Micha the DevOp

🔁 #Filament is an #opensource engine for pluggable data replication written in #golang. It moves data from sources to sinks via full, incremental or change data capture (#CDC) replication 🧵👇

🚀 Install via curl script, #Homebrew or prebuilt Linux/macOS binaries. Production runs on #Kubernetes with #Helm, or one-click deploys on #Railway, #Render and #DigitalOcean (standalone image with #SQLite)

github.comGitHub - galaxy-io/filament: Pluggable data replication with checkpointing, batching, and integrity eventsPluggable data replication with checkpointing, batching, and integrity events - galaxy-io/filament

📜 Apache-2.0 licensed 🌐 github.com/galaxy-io/f...

🔁 #Filament is an #opensource engine for pluggable data replication written in #golang. It moves data from sources to sinks via full, incremental or change data capture (#CDC) replication 🧵👇

🧩 Sources, sinks, state storage and event transport are replaceable interfaces. Run it as a service with API and #React web UI, deploy it on your own infrastructure, or embed the engine in a Go application

⚙️ Event-driven runtime: the server accepts pipeline and run requests, a control plane schedules and dispatches work, workers execute runs. #PostgreSQL stores durable state, #NATS JetStream carries lifecycle events

🔁 #Filament is an #opensource engine for pluggable data replication written in #golang. It moves data from sources to sinks via full, incremental or change data capture (#CDC) replication 🧵👇

🐘 Dear #PHP folks, please don't let the name confuse you :) This is not the #Laravel admin panel, it's a data pipeline engine

✅ Every batch is verified on both sides of the write, and durable checkpoints only advance after successful work, so runs can safely pause and resume

🔀 #HarnessRouter Community Edition is a self-hosted, Apache-2.0 #opensource layer that turns existing agent harnesses into pluggable backends behind one API #AIagents #selfhosted 🧵👇

🐳 One #Docker container bundles Console, Gateway and Runner. Bring your own provider key, no account or bundled model required

github.comGitHub - HarnessRouter/harnessrouter: HarnessRouter Community Edition: the self-hosted, Apache-2.0 edition of the unified interface for agent harnesses. Run Codex, Claude Code, Hermes, PI, DSH, and more through one API, with sessions, streaming, files, cancellation, and failure handling. Implements HarnessRouter Community Edition: the self-hosted, Apache-2.0 edition of the unified interface for agent harnesses. Run Codex, Claude Code, Hermes, PI, DSH, and more through one API, with sessions, ...

🚀 Starter kits cover slides, sheets, dashboards and videos, and the optional managed Cloud uses the same API contract 🌐 github.com/HarnessRout...

🔀 #HarnessRouter Community Edition is a self-hosted, Apache-2.0 #opensource layer that turns existing agent harnesses into pluggable backends behind one API #AIagents #selfhosted 🧵👇

📊 Project benchmark across eight harness × model configurations on one task: cost ranged from 223 down to 0.47 credits (99.8% lower) and latency from 4m 36s to 1m 25s (3.2x faster). The best configuration varies per task

🔐 Secrets passed through env references or vault are redacted from responses, streams, traces and stored records. Sessions run in separate workspaces under separate OS users

🔀 #HarnessRouter Community Edition is a self-hosted, Apache-2.0 #opensource layer that turns existing agent harnesses into pluggable backends behind one API #AIagents #selfhosted 🧵👇

🔌 Implements the Unified Harness Protocol (#UHP), an open, versioned standard whose task surface is compatible with the #OpenAI Responses API, so existing SDKs, streaming parsers and UI components keep working

⚙️ Handles the harness engineering: persistent sessions, streaming progress via server-sent events, file inputs and artifacts, cancellation, structured failures, idempotent retries and W3C trace context propagation

🔀 #HarnessRouter Community Edition is a self-hosted, Apache-2.0 #opensource layer that turns existing agent harnesses into pluggable backends behind one API #AIagents #selfhosted 🧵👇

🧩 26 harness bases supported today, including #Codex, #ClaudeCode, Hermes, Pi, DeepSeek Harness, #OpenCode, Kilo Code, Qwen Code, #GeminiCLI, Cline, goose, #Aider and #OpenHands. Switching harness means changing one field: metadata.harness_id

🤖 #Rakazo: #opensource #selfhosted #AIagents platform for persistent #AI teammates. Web, Electron desktop, iPhone and Android. Bring your own model and sandbox. Alternative to Grok Bot, OpenClaw and Hermes Agent. Apache-2.0, in beta. 🧵👇

🚀 One-command install from published Docker images (amd64 + arm64), one-click Railway deploy, or a VPS behind HTTPS that you connect to from desktop, mobile or browser. UI available in 9 languages, including Deutsch.

github.comGitHub - elie222/rakazo: Open-source Grok Bot alternative. Choose your own model and sandbox.Open-source Grok Bot alternative. Choose your own model and sandbox. - elie222/rakazo

🔧 Stack: #TypeScript, React 19, Vite, Tailwind CSS, Hono, oRPC, #PostgreSQL, Prisma, Better Auth, Graphile Worker and Expo. github.com/elie222/rakazo

🧠 Bring your own model credentials through Pi. Bots can delegate work to peer bots or short-lived subagents. Voice mode speaks replies, takes dictation and handles calls with your own ElevenLabs, OpenAI, Cartesia or Fish Audio key.

🔌 App integrations through Composio or Pipedream Connect, plus user-installed Treg, remote MCP and OpenAPI tool sources. Connector credentials are encrypted on the server and never returned by the API.

💬 Once running, it is just chat: set up a bot and manage it from that same conversation. Each bot keeps its own conversations, memory, routines and history.

🖥️ Bots get real computers with browser, terminal, file and graphical desktop access. Shared Team Computers or isolated Private computers via Docker, E2B, Daytona, CreateOS, Box, Railway or a trusted local machine.

🧩 #OpenUI is an open standard for #GenerativeUI: #LLMs stream a compact language, OpenUI Lang, that renders as live UI components while tokens arrive. #opensource, MIT. 🧵👇#ai

🔌 Works with LangChain and LangGraph via AG-UI, assistant-ui, Google's A2UI protocol, React Email, plus a browser bundle for CDN and iframe embeds.

github.comGitHub - thesysdev/openui: The Open Standard for Generative UIThe Open Standard for Generative UI. Contribute to thesysdev/openui development by creating an account on GitHub.

🚀 npx @openuidev/cli@latest create scaffolds a streaming chat app. An Agent Skill helps Claude Code, Codex, Cursor & Copilot build with it. #React #Vue #Svelte #Angular #LangChain github.com/thesysdev/o...

🧩 #OpenUI is an open standard for #GenerativeUI: #LLMs stream a compact language, OpenUI Lang, that renders as live UI components while tokens arrive. #opensource, MIT. 🧵👇#ai

🔄 Define a component library, generate the system prompt from it, stream OpenUI Lang back, render progressively. The model can only output registered components, with props typed via Zod.

🧱 First-party runtimes for React, Vue 3, Svelte 5 and Angular. React adds built-in charts, forms, tables, layouts and ready-made chat UIs.

🧩 #OpenUI is an open standard for #GenerativeUI: #LLMs stream a compact language, OpenUI Lang, that renders as live UI components while tokens arrive. #opensource, MIT. 🧵👇#ai

⚡ Up to 67% fewer tokens than JSON. Across seven UI scenarios: 4,800 tokens vs 10,180 (Vercel JSON-Render) and 9,948 (Thesys C1 JSON). At 60 tok/s: ~4.9s instead of 14.2s.

📦 Static site bundles from a #Laravel app #Spatie Laravel Export crawls your app, saves every URL as static HTML and adds the public folder for assets. One command: php artisan export #PHP #opensource #webdev 🧵👇

🔧 before and after hooks run any shell command: build assets with Yarn before the export, deploy with the Netlify CLI afterwards. Skip hooks with --skip-deploy, --skip-before, --skip-after or --skip-all

github.comGitHub - spatie/laravel-export: Create a static site bundle from a Laravel appCreate a static site bundle from a Laravel app. Contribute to spatie/laravel-export development by creating an account on GitHub.

📊 MIT licensed, 676 stars, installed via #Composer. Zero configuration needed to get started github.com/spatie/lara...

📁 include_files adds folders relative to the app root (default: public). exclude_file_patterns drops files via regex. .php files and mix-manifest.json are excluded by default, so index.php never lands in the export

💾 Output goes to a Laravel filesystem disk (default: a dist folder). Any driver works, including #S3, to export straight to cloud storage. All content options are also exposed in code via the injectable Exporter class, e.g. paths from Post::all()->pluck('slug')

🎯 Build a blog or site with the Laravel tools you already know, export it and upload it anywhere. No full server to manage. Or edit content in an admin panel like #Filament, #Nova, Wink or Sharp and publish the static result to #Netlify

🕷️ Crawling is on by default and finds pages automatically. Enable use_streaming to cut memory usage on large sites. Prefer full control? Disable crawl and list exact paths like "/" or "/rss.xml"

📋 #Redis memory tip for #Laravel counters: stop creating one key per counter. 1M posts means 1M keys, and each key carries roughly 50–100+ bytes of overhead, even when the value is a tiny integer. #PHP #performance 🧵👇

⚠️ Trade-offs: TTLs apply to the whole hash, not single fields (Redis 7.4+ adds HEXPIRE for field-level expiry). Laravel's Cache facade has no HINCRBY, so this runs through the Redis facade directly.

laracopilot.comLaravel Redis Cache Guide, 2026 Performance PlaybookLaravel Redis cache setup, key and TTL patterns, tags, locks, and the config mistakes to avoid. A 2026 playbook for faster Laravel caching at real scale.

🌐 More Laravel Redis patterns (key conventions, TTLs, tags, locks, Cache::flexible): laracopilot.com/blog/larave...

🎯 The catch: the compact listpack encoding only applies to small hashes (default hash-max-listpack-entries = 128). One giant hash with millions of fields falls back to a regular hashtable. Bucket instead: key "posts:views:" . intdiv($id, 100), field $id % 100.

📊 Result: often 3–10x less RAM for counters, depending on data shape. Best fit: views, likes, rate limits, per-IP or per-user counters with millions of entries.

❌ The costly pattern: Redis::incr("post:{$id}:views") plus an expire per key. Simple, but at high cardinality the key structure alone eats hundreds of MB.

✅ The leaner pattern: group counters into hashes. Redis::hincrby('posts:views', $id, 1) to write, HGET to read. The per-key overhead gets shared across many fields.

🧠 #DeepSeek has open-sourced #DeepInfer, the high-performance #inference framework that powers its large-scale production services. The release covers offline inference with the core features needed for serving at scale, currently for DeepSeek-V4.1-Flash #opensource #LLM 🧵👇

🖥️ Hardware: #NVIDIA SM100 GPUs and #Huawei Ascend 950 NPUs. Requires Linux, GCC 13+, #Python 3.12 and #CUDA 13 or CANN 9.2. Benchmarks were measured on 4 SM100 GPUs for prefill and 64 for decode

github.comGitHub - deepseek-ai/DeepInfer: DeepInfer: High-performance, large-scale inference framework for DeepSeek modelsDeepInfer: High-performance, large-scale inference framework for DeepSeek models - deepseek-ai/DeepInfer

🧩 Not included: a KV cache system, prefill/decode disaggregation and load balancing across data-parallel replicas. Originally built on #vLLM with inspiration from #SGLang and TensorRT-LLM. Apache 2.0 license 🌐 github.com/deepseek-ai...

🎯 Faster decoding with DSpark draft tokens and confidence-scheduled verification (default max draft length: 5). SWA bounded replay cuts decoder prefill work by replaying only a bounded suffix

🔒 Batch-invariant inference keeps results identical across batch compositions, deterministic sampling returns identical outputs for identical inputs and seeds (both NVIDIA only). Structured outputs constrain generation to regex, JSON schema or EBNF grammar

⚡ Optimized kernels from DeepSeek's own stack: #FlashMLA, #DeepGEMM, #DeepEP, TileKernels, DeepSelect and custom #TileLang kernels, plus an optimized model and sampler runtime