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@kala shared a link, 2 weeks, 1 day ago
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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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@kala shared a link, 2 weeks, 1 day ago
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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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@devopslinks shared a link, 2 weeks, 1 day ago
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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
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@devopslinks shared a link, 2 weeks, 1 day ago
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Owning a $5M data center

Comma.ai just dropped the specs on its hand-rolled ML data center. Picture this: 600 homegrown GPU rigs (TinyBox Pros), 4PB of flash. The whole thing trains on a PyTorch stack they built themselves, wired up with a custom model tracker and job scheduler they namedMiniray. Inference runs through dyna.. read more  

Owning a $5M data center
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@devopslinks shared a link, 2 weeks, 1 day ago
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GitHub Actions Is Slowly Killing Your Engineering Team

A seasoned CI engineer lays into GitHub Actions - too fragile, too fuzzy, too slow. Logs glitch. YAML confuses. Compute chokes. It solves for convenience, not power. Buildkitesteps in with stronger bones: reproducible runs, clean orchestration, and scalable agents you control... read more  

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@devopslinks shared a link, 2 weeks, 1 day ago
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Why does SSH send 100 packets per keystroke? ·

The default macOS SSH client now floods connections withSSH2_MSG_PING “chaff” packets- a 2023 privacy tweak meant to hide keystroke timing. Nice in theory. In practice? It tanks performance for real-time terminal apps like games built on Bubbletea over SSH. Turning it off - either through client fla.. read more  

Why does SSH send 100 packets per keystroke? ·
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@devopslinks shared a link, 2 weeks, 1 day ago
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From Paging to Postmortem: Google Cloud SREs on Using Gemini CLI for Outage Response

Google Cloud SREs just leveled up their incident response game with theGemini CLI- an LLM-fueled terminal sidekick built onGemini 3. It jumps in fast: drafts mitigation playbooks, digs into root causes, and cranks out postmortem reports. All withhuman-in-the-loopguardrails to keep things sane... read more  

From Paging to Postmortem: Google Cloud SREs on Using Gemini CLI for Outage Response
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@kala shared an update, 2 weeks, 1 day ago
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GitHub Launches Copilot SDK to Embed Agentic AI into Any Application

GitHub Copilot GitHub Copilot SDK

GitHub has released the Copilot SDK in technical preview, allowing developers to embed Copilot’s agentic execution loop into their own applications. The SDK supports multiple AI models, real-time streaming, and languages like Python, TypeScript, Go, and .NET, but currently requires a Copilot subscription and is intended for development and testing rather than production use.

GitHub Launches Copilot SDK to Embed Agentic AI into Any Application
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@varbear shared an update, 2 weeks, 1 day ago
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VillageSQL Launches: A Drop-In MySQL Fork Bringing Extensions and AI to the Core

MySQL VillageSQL

VillageSQL is a drop-in, open-source fork of MySQL that introduces a true extension framework, enabling permissionless innovation for AI-era workloads. It allows developers to add custom data types and functions - with vector indexing and search on the roadmap - bringing MySQL closer to PostgreSQL-style extensibility without waiting for core upstream changes.

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@kala added a new tool GitHub Copilot SDK , 2 weeks, 1 day ago.
Grafana Tempo is a distributed tracing backend built for massive scale and low operational overhead. Unlike traditional tracing systems that depend on complex databases, Tempo uses object storage—such as S3, GCS, or Azure Blob Storage—to store trace data, making it highly cost-effective and resilient. Tempo is part of the Grafana observability stack and integrates natively with Grafana, Prometheus, and Loki, enabling unified visualization and correlation across metrics, logs, and traces.

Technically, Tempo supports ingestion from major tracing protocols including Jaeger, Zipkin, OpenCensus, and OpenTelemetry, ensuring easy interoperability. It features TraceQL, a domain-specific query language for traces inspired by PromQL and LogQL, allowing developers to perform targeted searches and complex trace-based analytics. The newer TraceQL Metrics capability even lets users derive metrics directly from trace data, bridging the gap between tracing and performance analysis.

Tempo’s Traces Drilldown UI further enhances usability by providing intuitive, queryless analysis of latency, errors, and performance bottlenecks. Combined with the tempo-cli and tempo-vulture tools, it delivers a full suite for trace collection, verification, and debugging.

Built in Go and following OpenTelemetry standards, Grafana Tempo is ideal for organizations seeking scalable, vendor-neutral distributed tracing to power observability at cloud scale.