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Migrating from Slurm to Kubernetes

SkyPilot drops a clean interface that blendsSlurmwithKubernetes. AI/ML teams get to keep their Slurm-style comforts - job scripts, gang scheduling, GPU guarantees, interactive workflows - but pick up Kubernetes perks like container isolation and rich ecosystem hooks. It handles the messy bits: pods,.. read more  

Migrating from Slurm to Kubernetes
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Zero-Downtime Ingress Controller Migration in Kubernetes

Ingress-nginxis heading for the exits - end-of-life drops March 2026. That puts Kubernetes operators on the hook to swap in a new ingress controller. The migration path? Run both old and new in parallel. Use DNS cutover. Point explicitly with Ingress classes. Done right, the switchover hits zero dow.. read more  

Zero-Downtime Ingress Controller Migration in Kubernetes
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LLMs on Kubernetes: Same Cluster, Different Threat Model

Running LLMs on Kubernetes opens up a new can of worms - stuff infra hardening won’t catch. You need a policy-smart gateway to vet inputs, lock down tool use, and whitelist models. No shortcuts. This post drops a reference gateway build usingmirrord(for fast, in-cluster tinkering) andCloudsmith(to t.. read more  

LLMs on Kubernetes: Same Cluster, Different Threat Model
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The State of Java on Kubernetes 2026: Why Defaults are Killing Your Performance

Akamas just dropped fresh numbers: over60% of Java apps running on Kubernetesstick with default JVM settings. That means sluggish memory use, GC thrash, and CPUs getting choked out. Even with "container-friendly" Java builds out there, most teams still skip setting GC types or heap sizes. Kubernetes.. read more  

The State of Java on Kubernetes 2026: Why Defaults are Killing Your Performance
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Building a TUI is easy now

Hatchet usedClaude Code, a terminal-native coding agent, to build and ship a real TUI-based workflow manager - fast. Like, days-fast. Powered by theCharm stack(Bubble Tea, Lip Gloss, Huh), it leans hard into CLI-heavy development. Claude Code handled live testing intmux, whipped up frontend views fr.. read more  

Building a TUI is easy now
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Adventures in Neural Rendering

A graphics dev took a swing at encoding rendering signals - radiance, irradiance, depth, AO, BRDFs - using tightMLPs in HLSL. They benchmarked size, storage, and runtime cost. Turns out, MLPs beatL2 spherical harmonicsfor packing radiance. But they stumble on irradiance and specular BRDFs. Bring inR.. read more  

Adventures in Neural Rendering
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Why Trying to Secure OpenClaw is Ridiculous

OpenClaw, an open-source autonomous AI agent with full device access, racked up 179K GitHub stars - and walked straight into a security nightmare. It shipped wide open: default ports exposed to the internet, its plugin hub laced with malicious packages. Slapped-on fixes followed, warning labels, Vir.. read more  

Why Trying to Secure OpenClaw is Ridiculous
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GPT-5.2 derives a new result in theoretical physics

GPT-5.2 Pro spotted something wild: a nonzero gluon scattering amplitude in the half-collinear regime. That’s supposed to vanish, according to standard QFT gospel. Not anymore. OpenAI’s own model backed it up with a formal proof. Humans triple-checked it analytically. And yep - it holds. Now it’s bl.. read more  

GPT-5.2 derives a new result in theoretical physics
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YOLO Mode: Hidden Risks in Claude Code Permissions

A scrape of 18,470 Claude Code configs on GitHub shows a pattern: developers are handing their AI agents the keys to the castle. Unrestricted file, shell, and network accessis common. Among them: - 21.3% let Claude runcurl - 14.5% allowarbitrary Python execution - 19.7% give itgit pushprivileges Tha.. read more  

YOLO Mode: Hidden Risks in Claude Code Permissions
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The future of software engineering is SRE

Agentic coding and no-code tools are everywhere now. Building features? Easier than ever. The harder part is keeping systems solid once they’re out in the wild. The real game:maintainability, reliability, and evolutionunder real pressure - not just building, but keeping it together over time... read more  

The future of software engineering is SRE
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).