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@kala shared a link, 1 month, 1 week 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, 1 month, 1 week 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, 1 month, 1 week 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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@kala shared a link, 1 month, 1 week 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, 1 month, 1 week 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, 1 month, 1 week 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, 1 month, 1 week 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, 1 month, 1 week 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.

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@kaptain shared an update, 1 month, 1 week ago
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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 , 1 month, 1 week ago.
Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.