Tools Resources

I Built a RAG Agent on Azure AI Foundry in an Afternoon. Here's What Nobody Tells You.

Azure AI Foundry turns RAG setup from a week of manual plumbing into an afternoon of configuration — but access control, security, and cost planning are still on you.

July 30, 2026

by Balaji Venkatasubramaniyar

· 1,962 Views · 1 Like

Coordinating AI Agents With AWS SQS: A Practical Queue-Based Architecture

AWS SQS helps multi-agent AI workflows handle retries, duplicates, and repeated failures with queues, idempotency, and DLQs.

July 30, 2026

by Lucas Yoon

· 2,400 Views · 3 Likes

Build Your Own Local AI QA Engineer With Docker, Ollama, LibreChat, and Playwright MCP

Learn how to build a completely local AI-powered QA Automation Engineer using Docker, Ollama, Qwen3:8b, LibreChat, and Playwright MCP.

July 30, 2026

by Faisal Khatri

CORE

· 8,009 Views

What Nobody Tells You About Running AI Models in Docker

At 2 am, a bloated 14GB Docker image with baked-in weights crashed our inference service; externalizing weights and rethinking GPU isolation fixed it.

July 29, 2026

by Pruthvi Raj Seknametla

· 34,478 Views · 2 Likes

The Lethal Trifecta Is Hiding in Your MCP Server

MCP makes it trivial to give an agent the "lethal trifecta," so one poisoned input can leak your secrets. Prompts can't stop it; a deterministic broker can.

July 29, 2026

by Veera Ravindra DIVI

· 2,126 Views

From Idle Infrastructure to Elastic Capacity: Rethinking Kubernetes Scaling

As Kubernetes deployments expand across hybrid and multicloud environments, permanently provisioned infrastructure becomes an expensive default. Here's how scale-from-zero aligns capacity with actual demand instead of worst-case scenarios.

July 28, 2026

by DZone Staff

· 11,884 Views · 1 Like

Building a Voice-Controlled Graph Assistant With Neo4j, LiveKit, and OpenAI

Build a voice assistant that lets you ask natural-language questions to a Neo4j graph database and hear the answers spoken back.

July 27, 2026

by Akmal Chaudhri

CORE

· 2,618 Views

From APIs to Agents: How Back-End Engineering is Evolving in 2026

Back-end engineering is moving from static APIs to autonomous, AI-driven agents that can plan, decide, and act—not just respond to requests.

July 24, 2026

by Nathan Smith

· 2,588 Views · 1 Like

How Agentic AI Is Turning Traditional Automation Into a Tool Layer?

Agentic AI doesn’t replace traditional automation. It uses existing workflows, APIs, and systems as tools while handling decisions, exceptions, and complex tasks.

July 22, 2026

by Sagar Sahay Bhatnagar

· 3,245 Views

Search Is Becoming the Control Plane for AI Agents

The future of AI agents is searchable tool discovery, not hardcoded APIs. MCP and semantic search are turning tools into capabilities agents can find and use at runtime.

July 21, 2026

by sunil paidi

· 2,172 Views

The Agent Security Split: Tool Layer vs Sandbox Layer

Why enterprise agent security requires decoupling the tool layer from the sandbox layer, and how the helmdeck + NVIDIA OpenShell architecture enforces it.

July 20, 2026

by Tosin Akinosho

· 1,776 Views

Your AI Agent Trusts Every Tool It's Ever Been Introduced To; That's the Whole Problem

Learn about the 2026 MCP security crisis and a capability provenance architecture that detects tool drift, blocks attacks, and strengthens AI agent security.

July 16, 2026

by Igboanugo David Ugochukwu

CORE

· 2,754 Views · 1 Like

Agents, Tools, and MCP: A Mental Model That Actually Helps

Why more layers doesn't mean a better AI system, and how to think about agents, tools, memory, and MCP as building blocks you actually control.

July 15, 2026

by Jennifer Reif

CORE

· 3,999 Views · 2 Likes

GraphRAG in Practice Using Spring AI, Neo4j, and Goodreads Data

Building a GraphRAG application with Spring AI and Neo4j, covering data modeling, Cypher-based data loading, vector search, and key gotchas.

July 14, 2026

by Akmal Chaudhri

CORE

· 5,896 Views · 3 Likes

AWS Glue ETL Design Principles for Production PySpark Pipelines

Learn eight AWS Glue ETL design principles for building production PySpark pipelines that are maintainable, scalable, observable, and cost-efficient.

July 14, 2026

by Janani Annur Thiruvengadam

CORE

· 3,500 Views · 2 Likes

From Bash Script to Operational Triage: What Eight Months of Kubernetes Debugging Taught Me

Finding Kubernetes failures is easy. Knowing where to start is the hard part. Here's what eight months of building taught me.

July 9, 2026

by Shamsher Khan

CORE

· 2,337 Views

Azure Databricks vs Microsoft Fabric: An Honest Guide to When to Use What

Azure Databricks and Microsoft Fabric overlap, but they're built for different priorities. Databricks for data engineering, ML, open-source, and Spark workloads.

July 9, 2026

by Jubin Soni, FBCS

CORE

· 1,968 Views

Designing Tool-Calling AI Agents That Survive Production: A LangGraph Approach

AI agents work in demos and break into production. This LangGraph tutorial builds tool-calling agents that are fail-safe: validated, bounded, and observable.

July 7, 2026

by Shubham Gupta

· 1,995 Views

Azure Databricks for Scalable MLOps and Feature Engineering With Apache Spark, Delta Lake, and MLflow

A practical guide to feature engineering at scale with Azure Databricks, covering distributed data processing with Spark and reliable storage with Delta Lake.

July 6, 2026

by Jubin Soni, FBCS

CORE

· 1,384 Views

Building an AI Agent That Responds to Real-Time Events With AWS Bedrock, Kinesis, DynamoDB, and S3

Build an AI agent that processes real-time events with Amazon Bedrock and a serverless AWS architecture powered by Kinesis, DynamoDB, and S3.

July 3, 2026

by Jubin Soni, FBCS

CORE

· 2,287 Views · 1 Like

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