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

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

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?

AI for GitOps: Tame your Argo Sprawl | Harness Blog

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.

End to End Reliability for all your Workloads

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.

HAProxy at KubeCon Amsterdam 2026: the standard, by popular demand

KubeCon + CloudNativeCon Europe 2026 brought thousands of cloud-native practitioners to Amsterdam for four days of talks, demos, and hallway conversations about where Kubernetes is heading. HAProxy Technologies came as a Diamond Sponsor, and by the time the exhibition floor closed on Thursday, it was clear that the market had reached the same conclusion we had. HAProxy is the standard — and this year, more people than ever were ready to say so out loud.

Resolve Reels - Ep. 2 - Scheduled Jobs Dashboard LI

Episode 2 of Resolve Reels is here. In this walkthrough, we introduce the new Scheduled Workflows Dashboard in Resolve Actions. Get a centralized view of every scheduled automation across your environment. Track execution status, monitor success and failure rates, and quickly drill into workflow performance. See how teams can: This is how modern IT teams move from reactive oversight to proactive control. With Resolve, automation is not just executed. It is continuously monitored, optimized, and scaled.

Why Cloud and DevOps Practices Matter to Prop Trading Firms

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.

That production incident cost more than downtime

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.

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

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.