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

10 platform engineering tools your devs will thank you for

Modern engineering teams are shipping more services, managing more complex infrastructure, and moving faster than ever. But this velocity often comes at a cost to the developer experience. Engineers are frequently bogged down by infrastructure complexity, inconsistent tooling, and a lack of clear standards, which leads to cognitive overload and slower cycle times.

Metrics That Matter In FinOps: Co-Create Value With Engineering And Finance Collaborations

FinOps thrives on clarity, and clarity is built on metrics. Metrics give engineering and finance a shared language to understand costs, evaluate trade-offs, and guide innovation. The most impactful metrics go beyond “how much are we spending?” and help us answer: When we measure these things, we stretch beyond tracking progress to fueling it.

Smooth Operator: The Role Of Autonomous FinOps In Cloud Cost Management

(Almost) everyone is using generative AI, and just as many aren’t seeing any benefits. Research firm Gartner calls it the “gen AI paradox” — nearly 80% of companies say they’ve invested in generative solutions, and the same number report no benefits to their bottom line. What’s more, 90% of projects are stuck in pilot mode; ready to take off, but just can’t get up to speed.

Harness AWS: From Code to Cloud, Smarter and Faster

Harness makes software delivery in AWS faster, safer, and more delightful. Harness, the AI Platform for Everything After Code, offers CI/CD, infrastructure-as-code management, and cloud cost management capabilities tailored to the AWS environment. Harness has come a long way since its 2019 debut on the AWS Marketplace. Back then, over half of Harness customers were already running on AWS, and Harness focused on delivering Continuous Delivery as a Service for AWS applications.

AI and DevOps in 2025: How Autonomous Engineering Will Transform Software Operations and Reliability

DevOps started as a way to break down barriers between development and operations, but by 2025 the movement has shifted into something far more ambitious. Instead of simply speeding up releases or tightening workflows, companies are now adopting autonomous engineering systems-tools powered by AI that don't just support DevOps practices but actually carry them out.

KubeCon Retrospective: Platform Engineering Needs to Do More Testing

Every year, KubeCon offers a candid look at where the cloud-native community stands — the tools gaining traction, the pain points teams share, and the big gaps still holding organizations back. After a week of deep conversations, session hopping, and talking to dozens of platform teams, one theme became impossible to ignore: Platform engineering still isn’t doing enough testing. And even more surprising: many teams don’t think testing is their responsibility.

How LEO satellite technology is transforming enterprise connectivity

How LEO satellite technology is transforming enterprise connectivity It’s not new to say that reliable, high-speed connectivity is critical for businesses. Yet even as global networks expand, many enterprises still face connectivity challenges, whether operating in remote industrial zones, across oceans or in developing regions with limited terrestrial infrastructure.

Drowning in Tickets? Your IT Service Desk Solution Might be Why

You hear that? It’s the unmistakable, terrifying flood of tickets rolling in! Password resets, VPN issues, access requests, and performance alerts. The numbers climb faster than the team can respond. You’ve added automation, new tools, even a chatbot or two, but the tide surges on. Here’s a plot twist: sometimes, your IT service desk solution isn’t solving the problem. Sometimes, it’s the thing keeping the problem alive.

Microsoft Sentinel Cost Optimization with Staged Routes and Commit Processors

As security data volumes grow, so do the costs of processing and storing them. Microsoft Sentinel and other SIEM platforms charge based on data ingestion, which makes every decision about normalization rules critical and every duplicate log a direct expense. Enterprise-scale security data pipelines face a persistent problem: data duplication across normalization tiers. As logs move through multiple transformation stages, it’s often impossible to know in advance which version will succeed.