of cloud costs is always evolving, and AI spend is quickly becoming one of the most unpredictable and confusing cost drivers. As more organizations integrate generative AI into their products, FinOps teams are struggling to account for — and control — these new, often mind-boggling cost streams. In fact, 44% of engineering professionals say improving AI explainability is a top priority in AI budgeting, according to CloudZero’s State Of AI Costs In 2025 report.

In this guide, you will build and deploy a serverless data processing workflow using AWS Step Functions and AWS Lambda. This approach enables you to orchestrate discrete processing tasks in a scalable and cost-efficient way, leveraging the event-driven architecture that AWS offers. You will begin by creating individual Lambda functions that handle specific tasks in your data pipeline.