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@kala shared a link, 3 weeks ago
FAUN.dev()

AI's Dial-Up Era

AI's reshaping jobs - but not evenly. Some industries will feel the squeeze faster than others. It all comes down to a race: productivity vs. demand. History's playbook? Think textiles, steel, autos. Automation boosted output. Jobs stuck around - as long as demand kept growing. Once markets topped o.. read more  

AI's Dial-Up Era
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@kala shared a link, 3 weeks ago
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AI Broke Interviews

AI has revolutionized technical interviews, blurring the line between genuine skill and cheating with perfect solutions and polished answers. In response, companies are shifting back to in-person interviews for real-time cognitive transparency, authenticity constraints, realistic collaboration signa.. read more  

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@kala shared a link, 3 weeks ago
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How I Use Every Claude Code Feature

Claude Code isn't just generating responses anymore - it's gearing up to run projects. The new direction turns it into a programmable, auditable agent runtime. Think custom hooks, restart logic, planning workflows, GitHub Actions, and subagent delegation tricks like the “Master-Clone” pattern. At th.. read more  

How I Use Every Claude Code Feature
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@devopslinks shared a link, 3 weeks ago
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Why I Like Using Docker Compose in Production

A decade in, and this dev still rides with Docker Compose for production. Why? It just works. Clean deployments, solid uptime, same setup everywhere. No yak-shaving. It shines when you pair it with Git hooks for hands-off, zero-downtime deploys. No need to drag in Kubernetes unless you’re actually w.. read more  

Why I Like Using Docker Compose in Production
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@devopslinks shared a link, 3 weeks ago
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Perfetto: Swiss Army Knife for Linux Client Tracing

Perfetto now pulls in mixed trace data -perfsamples, scheduler events, app-level instrumentation - and lines it all up on a single timeline. One view, no silos. It readstrace-cmd’s text format now, with smoother flame graphs, sharper bottom-up views, and SQL-powered filtering baked right into the UI.. read more  

Perfetto: Swiss Army Knife for Linux Client Tracing
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@devopslinks shared a link, 3 weeks ago
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VMware Cloud Foundation – what’s actually going on?

Broadcom underwent significant changes post-VMware acquisition, with emphasis on subscription-based pricing and portfolio simplification. Prashant Shenoy claims VCF lowered prices by 50%, challenging industry norms about AI workloads on bare metal versus virtualized environments. Integration pointed.. read more  

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@kaptain shared an update, 3 weeks ago
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Kubernetes Gateway API 1.4.0 Makes Network Routing More Declarative and Reliable

Kubernetes Istio

Kubernetes releases Gateway API 1.4.0, enhancing service networking with new features like secure TLS connections and improved configuration options.

Gateway API Logo
News FAUN.dev() Team Trending
@kaptain shared an update, 3 weeks ago
FAUN.dev()

Grafana Pushes the Limits of Metrics Performance with Mimir 3.0

Prometheus Grafana Mimir

Grafana Mimir 3.0 debuts with a new query engine and architecture, boosting performance, reliability, and cost efficiency.

Grafana Pushes the Limits of Metrics Performance with Mimir 3.0
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@kaptain added a new tool Grafana Mimir , 3 weeks ago.
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@anjali shared a link, 3 weeks ago
Customer Marketing Manager, Last9

OpenTelemetry Metrics in Quarkus Explained

Understand how to enable, export, and extend OpenTelemetry metrics in your Quarkus application with practical examples.

otel_metrics_quarkus
Slurm Workload Manager is an open-source, fault-tolerant, and highly scalable cluster management and scheduling system widely used in high-performance computing (HPC). Designed to operate without kernel modifications, Slurm coordinates thousands of compute nodes by allocating resources, launching and monitoring jobs, and managing contention through its flexible scheduling queue.

At its core, Slurm uses a centralized controller (slurmctld) to track cluster state and assign work, while lightweight daemons (slurmd) on each node execute tasks and communicate hierarchically for fault tolerance. Optional components like slurmdbd and slurmrestd extend Slurm with accounting and REST APIs. A rich set of commands—such as srun, squeue, scancel, and sinfo—gives users and administrators full visibility and control.

Slurm’s modular plugin architecture supports nearly every aspect of cluster operation, including authentication, MPI integration, container runtimes, resource limits, energy accounting, topology-aware scheduling, preemption, and GPU management via Generic Resources (GRES). Nodes are organized into partitions, enabling sophisticated policies for job size, priority, fairness, oversubscription, reservation, and resource exclusivity.

Widely adopted across academia, research labs, and enterprise HPC environments, Slurm serves as the backbone for many of the world’s top supercomputers, offering a battle-tested, flexible, and highly configurable framework for large-scale distributed computing.