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

cloudzero

Cloud Cost Optimization Framework: Build Your FinOps Practice (2026)

Apr 6, 2026 By Lyne Carolyne In CloudZero
Quick answer: A cloud cost optimization framework is a structured, repeatable system for managing cloud spend across people, processes, and tools. It defines how teams gain cost visibility, allocate spend to the right owners, optimize resources and rates, and measure whether spend is generating business value. The FinOps Foundation organizes this around three phases: Inform, Optimize, and Operate — and the Crawl, Walk, Run maturity model maps directly to how organizations progress through them.
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harness

AI Demos Are Easy. Enterprise AI Is Not. | Harness Blog

Apr 6, 2026 By Shubham Jindal In Harness
‍Why 90% of AI prototypes never make it to production, and what to do about it. Every week, someone on my team shows me a demo that looks incredible. An agent that writes deployment pipelines. A chatbot that triages incidents. A copilot that generates test cases from Jira tickets. The demo takes 20 minutes. The audience claps. Everyone leaves convinced we're six weeks from shipping it. We're not.
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harness

Ansible vs Terraform Explained: Key Differences for Modern Infrastructure Automation | Harness Blog

Apr 6, 2026 By Mrinalini Sugosh In Harness
If DevOps teams mix up the roles of Ansible and Terraform, deployment pipelines can become unreliable. Manual handoffs slow down changes, and audits may find gaps where responsibilities overlap. Each tool solves different problems, so using them correctly avoids delays and compliance risks. Are you dealing with scattered provisioning and configuration workflows?
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harness

AI for GitOps: Tame your Argo Sprawl | Harness Blog

Apr 6, 2026 By Eric Minick In Harness
Innovation is moving faster than ever, but software delivery has become the ultimate chokepoint. While AI coding assistants have flooded our repositories with an unprecedented volume of code, the teams responsible for actually delivering that code, our Platform and DevOps engineers, are often left drowning in manual toil. If you’re managing Argo CD at an enterprise scale, you’re painfully familiar with the "Day 2" reality.
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End to End Reliability for all your Workloads

Apr 6, 2026 By Datadog In Datadog
Delivering great products to your customers requires a mix of evolution and consistency. To really land with users your product has to be ready to adapt and scale, prioritizing across a mix of customer and business needs. Join experts in reliability, systems engineering, and DevOps as they share real-world examples, true stories of pitfalls, and astounding impact from the experiments they have run. Learn how experienced practitioners handle failure, adapt to scale, and bridge gaps between teams to improve software performance and customer outcomes.
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Why Cloud and DevOps Practices Matter to Prop Trading Firms

Why Cloud and DevOps Practices Matter to Prop Trading Firms

Apr 6, 2026 By OpsMatters In OpsMatters
The financial industry has always been driven by speed, precision, and the ability to act on information faster than anyone else. In recent years, prop trading firms have found themselves at a crossroads where traditional infrastructure simply cannot keep up with the demands of modern markets. Cloud computing and DevOps practices have emerged as two of the most transformative forces reshaping how trading operations are built, managed, and scaled. Understanding why these technologies matter is not just useful for tech teams, it is essential knowledge for anyone involved in or curious about the future of high-performance trading.
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upsun

That production incident cost more than downtime

Apr 5, 2026 By Upsun In Upsun
Every developer knows the sudden, cold spike of adrenaline that comes with a P0 alert. The site is down, the Slack channel is overwhelmed with notifications, and the "war room" is officially open. In the immediate aftermath, leadership looks at one metric: downtime. They calculate the lost revenue per minute and the hit to brand reputation. But for the engineering team, the official resolution of the incident is only the beginning.
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upsun

Debugging the black box: why LLM hallucinations require production-state branching

Apr 4, 2026 By Upsun In Upsun
The most frustrating sentence in modern engineering is no longer "it works on my machine." It is: "It worked in the playground." When an LLM-powered feature, such as a RAG-based search, an autonomous agent, or a dynamic prompt engine, fails in production, it doesn’t throw a standard stack trace. It returns "slop," hallucinations, or silent retrieval failures. Standard debugging workflows fail during triage because LLM hallucinations cannot be reproduced using static mocks or clean seed data.
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