vBrownBag

vBrownBag
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vBrownBag.com is a community of people who believe in helping other people. Specifically we work in IT infrastructure and we help other people in the IT industry to better their careers through education. Most frequent activity is producing the vBrownBag podcast. vBrownBag also attends global conferences to produce TechTalks and theater sessions.

  1. 3D AGO · VIDEO

    Troubleshooting AWS Hallucinations from Vector Store DBs

    Join us as Amelia shares the debugging story nobody tells you about - how her vector store DB couldn't surface specific data until she tested it with simplified data from ChatGPT. Amelia walks through her journey from throwing JIRA tickets into a large language model without understanding pipelines or data cleaning, to discovering why her production vector store was failing. You'll learn about the gap between chatting with data and getting accurate connections, how to validate vector similarity search results, the difference between production and synthetic test data, and practical troubleshooting workflows for AWS vector stores. This episode reveals the messy reality of RAG systems - when everything seems fine but the outputs are subtly wrong, and how testing with simplified data can expose what production complexity hides. Timestamps 0:00 Cold Open 1:03 Welcome & Introduction 2:06 Amelia's Background & DeepRacer Trophy 4:49 The JIRA Ticket Use Case Origin Story 5:53 Getting Into the Presentation 6:03 Accessing & Cleaning Data Sets 8:12 Losing Production Data & Recreating with ChatGPT 12:45 Understanding Vector Databases 18:22 How Embeddings Work 24:16 The Hallucination Discovery 30:41 Testing Strategies for Vector Stores 36:52 Debugging Vector Similarity Search 42:18 Real-World Troubleshooting Workflows 44:26 Where to Find Amelia & Wrap-up How to find Amelia: https://www.linkedin.com/in/ameliahoughross/

    48 min

  2. FEB 27 · VIDEO

    AI Agents Made Simple: Everything You Need to Know

    Join us as Du'An breaks down AI agents in a way that actually makes sense - what they are, how to use them, and how to get started today. Du'An walks through the fundamentals of AI agents with live demos and practical code examples you can use immediately. You'll learn about agent frameworks, when to use agents versus simple LLM calls, building your first agent, and real-world applications from bookmark management to automated workflows. This episode cuts through the hype with realistic expectations about what agents can and can't do, while showing you concrete examples including MCP servers, Strands Pack, and Du'An's personal second brain system. Timestamps 0:00 Welcome & Introduction 1:39 Du'An's Background & Previous Episode Success 3:06 Segueing from Last Week's Episode 4:03 CEOs Vibe Coding Discussion 6:49 Real Estate Developer Building Apps Story 8:23 Getting Started with the Presentation 12:45 What Are AI Agents? 18:22 Agent Frameworks Overview 24:16 When to Use Agents vs Simple LLM Calls 30:41 Building Your First Agent 36:52 Live Demo: Strands Pack 42:18 MCP Servers Explained 47:35 WriteStats MCP Demo 52:14 Real-World Applications 58:33 Du'An's Second Brain System 1:04:01 Bookmark Manager Walkthrough 1:07:17 Organizing Cloud Storage & Email 1:09:06 Wrap-up & Next Episode Teaser How to find Du'An: https://www.duanlightfoot.com/ https://github.com/labeveryday/ Links from the show: https://github.com/labeveryday/strands-pack https://github.com/labeveryday/writestat-mcp https://github.com/labeveryday/bookmark-manager-site https://bookmarks.duanlightfoot.com/ https://github.com/openai/whisper https://openai.com/index/whisper/

    1h 9m

  3. FEB 20 · VIDEO

    This is Fine: Tech Employment in the AI Era

    Join us as Chris gets brutally honest about tech employment in the AI era: what's dying, what's thriving, and how to position yourself to survive the chaos. Chris walks through the current state of tech layoffs hitting record numbers while companies post record profits, the disappearance of entry-level roles, and practical strategies for navigating this unprecedented moment. You'll learn about skill development in the AI era, why fundamentals still matter more than hype, how to build resilience through community, and what hiring managers are actually looking for right now. This episode doesn't sugarcoat the challenges from hollowed-out expertise at major companies to early-career professionals wondering if their degree still matters, but it also provides actionable guidance on positioning yourself and why humor and human connection remain irreplaceable in an AI-driven world. Timestamps 0:00 Welcome & Setting the Tone 3:09 Chris Miller's Background & Journey 7:30 The Current State of Tech Employment 12:45 Layoffs vs Record Profits Discussion 18:22 Entry-Level Roles Disappearing 24:16 What Skills Actually Matter Now 30:41 Building Career Resilience 36:52 The Fundamentals Still Win 42:18 Community & Support Networks 47:35 Practical Job Search Strategies 52:14 What AI Can't Replace (Yet) 55:06 Things We're Thankful For 59:00 Wrap-up & Resources How to find Chris: https://www.linkedin.com/in/chris-t-miller/ https://www.chrismiller.com/ Links from the show: https://roadmap.sh

  4. FEB 16 · VIDEO

    AI Governance for Virtualized Infrastructure: What vSphere Admins Need to Know

    Join us as Marian explains what AI governance means for vSphere administrators and why it matters now. Marian walks through practical governance frameworks that vSphere admins need to understand, from IEEE 7000 series standards to mapping governance controls onto infrastructure you already manage. You'll learn what your CISO will ask for, how to respond using your existing VMware stack, and why governance isn't about slowing innovation - it's about enabling it safely. This episode covers real-world scenarios from data lineage and model transparency to integrating governance tools with existing infrastructure, and addresses the gap between compliance requirements and practical implementation for virtualized environments. Timestamps 0:00 Welcome & Introduction 5:16 Marian's Background in Tech & Governance 6:37 What is Governance? 12:45 IEEE 7000 Series Standards Overview 18:22 AI Governance for vSphere Admins 24:16 Data Lineage & Model Transparency 30:41 Risk Assessment Frameworks 36:52 Practical Implementation Strategies 42:18 Integration with Existing Tools 47:35 Common Governance Challenges 51:12 Vendor Landscape Discussion 54:27 Missing Innovation in the Space 58:09 Wrap-up & Resources How to find Marian: https://www.linkedin.com/in/mariannewsome/ Links from the show: https://ethicaltechmatters.com/

    59 min

  5. FEB 12 · VIDEO

    FinOps - What It Is & Why It Matters

    Join us as Peter explores the core principles and practices of FinOps that help organizations optimize cloud spend without slowing innovation. Peter walks through what FinOps really is, why it matters beyond just cost cutting, and how engineers can collaborate effectively with finance teams to design cost-aware architectures. You'll learn about the three phases of FinOps (Inform, Optimize, Operate), how to get leadership buy-in for cloud initiatives, and practical strategies for managing cloud costs from the architecture phase through operations. This episode covers real-world scenarios from hybrid cloud cost tracking to building cost models before migrations, and explains how FinOps fits into your existing team structure regardless of organization size. Timestamps 0:00 Welcome & Introduction 6:10 Peter's Background & Journey to FinOps 10:45 What is FinOps? 16:32 The Three Phases: Inform, Optimize, Operate 22:18 Getting Leadership Buy-In 28:45 Cost-Aware Architecture Design 34:20 Hybrid Cloud & On-Prem Cost Tracking 40:15 FinOps Team Structure & Roles 46:30 Tools & Platforms Discussion 52:14 Accounting & Finance Collaboration 54:13 Starting FinOps Before Cloud Migration 57:17 FinOps for Small Teams & DBAs 1:00:13 Wrap-up & Resources How to find Peter: https://www.linkedin.com/in/petercrenshaw/ Links from the show: https://finops.org https://finopsweekly.com https://thefrugalarchitect.com

    1h 1m

  6. FEB 1 · VIDEO

    Observability 2.0 - More Than Just Logs, Metrics & Traces

    Join us as Neel explores how observability is evolving beyond traditional logs, metrics, and traces into a predictive, AI-powered discipline. Neel walks through the evolution of Observability, demonstrating how OpenTelemetry, machine learning, and LLMs are transforming how we monitor and maintain modern applications. You'll learn about dynamic sampling techniques that reduce costs while maintaining visibility, how ML algorithms detect anomalies before they cause outages, and practical implementations using tools like the OpenTelemetry Collector. This episode covers real-world scenarios from reducing massive log volumes to predicting system failures before they impact customers. Timestamps 0:00 Welcome & Introduction 4:29 Neel's Background & Community Work 5:03 The Evolution of Observability 6:29 The 2 AM Production Incident Scenario 8:13 OpenTelemetry's Role in Modern Observability 12:45 Dynamic Sampling Techniques 18:22 ML & AI in Anomaly Detection 24:16 LLM Observability Explained 28:32 Cost Optimization Strategies 30:04 Context Windows & Token Management 32:00 Self-Healing Systems Discussion 34:15 Edge Cases: When Dynamic Sampling Doesn't Work 36:27 Wrap-up & Resources How to find Neel: https://www.linkedin.com/in/neelcshah/ https://bento.me/neelshah Links from the show: https://neelshah.dev/blogs/observability-2 https://opentelemetry.io/ https://middleware.io/blog/observability-2-0/

    38 min

  7. JAN 24 · VIDEO

    Teaching AI to Terraform (So We Don't Have To)

    Join us as Sam demonstrates how to teach AI to write Terraform configurations using Model Context Protocol (MCP) servers. Sam introduces the Terraform MCP server and walks through practical demos showing how AI can understand and safely interact with your infrastructure. You'll see live examples of AI planning, generating, and evolving Terraform configurations - from creating landing zones to setting up workspace variables automatically. Whether you're managing complex multi-cloud environments or just getting started with infrastructure as code, this episode demonstrates how MCP servers bridge the gap between AI capabilities and real-world Terraform workflows. Learn how to get started, which Claude models work best for different tasks, and best practices for integrating AI into your IaC pipelines. Timestamps 0:00 Welcome & Introduction 4:37 Sam McGeown's Background 6:02 Introduction to Terraform MCP Server 12:35 What is Model Context Protocol? 18:22 Setting Up the Terraform MCP Server 24:16 Demo: Claude Desktop Integration 30:41 Creating Infrastructure with AI Prompts 36:52 Reading & Analyzing Existing Terraform Code 42:18 Generating Landing Zone Configurations 47:35 Working with Terraform Workspaces 50:37 Creating Variables Automatically 52:14 Model Selection: Sonnet vs Opus 55:11 Live Demo: Workspace Variable Creation 58:33 Getting Started & Resources How to find Sam: https://www.linkedin.com/in/sammcgeown/ Links from the show: https://developer.hashicorp.com/terraform/mcp-server

    1 hr

  8. JAN 23 · VIDEO

    Evolution of Tool Use and MCP in Generative AI

    Join us as Gautam breaks down the evolution of tool use in generative AI and dives deep into MCP. Gautam walks through the progression from simple prompt engineering to function calling, structured outputs, and now MCP—explaining why MCP matters and how it's changing the way AI systems interact with external tools and data. You'll learn about the differences between MCP and traditional API integrations, how to build your first MCP server, best practices for implementation, and where the ecosystem is heading. Whether you're building AI-powered applications, integrating AI into your infrastructure workflows, or just trying to keep up with the latest developments, this episode provides the practical knowledge you need. Gautam also shares real-world examples and discusses the competitive landscape between various AI workflow approaches. Subscribe to vBrownBag for weekly tech education covering AI, cloud, DevOps, and more! ⸻ Timestamps 0:00 Introduction & Welcome 7:28 Gautam's Background & Journey to AI Product Management 12:45 The Evolution of Tool Use in AI 18:32 What is Model Context Protocol (MCP)? 24:16 MCP vs Traditional API Integrations 30:41 Building Your First MCP Server 36:52 MCP Server Discovery & Architecture 42:18 Real-World Use Cases & Examples 47:35 Best Practices & Implementation Tips 51:12 The Competitive Landscape: Skills, Extensions, & More 52:14 Q&A: AI Agents & Infrastructure Predictions 55:09 Closing & Giveaway How to find Gautam: https://gautambaghel.com/ https://www.linkedin.com/in/gautambaghel/ Links from the show: https://www.hashicorp.com/en/blog/build-secure-ai-driven-workflows-with-new-terraform-and-vault-mcp-servers Presentation from HashiConf: https://youtu.be/eamE18_WrW0?si=9AJ9HUBOy7-HlQOK Kiro Powers: https://www.hashicorp.com/en/blog/hashicorp-is-a-kiro-powers-launch-partner Slides: https://docs.google.com/presentation/d/11dZZUO2w7ObjwYtf1At4WnL-ZPW1QyaWnNjzSQKQEe0/edit?usp=sharing

    58 min
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Ratings & Reviews

4.7
out of 5
34 Ratings

About

vBrownBag.com is a community of people who believe in helping other people. Specifically we work in IT infrastructure and we help other people in the IT industry to better their careers through education. Most frequent activity is producing the vBrownBag podcast. vBrownBag also attends global conferences to produce TechTalks and theater sessions.

Information

  • Creator
    vBrownBag
  • Years Active
    2011 - 2026
  • Episodes
    77
  • Rating
    Clean
  • Show Website
    vBrownBag