Celery on ECS: Separate Container Architecture
A visual deep-dive into running Celery workers as separate ECS containers — broker topology, task lifecycle, concurrency models, and the Beat scheduler gotcha.
I build production AI products from 0 to 1: Stella at Ourself Health and KiNDD / NDD Resource Navigator. My work spans scalable Django/Python backends, AWS Bedrock, Strands agents, Langfuse observability/evals, RAG pipelines, cost-aware model routing, GraphQL APIs, Flutter-connected mobile platforms, and the operational details that make AI products dependable after launch.
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A visual deep-dive into running Celery workers as separate ECS containers — broker topology, task lifecycle, concurrency models, and the Beat scheduler gotcha.
I have 268 markdown files in my Obsidian vault – internal docs, architecture decisions, API specs, meeting notes. Searching them with Obsidian’s built-in sea...
Part 4 of building the AI assistant. This covers the most critical issue in health AI: preventing the model from making up data that doesn’t exist.
Part 3 of the series on building a women’s health AI assistant. This covers the system prompts, safety guardrails, and behavior control that make an AI agent...
This is the first in a series documenting how I built a women’s health AI assistant using AWS Strands SDK, Bedrock, and Django. The system handles personal h...
If you’re building multi-user AI agents with AWS Strands SDK, you’ll quickly hit a common problem: how do you bind tools to a specific user without passing u...