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@faun shared a link, 10 months ago
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Serving 200 million requests per day with a cgi-bin

UsingGoandRustwith CGI-style requests taps into multi-core CPU might, poking fun at long-held CGI inefficiency myths... read more  

Serving 200 million requests per day with a cgi-bin
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@faun shared a link, 10 months ago
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Caching is an Abstraction, not an Optimization

Cachingdoes more than rev up performance; it cuts through the chaos of software design, making it tidier and more modular. Sure,LRUandLFUsound like they should open for a prog rock band, but their trusty old formulas stand strong against those wild swings in data access... read more  

Caching is an Abstraction, not an Optimization
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@faun shared a link, 10 months ago
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Insights from paper — Bigtable: A Distributed Storage System for Structured Data

Bigtableisn't just another footnote in Google's lineup. It dominates the data landscape, wrangling petabytes like a charm. Built for atomic row operations and sly tablet splits. Plus, it’s backed by Chubby’s fault-tolerance magic. Picture it as a NoSQL and relational database crossbreed with the fle.. read more  

Insights from paper — Bigtable: A Distributed Storage System for Structured Data
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OpenYurt Becomes a CNCF Incubating Project

OpenYurt, a CNCF brainchild, shakes up cloud-edge orchestration. It dances with Kubernetes like Fred Astaire and partners with any vendor under the sun... read more  

OpenYurt Becomes a CNCF Incubating Project
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@faun shared a link, 10 months ago
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Understanding Network Packet Offsets & Safe Parsing in eBPF

eBPFandRustteam up to drive a network packet parser that catches packets at breakneck kernel speed. Welcome to the future of observability and security.XDPsteps in, slicing latency to the bone for real-time inspection... read more  

Understanding Network Packet Offsets & Safe Parsing in eBPF
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Atlassian moved 4 million Postgres databases to AWS Aurora

Atlassianpulled off a major coup, relocating 4 million Jira Postgres databases toAWS Aurora. They slashed expenses by taming CPU beasts and carved out a rock-solid 99.99% uptime. A delightful efficiency cocktail. SamsungandTSMCare brooming through some project cobwebs. Samsung's rethinking its Texas.. read more  

Atlassian moved 4 million Postgres databases to AWS Aurora
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@faun shared a link, 10 months ago
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Why Kubernetes Throttled My Idle Pods

70% CPU throttlingbaffled me in Kubernetes—minimal CPU usage, yet throttling? Alexandru Lazarev nailed it: ditch the CPU limits. Instant fix. Prometheus paints the spikes, while Grafana smooths them into a bore. Maybe those burstable CPU limits will swoop in to save us soon... read more  

Why Kubernetes Throttled My Idle Pods
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Kmesh v1.1.0 Officially Released!

Kmesh v1.1.0shakes things up with an overhauled DNS module. It’s got one job: tackle hostname resolution—no more, no less. BPF configuration? Now effortless, thanks to global variables. As for Kernel-Native mode, it’s less needy. Just a single tweak left inLinux kernel 6.6. Progress... read more  

Kmesh v1.1.0 Officially Released!
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Running high-performance PostgreSQL on Azure Kubernetes Service

PostgreSQLpumps life into 36% ofKubernetesworkloads. Over at Azure, they've got localNVMestorage that's as fast as a hot knife through butter—perfect for those deployments that absolutely must defy gravity. For the budget-conscious,Premium SSD v2struts in offering beefy scalability. We're talking up.. read more  

Running high-performance PostgreSQL on Azure Kubernetes Service
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Cloud Native App Local Development Made Easy with Microcks and Dapr

Dapr's sidecar model makes service talk a breeze.Microcks? It's all about pretending those pesky dependencies are there, so developers can run tests without spinning up an entire Kubernetes circus... read more  

Cloud Native App Local Development Made Easy with Microcks and Dapr
NanoClaw is an open-source personal AI agent designed to run locally on your machine while remaining small enough to fully understand and audit. Built as a lightweight alternative to larger agent frameworks, the system runs as a single Node.js process with roughly 3,900 lines of code spread across about 15 source files.

The agent integrates with messaging platforms such as WhatsApp and Telegram, allowing users to interact with their AI assistant directly through familiar chat applications. Each conversation group operates independently and maintains its own memory and execution environment.

A core design principle of NanoClaw is security through isolation. Every agent session runs inside its own container using Docker or Apple Container, ensuring that the agent can only access files and resources that are explicitly mounted. This approach relies on operating system–level sandboxing rather than application-level permission checks.

The architecture is intentionally simple: a single orchestrator process manages message queues, schedules tasks, launches containerized agents, and stores state in SQLite. Additional functionality can be added through a modular skills system, allowing users to extend capabilities without increasing the complexity of the core codebase.

By combining a minimal architecture with container-based isolation and messaging integration, NanoClaw aims to provide a transparent, customizable personal AI agent that users can run and control entirely on their own infrastructure.