How to Monitor Docker Container CPU and Memory Usage Without Extra Tools

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Docker includes a built-in 'docker stats' command that provides real-time CPU and memory metrics for running containers, requiring no additional software. Developers can customize output using format flags or capture periodic snapshots via shell scripts for lightweight historical logging. Setting memory limits on production containers is strongly advised, as unlimited containers can exhaust host RAM and trigger kernel OOM kills. For more robust monitoring, Google's open-source cAdvisor tool runs as a container and exposes Prometheus-compatible metrics for long-term storage and alerting. Pairing cAdvisor with Grafana enables full dashboard visibility, helping teams correlate performance issues with deployment events over time.

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Developer Builds MVP Weather Chatbot Using Node.js and Agentic Tool-Use Architecture

A developer has published Mausam AI, an open-source MVP chatbot built with Node.js that fetches real-time weather, temperature, and humidity data for any city. The project addresses a core limitation of large language models — their lack of real-time data — by integrating an external weather API called wttr.in. The bot uses an agentic loop architecture that forces the AI to follow a strict sequence of steps: START, PLAN, TOOL, and OUTPUT, with all responses structured as JSON. A maximum iteration cap of five cycles is enforced to prevent infinite loops or hallucinations during the tool-calling process. The project is explicitly described as a conceptual demonstration and is not intended for production use, with source code available on GitHub.

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ProgrammingHacker News ·

My Feed, My Way

Article URL: https://www.pm.gov.au/media/my-feed-my-way Comments URL: https://news.ycombinator.com/item?id=49605782 Points: 3 # Comments: 0

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ProgrammingDEV Community ·

Google Apps Script Turns Drive into Serverless AI Vector Search Engine via Apache Iceberg

A developer has published a serverless multimodal vector search architecture that uses Google Apps Script, Apache Iceberg, and BigQuery to eliminate the need for dedicated vector databases like Pinecone or Milvus. The system, built around an engine called IcebergApp.js, ingests heterogeneous Google Drive content — including Docs, Sheets, Slides, binary images, and web-fetched files — into a unified Apache Iceberg table stored as open Parquet files on Google Cloud Storage. Gemini's text-embedding-004 API generates 768-dimensional vector embeddings on the fly, while BigQuery executes cosine distance queries directly against the Parquet files, returning ranked results in 0.3 to 0.5 seconds. Each search result retains the original Google Drive file ID, enabling one-click navigation back to the live collaborative document. The approach is presented as a zero-maintenance, zero-subscription alternative to conventional RAG pipelines, avoiding vendor lock-in while keeping embeddings within core analytical storage.

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ProgrammingDEV Community ·

How VSporte Replaced vMix-Based Broadcast Graphics With a Web-Overlay System

VSporte, a sports broadcasting software company, spent several years migrating its on-air graphics workflow away from vMix's proprietary title system after hitting consistent performance ceilings. The original setup stored graphics as gtzip files inside vMix, requiring manual data entry for each match and growing memory usage as client template packs expanded to 20–50 elements. vMix's own documentation warns against exceeding 20 open templates and notes that a single animated intro can consume nearly 2.5 GB of graphics memory, limits VSporte regularly breached. The engineering team's solution was to build a proprietary graphics control platform that renders overlays as web pages fed into vMix as an input layer, keeping vMix as the final mixer while removing graphics from its memory footprint entirely. According to the company's lead architect, each fix in the multi-step migration exposed a new bottleneck, making the process incremental rather than a single overhaul.

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