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@varbear shared a link, 2 months, 2 weeks ago
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Why I Vibe in Go, Not Rust or Python

In a world where the machine writes most of the code, Python lacks solid type enforcement, Rust is overly strict with complex lifetimes, while Go strikes the right balance by catching critical issues without hindering development velocity. The article argues in favor of Go over Python and Rust for A.. read more  

Why I Vibe in Go, Not Rust or Python
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@varbear shared a link, 2 months, 2 weeks ago
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What if Python was natively distributable?

The Python ecosystem's insistence on solving multiple problems when distributing functions has led to unnecessary complexity. The dominant frameworks have fused orchestration into the execution layer, imposing constraints on function shape, argument serialization, control flow, and error handling. W.. read more  

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@kaptain shared a link, 2 months, 2 weeks ago
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AWS Load Balancer Controller Reaches GA with Kubernetes Gateway API Support

AWS ships GAGateway APIsupport in theAWS Load Balancer Controller. Teams can manageALBandNLBwith the SIG standard. The controller swaps annotation JSON for validated CRDs -TargetGroupConfiguration,LoadBalancerConfiguration,ListenerRuleConfiguration- and handles L4 (TCP/UDP/TLS) and L7 (HTTP/gRPC). M.. read more  

AWS Load Balancer Controller Reaches GA with Kubernetes Gateway API Support
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@kaptain shared a link, 2 months, 2 weeks ago
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jsongrep is faster than {jq, jmespath, jsonpath-rust, jql}

This article introduces a tool called jsongrep, explains the internal search engine it uses, and outlines the benchmarking strategy used to compare its performance with other JSON path-like query tools. The tool parses the JSON document, constructs an NFA from the query, determinizes the NFA into a .. read more  

jsongrep is faster than {jq, jmespath, jsonpath-rust, jql}
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@kaptain shared a link, 2 months, 2 weeks ago
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A one-line Kubernetes fix that saved 600 hours a year

Atlantis, a tool for planning and applying Terraform changes, faced slow restarts of up to 30 minutes due to a safe default in Kubernetes that became a bottleneck as the persistent volume used by Atlantis grew to millions of files. After investigation, a one-line change to fsGroupChangePolicy reduce.. read more  

A one-line Kubernetes fix that saved 600 hours a year
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@kaptain shared a link, 2 months, 2 weeks ago
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Deploying Disaggregated LLM Inference Workloads on Kubernetes

In large language model (LLM) inference workloads, a single monolithic serving process can hit its limits due to different compute profiles for prefill and decode stages. Disaggregated serving splits the pipeline into distinct stages to better utilize GPU resources and scale more flexibly on Kuberne.. read more  

Deploying Disaggregated LLM Inference Workloads on Kubernetes
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@kaptain shared a link, 2 months, 2 weeks ago
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Trivy Hack Spreads Infostealer via Docker, Triggers Worm and Kubernetes Wiper

Cybersecurity researchers found malicious artifacts distributed via Docker Hub after the Trivy supply chain attack. Malicious versions 0.69.4, 0.69.5, and 0.69.6 of Trivy were removed from the image library. Threat actor TeamPCP targeted Aqua Security's GitHub organization, compromising 44 repositor.. read more  

Trivy Hack Spreads Infostealer via Docker, Triggers Worm and Kubernetes Wiper
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@kala shared a link, 2 months, 2 weeks ago
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Building a digital doorman

Larson runs a dual-agent system. A tiny public doorman,nullclaw, lives on a $7 VPS. A private host,ironclaw, runs over Tailscale. Nullclaw sandboxes repo cloning. It routes heavy work to ironclaw viaA2AJSON‑RPC. It enforcesUFW, Cloudflare proxying, and single‑gateway billing... read more  

Building a digital doorman
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@kala shared a link, 2 months, 2 weeks ago
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What 81,000 people want from AI

Anthropic used a version of Claude to interview 80,508 users across 159 countries and 70 languages - claiming the largest qualitative AI study ever conducted. The top ask wasn't productivity, it was time back for things that matter outside of work. The top fear was hallucinations and unreliability. .. read more  

What 81,000 people want from AI
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@kala shared a link, 2 months, 2 weeks ago
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Multi-Agent AI Systems: Architecture Patterns for Enterprise Deployment

Last quarter, a mid-sized insurance company struggled to deploy an AI agent that collapsed in production due to cognitive overload. Enterprises are facing similar challenges when building single-agent AI systems and are moving towards multi-agent architectures to distribute responsibilities effectiv.. read more  

Multi-Agent AI Systems: Architecture Patterns for Enterprise Deployment
BigQuery is a cloud-native, serverless analytics platform designed to store, query, and analyze massive volumes of structured and semi-structured data using standard SQL. It separates storage from compute, automatically scales resources, and eliminates the need for infrastructure management, indexing, or capacity planning.

BigQuery is optimized for analytical workloads such as business intelligence, log analysis, data science, and machine learning. It supports real-time data ingestion via streaming, batch loading from cloud storage, and federated queries across external data sources like Cloud Storage, Bigtable, and Google Drive.

Query execution is distributed and highly parallel, enabling interactive performance even on petabyte-scale datasets. The platform integrates deeply with the Google Cloud ecosystem, including Looker for BI, Vertex AI for ML workflows, Dataflow for streaming pipelines, and BigQuery ML, which allows users to train and run machine learning models directly using SQL.

Built-in security features include fine-grained IAM controls, column- and row-level security, encryption by default, and audit logging. BigQuery follows a consumption-based pricing model, charging for storage and queries (on-demand or reserved capacity).