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@kala shared a link, 4 months, 2 weeks ago
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You Should Write An Agent

Building LLM agents - essentially looping stateless models through tools - looks simple. Until it isn't. Peel back the layers, and you hit real architectural puzzles:context engineering, agent loops, sub-agent choreography, execution constraints... read more  

You Should Write An Agent
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@kala shared a link, 4 months, 2 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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@kala shared a link, 4 months, 2 weeks ago
FAUN.dev()

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, 4 months, 2 weeks ago
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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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@devopslinks shared a link, 4 months, 2 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, 4 months, 2 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, 4 months, 2 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  

News FAUN.dev() Team
@kaptain shared an update, 4 months, 2 weeks ago
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Kubernetes Gateway API 1.4.0 Makes Network Routing More Declarative and Reliable

Istio Kubernetes

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
@kaptain shared an update, 4 months, 2 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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@anjali shared a link, 4 months, 2 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
k3d is an open-source utility designed to simplify running Kubernetes locally by wrapping K3s (Rancher’s lightweight Kubernetes distribution) inside Docker containers. Instead of creating virtual machines, k3d uses Docker as the execution layer, allowing developers to spin up multi-node Kubernetes clusters in seconds using minimal system resources.

k3d is especially popular for local development, CI pipelines, demos, and testing Kubernetes-native applications. It supports advanced setups such as multi-node clusters, load balancers, custom container registries, port mappings, and volume mounts, while remaining easy to tear down and recreate.

Because it uses K3s, k3d inherits a simplified control plane, bundled components, and reduced memory footprint compared to full Kubernetes distributions. This makes it ideal for developers who want a realistic Kubernetes environment without the overhead of tools like Minikube or full VM-based clusters.

k3d integrates cleanly with common Kubernetes workflows and tools such as kubectl, Helm, Skaffold, and Argo CD. It is frequently used to validate manifests, test Helm charts, and simulate production-like environments locally before deploying to cloud or on-prem clusters.