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

Running AI without blowing up your storage

Aug 1, 2025 By Canonical Ubuntu In Canonical
Storage is often underestimated: In infrastructure discussions, compute and networking get most of the attention, while storage is treated as secondary. For AI workloads, that can be a costly oversight. Data throughput for specialized hardware: AI infrastructure powered by GPUs can process massive volumes of data at unprecedented speeds. This puts immense pressure on the storage system to keep up. Scale-out performance: An on-prem, scale-out, software-defined storage setup allows you to meet high performance demands, grow capacity as needed, and stay in control of infrastructure costs.
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puppet

Bridging the Gap: 3 Practical Strategies to Align Security and Operations in DevOps

Aug 1, 2025 By Puppet In Puppet
The gap between security operations and IT operations poses significant risk. It’s increasingly clear that DevOps leaders, IT managers, and enterprise teams face an uphill battle to manage growing threat complexity, endless patches, and compliance requirements while operating in silos. Bridging this gap is essential to effectively manage risks and enhance operational efficiency.
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Teneo

Securing the Invisible: Why Ambient AI Needs Next-Gen Security

Aug 1, 2025 By Teneo In Teneo
If, like me, you’re continuously striving to keep pace with the ever-evolving world of artificial intelligence, you’re probably hearing a lot about how Ambient AI is poised to dominate discussions and developments throughout the second half of 2025. Ambient AI refers to artificial intelligence systems that operate unobtrusively in the background of our daily environments, constantly sensing, analyzing, and responding to various inputs without explicit human interaction.
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metricfire

Librato on Heroku is Going Away and Hosted Graphite Is the Better Next Step

Aug 1, 2025 By Benjamin Pitts In MetricFire
Librato (a SolarWinds product) is being sunsetted summer of 2025, and that directly affects Heroku teams who’ve relied on the Librato add-on for “good enough” visibility into dynos, routers, and Postgres. If you’re in that group, you’ll need a replacement monitoring add-on that keeps you covered on Heroku and lets you grow beyond it without re-architecting how you ship metrics.
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The strategic art of build vs. buy in software delivery ft. Tara Hernandez of MongoDB

Aug 1, 2025 By CircleCI In CircleCI
Rob Zuber sits down with Tara Hernandez, VP of Developer Productivity at MongoDB and former Netscape engineer who helped create early continuous integration systems, to explore strategic frameworks for build vs. buy decisions in modern software delivery.
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last9

Jaeger Monitoring: Essential Metrics and Alerting for Production Tracing Systems

Aug 1, 2025 By Anjali Udasi In Last9
Your Jaeger setup is running. Traces are coming in, and the UI is helping you spot slow services or debug broken flows. But just like any part of your observability stack, Jaeger needs some basic monitoring to stay reliable. If the collector starts queueing spans or the agent runs out of buffer, it can lead to dropped traces, sometimes without any obvious sign in the UI. This blog focuses on the operational side of Jaeger.
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bunnyshell

When AI Becomes the Judge: Understanding "LLM-as-a-Judge"

Jul 31, 2025 By Alin Dobra In Bunnyshell
Imagine building a chatbot or code generator that not only writes answers - but also grades them. In the past, ensuring AI quality meant recruiting human reviewers or using simple metrics (BLEU, ROUGE) that miss nuance. Today, we can leverage Generative AI itself to evaluate its own work. LLM-as-a-Judge means using one Large Language Model (LLM) - like GPT-4.1 or Claude 4 Sonnet/Opus - to assess the outputs of another. Instead of a human grader, we prompt an LLM to ask questions like "Is this answer correct?" or "Is it on-topic?" and return a score or label. This approach is automated, fast, and surprisingly effective.
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rancher

Autoscaling Made Easy with Rancher Cluster API

Jul 31, 2025 By Davide Rutigliano In Rancher
Kubernetes has revolutionized application deployment and management. However, manually adjusting cluster sizes to meet fluctuating workloads, without constantly under- or over-provisioning resources, quickly drains platform teams’ time and energy. While traditional cloud provider autoscaling tools are functional, they often fall short when it comes to truly dynamic, Kubernetes-aware scaling, especially in a world with diverse infrastructure.
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