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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Product Portfolio Management for New Paradigms - DevOps, AI, and Beyond - Job Task Analysis | Harness Blog

Taking a look back over the last ten years in enterprise technology, paradigm shifts are occurring more frequently. For example, the maturity of DevOps/Platform Engineering and Cloud Native infrastructure has occurred. The new frontier depending where you are in adoption is AI. As your adoption and maturity curve progress, operationalizing these paradigms become important.

AI Cost Management: How To Track, Allocate And Optimize AI Spend

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.

A Tour of Cortex

Get a guided tour of Cortex, the Engineering Operations Platform built to help teams improve operational maturity and reduce developer friction. This video covers the core features of Cortex: the Catalog, Scorecards, Initiatives, engineering metrics, and Workflows. Each one maps to the three things any great EngOps platform needs to do: provide clarity, drive improvement, and remove friction. Ready to see it in action? Visit our website: cortex.io Book a custom demo: cortex.io/demo.

Real-Time Visibility, Orchestrated Deployments, and More

The latest VirtualMetric DataStream release brings a significant step forward in platform observability and deployment flexibility. Version 1.9.0 gives security and infrastructure teams direct visibility into what’s happening across their pipelines in real time while expanding support for cloud-native environments and broadening connectivity options. Here’s what’s new.

Load Testing: An Essential Guide for 2026 | Harness Blog

This comprehensive guide covers the fundamentals of load testing, key differences from stress and performance testing, step-by-step execution methods, popular tools, and best practices to help teams build resilient systems with confidence. In today's always-on digital economy, a single slow page or unexpected crash during peak traffic can cost businesses thousands or even millions of dollars in lost revenue, damaged reputation, and frustrated customers.

Lowering PUE: Building Envelope Efficiency in Edge Computing Units

Edge computing is changing how we handle data across the globe. Smaller units closer to the user need smart cooling to stay efficient. Compact systems handle big tasks in small spaces without needing giant server rooms. Power Usage Effectiveness (PUE) tracks how much energy goes to IT versus support. Improving the outer shell of units helps keep costs low. High efficiency is a goal for every tech site, and it saves money.

The Observability Gap: Why Monitoring Data Should Drive Tests

Most teams already know a lot about production. They have dashboards. They have traces. They have alerts. They have enough telemetry to explain what happened after an incident and enough graphs to argue about it for the rest of the week. Then they go to test a change and start from scratch. The integration tests hit a hand-written mock that returns {"status": "ok"}. The load tests replay a CSV somebody exported months ago. Staging is close enough to production right up until it matters.

Feature Friday: How to Track GitHub Copilot Adoption with Cortex Scorecards

Are you getting the most out of your GitHub Copilot investment? In this week's, Cortex Engineer Aaron Warrick demonstrates how to turn "AI adoption" from a buzzword into a measurable metric. Using the CQL (Cortex Query Language) Query Builder, you can now pull real-time GitHub Copilot data into your service maturity scorecards. In this video, we cover: How to use the new AI Tools Analysis in the CQL Query Builder.