Tutorials ASP.NET Core with Agentic AI Tutorial

AI Queue Systems — Complete Guide

AI Queue Systems — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of ASP.NET Core with Agentic AI Tutorial on Toolliyo Academy.

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ASP.NET Core with Agentic AI Tutorial · Lesson 85 of 100

AI Queue Systems

AI basics ✓Agents

Agents · 2 — Build · ~10 min · Module 9: AI System Design and Architecture

What is this?

AI queue systems buffer heavy or retryable agent work — bulk enrich, reindex, nightly briefs. AgentNest uses Azure Service Bus queues with visibility timeout and dead-letter.

Why should you care?

API must not run 10-minute ERP reconciliation synchronously; queues smooth load and survive transient OpenAI 429.

See it live — copy this example

Paste into an ASP.NET Core 8+ / AgentNest project, then run with dotnet run (set your API keys in user-secrets).

// AgentNest.Queues/AgentJobPublisher.cs
public sealed class AgentJobPublisher(ServiceBusSender sender)
{
    public Task EnqueueAsync(AgentJob job, CancellationToken ct) =>
        sender.SendMessageAsync(new ServiceBusMessage(JsonSerializer.Serialize(job))
        {
            MessageId = job.IdempotencyKey,
            Subject = job.AgentName
        }, ct);
}

What happened?

  • AgentJobPublisher sends serialized jobs with idempotency MessageId so duplicate CRM webhooks do not double-enrich leads.
  • Follow the steps below — typing the code yourself is the fastest way to learn.

Practice next

  1. Create queue agentnest-jobs with dead-letter subqueue.
  2. build AgentJobWorker hosted service with peek-lock.
  3. Complete message only after agent success; abandon on retryable errors.
  4. Priority subqueues for hospital vs CRM jobs.
  5. Schedule delayed messages for off-peak ERP batches.

Remember

Offload long agent work to Service Bus queues. Use MessageId idempotency and peek-lock processing. Monitor dead-letter queue for poison jobs.

Bulk lead enrichment

Marketing imports 50k leads; API enqueues jobs instead of timing out.

Outcome: Workers process overnight; CRM UI shows progress from queue depth metric.

Interview prep for this lesson

Practice these questions aloud after reading—each links to a full structured answer.

Junior Detailed
Explain Concepts in the context of ASP.NET Core with Agentic AI.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Concepts…
Mid Detailed
What are common mistakes teams make with LLMs when using ASP.NET Core with Agentic AI?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define LLMs in p…
Senior Detailed
How would you debug a production issue related to RAG in a ASP.NET Core with Agentic AI application?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define RAG in pl…
Junior Detailed
Describe a real-world scenario where Production mattered in a ASP.NET Core with Agentic AI project.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. Explain a bit more How to structure your answer (60–90 seconds) Define Productio…
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ASP.NET Core with Agentic AI Tutorial
Course syllabus

ASP.NET Core with Agentic AI Tutorial

Module 1: AI and Agentic AI Foundations
Module 2: ASP.NET Core AI Fundamentals
Module 3: Semantic Kernel
Module 4: AI Agents and Multi-Agent Systems
Module 5: RAG and Vector Databases
Module 6: AI Security and Observability
Module 7: Cloud-Native AI and DevOps
Module 8: AI SaaS and Enterprise Systems
Module 9: AI System Design and Architecture
Module 10: Enterprise AI Projects
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