Scalable BullMQ Queue with Redis for Node.js (2026)
Build a BullMQ task queue with Redis in Node.js, enabling horizontal worker scaling, automatic retries, and real‑time monitoring for reliable background jobs.
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’m Nilesh, a Software Development Engineer with 2+ years of experience, specializing in Go, JavaScript, Python, Docker, Kubernetes, Git, Jenkins, microservices, and system design (LLD/HLD), backed by a strong foundation in data structures and algorithms. Alongside my engineering journey, I bring 4+ years of hands-on experience in SEO, where I’ve worked extensively on content strategy, keyword research, technical SEO, and organic growth, helping products and businesses scale efficiently by aligning solid technology with search-driven performance.
336 articles
Build a BullMQ task queue with Redis in Node.js, enabling horizontal worker scaling, automatic retries, and real‑time monitoring for reliable background jobs.
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💡 Pro Tip: Skipping observability until after your AI agent goes live usually ends with painful firefighting sessions. TL;DR Start simple: Add a correlation…
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TL;DR – 5 Takeaways – Pgpool‑II sits between your app and PostgreSQL, handling connection pooling, read/write split, and HA failover. – The Watchdog process…
⚡ Hook: When the checkout page of a fast‑growing e‑commerce site suddenly returned “Service Unavailable” after a weekend spike, the ops team traced the…
⚡ Opening Hook During a Black Friday sale, the e‑commerce platform nileshblog.tech saw traffic soar to 120 k RPS. Within seconds, its customer‑facing services returned 502…
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A clear, jargon-free explainer on multi-agent AI systems: how specialized agents coordinate, the three core architecture patterns, MCP vs A2A protocols, and when not…
A complete, beginner-friendly guide to calling the Claude API from Node.js — SDK setup, your first request, streaming, multi-turn chat, error handling, and an…
⚡ Opening Hook A fresh deployment of a Flask‑based order service went live at 02:13 AM. Within minutes the e‑commerce checkout stalled, customers saw “Service…
TL;DR – Quick Takeaways Keep Assistant threads short when possible; long‑lived threads inflate token counts. Cache recurring prompts and reuse completions to cut per‑call…
⚡️ TL;DR – Treat secrets as short‑lived, rotating assets and never store them plaintext in git or container images. – Pick a single source‑of‑truth…