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@varbear shared a link, 1 month ago
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The AWS Lambda 'Kiss of Death'

A Galera writer node froze afterInnoDBundo history ballooned. PooledAWS Lambdaconnections left transactions open and pinned MVCC read views. The team killed stalled sessions, enabledinnodb_undo_log_truncate, and cappedinnodb_max_undo_log_size. They also set sessiontransaction_isolation=READ-COMMITTE.. read more  

The AWS Lambda 'Kiss of Death'
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@varbear shared a link, 1 month ago
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How The Heck Does Shazam Work? (An Interactive Exploration)

A phone captures audio and runs aFast Fourier Transform (FFT)on short windows. It builds aspectrogramand extractspeaks. Nearby peak pairs form compacthashes(two frequencies + time delta). Aninverted indexmaps those hashes to songs, and timing validates matches. Most services run lookups onserversaga.. read more  

How The Heck Does Shazam Work? (An Interactive Exploration)
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@kaptain shared a link, 1 month ago
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From public static void main to Golden Kubestronaut: The Art of unlearning

The author left JVM monolith ops forKubernetes. They stacked certs:CKA,CKAD,CKS,KCNA,KCSA,CNCF Golden Kubestronaut. They treatPodsas the atomic deployable. They pick fights:IngressvsNodePort. They warn aboutConfigMapdrift. They spotlight runtime primitives:Horizontal Pod Autoscalerandservice meshfor.. read more  

From public static void main to Golden Kubestronaut: The Art of unlearning
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@kaptain shared a link, 1 month ago
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Why MicroVMs: The Architecture Behind Sandboxes

Docker Sandboxes puts each agent session in a dedicatedmicroVM. Each microVM runs a privateDocker daemoninside the VM boundary. That blocks access to the host. A new cross‑platformVMMruns on macOS, Windows, and Linux hypervisors. It slashes cold starts and runs fullDockerbuild, run, and compose work.. read more  

Why MicroVMs: The Architecture Behind Sandboxes
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@kaptain shared a link, 1 month ago
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The AI-driven shift in vulnerability discovery: What maintainers and bug finders need to know

AI modelslet non-experts craft real and fake vulnerabilities at scale. They spit out low-quality noise and the occasional high-value report. Reports floodOSS maintainers. Triage, patching, release cadences, and downstreamupgrade/compliancepipelines buckle under the load. Guidance recommends publishi.. read more  

The AI-driven shift in vulnerability discovery: What maintainers and bug finders need to know
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@kaptain shared a link, 1 month ago
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Building a fault-tolerant metrics storage system at Airbnb

Airbnb built a metrics system that ingests50M samples/s, stores2.5PBof logical time series, and hosts1.3B active series. They use tenant-per-service grouping andshuffle sharding. They enforce per-tenant guardrails and a consolidatedcontrol plane. They shard queries and compaction. They run zone-awar.. read more  

Building a fault-tolerant metrics storage system at Airbnb
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@kaptain shared a link, 1 month ago
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v1.36: User Namespaces in are finally GA

Kubernetesv1.36promotesUser Namespacesto GA on Linux. It brings rootless workload isolation. Kubelet leans on kernelID-mapped mounts. It sidesteps expensivechownby remappingUID/GIDat mount time and confines privileged processes. No more mass-chown screams... read more  

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@kala shared a link, 1 month ago
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Introducing Coregit

Coregit reimplements Git's object model inTypeScriptand runs onCloudflare Workersas a serverless edge Git API. Its commit endpoint accepts up to 1,000 file changes per request and replaces 105+ GitHub calls with one. Yes - one. It acknowledges writes inDurable Objects(~2ms), then flushes objects toR.. read more  

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@kala shared a link, 1 month ago
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The PR you would have opened yourself

ASkillports models fromtransformerstomlx-lm. It bootstraps an env, discovers variants, downloads checkpoints, writes MLX implementations, and runs layered tests. It produces disclosed PRs with per-layer diffs, dtype checks, generation examples, numerical comparisons, and a reproducible, non-agentict.. read more  

The PR you would have opened yourself
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@kala shared a link, 1 month ago
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A GitHub agentic workflow

The developer automated parsing of unstructured release notes withGitHub agentic workflows. The pipeline compilesMarkdowntoYAML, then runs an agent. The setup requires afine-grained Copilot token. It enforces a hardenedsandboxpolicy and forbids Marketplace actions. CI runs a compile-then-compare che.. read more  

A GitHub agentic workflow
INTELLECT-3 is a frontier-class 100B+ Mixture-of-Experts language model developed by Prime Intellect and trained end-to-end using their large-scale asynchronous RL framework, PRIME-RL. Built on the GLM-4.5-Air base model, INTELLECT-3 combines supervised fine-tuning with long-horizon reinforcement learning across hundreds of verifier-backed environments spanning math, code, science, logic, and agentic tasks.

The model was trained on a high-performance cluster of 512 NVIDIA H200 GPUs across 64 nodes, supported by Prime Intellect’s Sandboxes execution engine, deterministic compute orchestration, and Lustre-backed distributed storage. The result is a model that surpasses many larger systems in reasoning benchmarks while remaining fully open-source.

Prime Intellect released not only the model weights but also the full training recipe: PRIME-RL, Verifiers, the Environments Hub, datasets, and evaluation suites. INTELLECT-3 is positioned as a foundation for organizations seeking to post-train or customize their own frontier-grade models without relying on proprietary AI labs.