Many customers have relied on SQL Server for over 3 decades to run their mission critical business applications. As these customers get ready to modernize their data to use the latest capabilities of A.I and cloud native application trends, they want to migrate and modernize their applications and SQL Servers to use Azure SQL. This is also an excellent opportunity for many of the SQL Solution partners to help their clients with modernization. But it is critical to understand the important technical considerations before, during and after data modernization or it could have long term higher costs and operational concerns. The SQL Team has helped many customers modernize their SQL. In this episode, Anna and Dhananjay share the top 3 reasons customers that have stalled Enterprise SQL Server modernization. They cover best practices that can help you avoid costly mistakes to implement on Day 1 after the data migration to Azure is done to get the best of running SQL in Azure

✅ Resources:
Azure Database Migration Guides | Microsoft Learn

SQL Server to Azure SQL Database: Migration Overview | Microsoft Learn

SQL Server to Azure SQL Database: Migration Guide | Microsoft Learn

SQL Server to SQL Server on Azure Virtual Machines: Migration Guide - SQL Server on Azure VMs | Mic…

Generally Available: Azure SQL Managed Instance Next-gen General Purpose | Microsoft Community Hub

SQL Server Blog | Microsoft Community Hub

Azure SQL documentation - Azure SQL | Microsoft Learn

📌 Let's connect:
Twitter - Anna Hoffman, https://twitter.com/AnalyticAnna
Twitter - AzureSQL, https://aka.ms/azuresqltw

🔴 Watch even more Data Exposed episodes: https://aka.ms/dataexposedyt

🔔 Subscribe to our channels for even more SQL tips:
Microsoft Azure SQL: https://aka.ms/msazuresqlyt
Microsoft SQL Server: https://aka.ms/mssqlserveryt
Microsoft Developer: https://aka.ms/microsoftdeveloperyt

#AzureSQL #SQL #LearnSQL

Version control for game dev is messier than for regular software. You've got binary assets that can't be merged, artists who want file locking, and developers who want to move fast. Those two worlds don't naturally get along.

Andy and Stacey dig into how version control actually works in game studios, walk through setting up git for a real Godot project in the terminal, and cover Git LFS, the piece that makes git viable when your repo is full of textures, audio, and 3D models.

🚀 What You'll Learn
• How centralized (SVN/Perforce) and distributed (git) version control differ
• How Git LFS handles binary assets: pointer files, separate storage, and reduced local repo size.
• How file locking works in Git LFS and why it matters for game assets.
• Git fundamentals in the terminal: init, add, commit, push, pull, branching, and merge conflicts.
• Best practices for Unity and Godot projects: scene structure, .gitignore, commit hygiene, and keeping your main branch stable.

⏱️Chapters
00:00:00 Intro
00:01:35 Centralized vs. distributed
00:08:31 Creating a repo on GitHub
00:14:49 Setting up git in the terminal
00:23:18 Branching
00:34:59 Merge conflicts
00:38:45 Git LFS for binary assets
00:48:29 Best practices

🔗 Links & Resources
Git — https://git-scm.com
Git LFS — https://git-lfs.com
GitHub — https://github.com
Godot C# Essentials series — https://youtu.be/0Pf41YBedMk

📺 Watch the full series: https://aka.ms/Quest-to-Compile

#git #GameDev #VersionControl
#GameDevelopment #gitlfs #GitTutorial #GodotEngine #Unity3d #GitForGameDev #Perforce #SVNvsGit #DevOps #GameDevWorkflow #IndieGameDev #SoftwareEngineering

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youtube.com/@staceyhaffner
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Join us for another episode of Sip N’ Sync with Azure ☕🎤 as we explore how AI is transforming DevOps end-to-end.

Host Priyanka Vergadia welcomes David Sanchez, Director in the Developer Go-To-Market team, to walk through a real-world demo of AI-infused DevOps (aka Agentic DevOps). From planning and coding to CI/CD, testing, security, and production monitoring—see how AI agents and GitHub Copilot are reshaping every stage of the lifecycle.

🚀 You’ll see:
- AI-powered code generation and review
- Automated CI/CD workflows across environments
- GitHub Advanced Security in action
- Custom DevOps agents and task delegation
- End-to-end deployment with QA validation and load testing

Whether you're a DevOps engineer, developer, or architect, this episode shows how to build faster, safer, and smarter pipelines with AI.

Chapters:
00:04 - Welcome to Sip N’ Sync: AI in DevOps
00:49 - Meet David Sanchez + Agentic DevOps Overview
02:18 - Demo App: Secret Gift Exchange Web App
03:57 - Exploring the GitHub Repo & CI/CD Workflows
05:12 - Pull Requests, AI Code Reviews & Deployments
06:58 - End-to-End CI/CD: QA, Testing & Load Validation
08:04 - Human-in-the-Loop Deployment Approval
09:20 - AI Agents for DevOps Tasks (Custom Agent Roles)
11:00 - Improving CI/CD with DevOps AI Agents
13:22 - Code Quality & Security with GitHub Advanced Security
15:54 - Secret Scanning & Protecting Sensitive Data
17:12 - Why Security & Quality Matter in AI-Driven DevOps
17:42 - Wrap-Up & Resources

Resources
🚀 Sample Repo (DevOps Engineer Persona)
https://github.com/azure-samples/devopsengineerpersona

Explore the full demo application and workflows:
👉 https://github.com/Azure-Samples

🔍 GitHub Copilot
AI-powered coding, reviews, and automation:
👉 https://github.com/features/copilot

⚡ GitHub Advanced Security
CodeQL, secret scanning, and security insights:
👉 https://github.com/security/advanced-security

🎯 Azure DevOps & CI/CD
Build and deploy pipelines with Azure:
👉 https://learn.microsoft.com/azure/devops

📊 Azure Load Testing
Validate performance at scale:
👉 https://learn.microsoft.com/azure/load-testing

🧠 Azure AI + DevOps
Learn how AI integrates across the lifecycle:
👉 https://learn.microsoft.com/azure/architecture/ai-ml/

💡 Try Azure for Free
👉 https://aka.ms/AzureFreeTrialYT

📺 Watch More Sip N’ Sync Episodes
👉 https://aka.ms/SipAndSyncPlaylist

🔔 Subscribe for more Azure & DevOps content!

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