Model Mondays S2E13: Open Source Models (Hugging Face)
1. Weekly Highlights 1. Weekly Highlights Here are the key updates we covered in the Season 2 finale: O1 Mini Reinforcement Fine-Tuning (GA): Fine-tune models with as few as ~100 samples using built-in Python code graders. Azure Live Interpreter API (Preview): Real-time speech-to-speech translation supporting 76 input languages and 143 locales with near human-level latency. Agent Factory – Part 5: Connecting agents using open standards like MCP (Model Context Protocol) and A2A (Agent-to-Agent protocol). Ask Ralph by Ralph Lauren: A retail example of agentic AI for conversational styling assistance, built on Azure OpenAI and Foundry’s agentic toolset. VS Code August Release: Brings auto-model selection, stronger safety guards for sensitive edits, and improved agent workflows through new agents.md support. 2. Spotlight – Open Source Models in Azure AI Foundry Guest: Jeff Boudier, VP of Product at Hugging Face Jeff showcased the deep integration between the Hugging Face community and Azure AI Foundry, where developers can access over 10 000 open-source models across multiple modalities—LLMs, speech recognition, computer vision, and even specialized domains like protein modeling and robotics. Demo Highlights Discover models through Azure AI Foundry’s task-based catalog filters. Deploy directly from Hugging Face Hub to Azure with one-click deployment. Explore Use Cases such as multilingual speech recognition and vision-language-action models for robotics. Jeff also highlighted notable models, including: SmoLM3 – a 3 B-parameter model with hybrid reasoning capabilities Qwen 3 Coder – a mixture-of-experts model optimized for coding tasks Parakeet ASR – multilingual speech recognition Microsoft Research protein-modeling collection MAGMA – a vision-language-action model for robotics Integration extends beyond deployment to programmatic access through the Azure CLI and Python SDKs, plus local development via new VS Code extensions. 3. Customer Story – DraftWise (BUILD 2025 Segment) The finale featured a customer spotlight on DraftWise, where CEO James Ding shared how the company accelerates contract drafting with Azure AI Foundry. Problem Legal contract drafting is time-consuming and error-prone. Solution DraftWise uses Azure AI Foundry to fine-tune Hugging Face language models on legal data, generating contract drafts and redline suggestions. Impact Faster drafting cycles and higher consistency Easy model management and deployment with Foundry’s secure workflows Transparent evaluation for legal compliance 4. Community Story – Hugging Face & Microsoft The episode also celebrated the ongoing collaboration between Hugging Face and Microsoft and the impact of open-source AI on the global developer ecosystem. Community Benefits Access to State-of-the-Art Models without licensing barriers Transparent Performance through public leaderboards and benchmarks Rapid Innovation as improvements and bug fixes spread quickly Education & Empowerment via tutorials, docs, and active forums Responsible AI Practices encouraged through community oversight 5. Key Takeaways Open Source AI Is Here to Stay Azure AI Foundry and Hugging Face make deploying, fine-tuning, and benchmarking open models easier than ever. Community Drives Innovation: Collaboration accelerates progress, improves transparency, and makes AI accessible to everyone. Responsible AI and Transparency: Open-source models come with clear documentation, licensing, and community-driven best practices. Easy Deployment & Customization: Azure AI Foundry lets you deploy, automate, and customize open models from a single, unified platform. Learn, Build, Share: The open-model ecosystem is a great place for students, developers, and researchers to learn, build, and share their work. Sharda's Tips: How I Wrote This Blog For this final recap, I focused on capturing the energy of the open source AI movement and the practical impact of Hugging Face and Azure AI Foundry collaboration. I watched the livestream, took notes on the demos and interviews, and linked directly to official resources for models, docs, and community sites. Here’s my Copilot prompt for this episode: "Generate a technical blog post for Model Mondays S2E13 based on the transcript and episode details. Focus on open source models, Hugging Face, Azure AI Foundry, and community workflows. Include practical links and actionable insights for developers and students! Learn & Connect Explore Open Models in Azure AI Foundry Hugging Face Leaderboard Responsible AI in Azure Machine Learning Llama-3 by Meta Hugging Face Community Azure AI Documentation About Model Mondays Model Mondays is your weekly Azure AI learning series: 5-Minute Highlights: Latest AI news and product updates 15-Minute Spotlight: Demos and deep dives with product teams 30-Minute AMA Fridays: Ask anything in Discord or the forum Start building: Watch Past Replays Register For AMA Recap Past AMAs Join The Community Don’t build alone! The Azure AI Developer Community is here for real-time chats, events, and support: Join the Discord Explore the Forum About Me I'm Sharda, a Gold Microsoft Learn Student Ambassador focused on cloud and AI. Find me on GitHub, Dev.to, Tech Community, and LinkedIn. In this blog series, I share takeaways from each week’s Model Mondays livestream.August 2025 Recap: Azure Database for PostgreSQL
Here’s what’s new this month to help you build smarter and scale securely: Advisor performance tuning (GA): New insights on index scans, logging, stats, and connections Entra ID group login (Preview): Let users sign in with their own credentials (no need for login using group-ID). New region – Austria East: Lower latency + data residency options for Central Europe LangChain & LangGraph support: Use Azure PostgreSQL as a vector store for AI agents Active-active replication guide: Step-by-step walkthrough using pglogical Full details in monthly recap: https://techcommunity.microsoft.com/blog/adforpostgresql/august-2025-recap-azure-database-for-postgresql/4450527New ESG study validates how fully managed PostgreSQL on Azure delivers economic wins
Migrating your PostgreSQL databases to Azure delivers cost, performance and productivity benefits, while laying a strong foundation for innovation. But don’t just take our word for it. We’ve worked with the Enterprise Strategy Group (ESG), now a part of Omdia, to validate how organizations benefit economically from moving their PostgreSQL databases to Azure. Whether you’re modernizing your mission-critical applications or developing the next groundbreaking feature, migrating to Azure gives you the freedom, flexibility and continuous improvements of open source backed by the reliability, security and efficiency of Azure. Read the full PostgreSQL report PostgreSQL is the preferred choice of developers building the next generation of intelligent applications, according to the 2025 Stack Overflow survey. However, many teams are finding that managing these open-source databases on-premises is increasingly challenging, especially as their innovation initiatives demand more and more resources. Because of this, organizations are rapidly modernizing their database infrastructure to better support these next-gen initiatives. At a glance – benefits of migrating to Azure Database for PostgreSQL Increasing complexity is nothing new to today’s IT and developer teams. Some of the key drivers contributing to this complexity include integrating emerging tech like AI and managing cybersecurity concerns—two things that the fully managed Azure Database for PostgreSQL service handles very well. Built-in GenAI capabilities, performance recommendations, and enterprise-grade security, scalability, compliance and availability make PostgreSQL on Azure a natural fit for teams looking to build intelligent enterprise applications. The ESG report highlights: 58% lower total cost of ownership 65% improvement in database performance $770K in savings from avoiding downtime “We have seen wins on both sides of the financial equation. Our costs are down across the board, and we have increased our revenue specifically because of the capabilities that moving our Azure Database for PostgreSQL.” Review the Azure Database for PostgreSQL Economic Validation Infographic A closer look – how fully managed PostgreSQL on Azure delivers economic wins for the enterprise Lower total cost of ownership Migration dramatically lowers the total cost of ownership of enterprise databases. By shifting from on-premises infrastructure to Azure’s managed service, enterprises eliminate many capital and operational expenses. Elimination of hardware and maintenance costs: On-premises PostgreSQL deployments require investing in servers, storage, networking hardware, as well as ongoing power, cooling, and data center space. Migrating to Azure removes these needs entirely. Companies no longer have to purchase or refresh hardware or pay for associated facilities and utilities, directly cutting capex and support costs. Reduced licensing and support expenses: Azure’s model also eliminates traditional database licensing fees, third-party support contracts, and expensive monitoring tools for on-premises systems. Organizations reported saving thousands on separate support agreements or software licenses for their PostgreSQL instances. Pay-as-you-go flexibility: Azure Database for PostgreSQL offers pay-as-you-go and reserved pricing models, so enterprises only pay for the compute and storage they actually use. There’s no more overprovisioning resources to handle peak loads, and dynamic scaling ensures capacity matches demand. Operational efficiency: By offloading database management to Microsoft, organizations also reduce administrative overhead, which indirectly lowers labor costs. In ESG’s study, moving to Azure cut the monthly DBA hours per database from 2.1 hours to just 0.6 hours, a ~70% decrease in effort, effectively saving payroll expenditure on routine upkeep. Improved performance and scalability Enterprises see substantial improvements in database performance and scalability after migrating to Azure. Because Azure Database for PostgreSQL runs on high-end cloud infrastructure with intelligent optimizations, applications can achieve faster response times and handle greater workloads. Higher throughput and lower latency: ESG’s interviews found average database performance improved by ~65%, and in one case a customer saw a 9× increase in throughput for its primary application after migration. Such gains come from Azure’s optimized compute, premium SSD storage options, and features like automatic performance tuning that are difficult to replicate on-premises. Elastic scaling on demand: In on-premises environments, supporting peak workloads often meant overprovisioning. Azure Database for PostgreSQL completely changes this paradigm with cloud elasticity. The ability to instantly right-size resources means applications always have the performance they need, and users experience responsive, low-latency service. Handling growth with ease: As an enterprise’s data and user base grows, Azure’s global infrastructure can seamlessly accommodate that expansion. This cloud scalability gives enterprises headroom to innovate and onboard more customers without performance bottlenecks. In contrast, scaling an on-premises PostgreSQL often requires complex sharding or hardware upgrades. Accelerated time to value: Improved performance and scalability directly impact business agility. Batch processes complete faster, reports generate sooner, and websites or applications can serve more customers per second. ESG noted that by removing infrastructure constraints, Azure empowered businesses to accelerate their time-to-value and respond faster to market demands. Operational agility and developer productivity By migrating to a fully managed service, enterprises gain agility and allow their IT/development teams to focus on innovation. Offloading database management to Azure not only saves costs but also frees up technical staff from mundane maintenance. This shift translates into faster project delivery and greater productivity: Less time spent “keeping the lights on”: ESG found that after migration, companies saw a major reduction in the effort required to manage databases. Administrators went from spending 2+ hours per database per month on upkeep to less than one hour. This over 70% drop in DBA workload means IT teams are no longer bogged down by routine chores. Faster development and release cycles: ESG observed that organizations enjoyed increased development velocity after migrating, since their engineers could devote time to coding and testing new features instead of managing database infrastructure. For example, one company in the study was able to increase its software release frequency significantly. Improved business agility: The combination of easier scaling, better performance, and less ops overhead means the organization can respond to opportunities faster. Some enterprises even credited the move to Azure with helping increase their revenue, because it allowed them to deliver new capabilities to market sooner. Focus on core competencies: After migration, organizations can let Azure handle the heavy lifting of database administration and instead concentrate on work that differentiates them in the marketplace. Developers spend more time building applications and analyzing areas that drive business value rather than performing software updates or fixing replication issues. Enhanced security, compliance, and reliability Azure Database for PostgreSQL provides enterprise-grade security and reliability features that far exceed what most companies can achieve on-premises. This results in a stronger risk posture, reducing the likelihood of breaches or downtime while also easing compliance burdens. Built-in high availability and disaster recovery: ESG’s modeled scenario saw annual PostgreSQL downtime drop from 10 hours on-premises to just 5 hours on Azure. With a 99.99% availability SLA for Azure Database for PostgreSQL, unplanned outages that used to disrupt business are largely a thing of the past. One ESG case study estimated about $770K in costs were avoided thanks to preventing downtime and the associated business disruptions. Strong security and data protection: PostgreSQL instances on Azure benefit from Microsoft’s massive investments in cybersecurity and compliance. One customer highlighted, “We are much more secure since we moved to Azure Database for PostgreSQL. We use Azure AI to set our security standards and get constant recommendations on how to increase our security even more.” Automated updates and governance: Azure takes care of updating PostgreSQL with the latest security fixes and can even upgrade the database engine version with minimal downtime. Furthermore, features like audit logging, advanced threat protection, and integration with Azure Security Center provide continuous oversight of database activity. Geo-redundancy and backup management: For disaster recovery, Azure allows geo-redundant backups and read replicas in different regions, improving an enterprise’s resilience to regional outages or disasters. Should data restoration be needed, it’s as simple as clicking a button. Azure Database for PostgreSQL offers enterprises a frictionless path to greater efficiency, innovation, and growth. By lowering costs and management burdens, it lets you redirect resources to strategic projects. By boosting performance and scalability, it ensures your applications can keep up with business demands. And by enhancing security and reliability, it safeguards one of your most precious assets—your data—while meeting the strict requirements of enterprise IT. The benefits outlined in the ESG study make a strong business case: migrating on-premises databases to Azure’s managed PostgreSQL can transform your IT operations and deliver tangible business value from day one. Tested, approved, trusted Migrating to a fully managed PostgreSQL service supports digital transformation. It allows enterprises to modernize their data estate without abandoning the familiarity of PostgreSQL. Developers can continue using the open-source tools and skills they know, but now with cloud-powered capabilities at their fingertips. Azure integrations (with AI services, analytics tools, etc.) further enable organizations to do more with their data. For example, companies can readily infuse AI or machine learning into their applications or take advantage of advanced analytics on their PostgreSQL data, since that data is easily accessible in the cloud. Read the full report for more details about the quantified benefits and customer testimonials. If you’re ready to start your journey, check out our migration guides. With Azure’s fully managed PostgreSQL, you can supercharge your data strategy, empower your developers, and ultimately accelerate your path to an AI-driven future.June 2025 updates for Azure Database for PostgreSQL
Big news this month — PostgreSQL 17 is now GA with in-place upgrades, and our Migration Service fully supports PG17, making adoption smoother than ever. Also in this release: Online Migration is now generally available SSD v2 HA (Preview) with 10s failovers and better resilience Azure PostgreSQL now available in Indonesia Central VS Code extension enhancements for smoother dev experience Enhanced role management for improved admin control Ansible collection updated for latest REST API Check all these updates in this month’s recap blog: https://techcommunity.microsoft.com/blog/adforpostgresql/june-2025-recap-azure-database-for-postgresql/4412095 Check it out and tell us which feature you're most excited about!Skill Up On The Latest AI Models & Tools on Model Mondays - Season 2 starts Jun 16!
Quick Links To RSVP for each episode: EP1: Advanced Reasoning Models: https://developer.microsoft.com/en-us/reactor/events/25905/ EP2: Model Context Protocol: https://developer.microsoft.com/en-us/reactor/events/25906/ EP3: SLMs (and Reasoning): https://developer.microsoft.com/en-us/reactor/events/25907/ Get All The Details: https://aka.ms/model-mondays Azure AI Foundry offers the best model choice Did you manage to catch up on all the talks from Microsoft Build 2025? If, like me, you are interested in building AI-driven applications on Azure, you probably started by looking at what’s new in Azure AI Foundry. I recommend you read Asha Sharma’s post for the top 10 things you need to know in this context. And it starts with New Models & Smarter Models! New Models | Azure AI Foundry now has 11,000+ models to choose from – including frontier models from partner providers, and thousands of open-source community variants from Hugging Face. But how do you pick the right one for your needs? Smarter Models | It's not just about model selection, but about the effort required to use the model and validate the results. How can you improve the user experience and build trust and confidence in your customers? Solutions like Model Router and Azure AI Evaluations SDK help. The Challenge? | New models, features, and tools being released daily - the information overload is real. How do we keep up with the latest updates – and skill up on model choices? Say Hello to Model Mondays! Model Mondays is a weekly series with a livestream on Microsoft Reactor (on Mondays) and a follow-up AMA on Azure AI Foundry Discord (on Fridays). Here are the three links to know: Visit the Model Mondays repo: https://aka.ms/model-mondays Watch the Model Mondays playlist: https://aka.ms/model-mondays/playlist Join #model-mondays on Discord: https://aka.ms/model-mondays/discord Visit the playlist or repo to catch up on replays from Season 1 (above). Learn about topics like reasoning models, visual generative models, open-source AI, forecasting models, and local AI development with Visual Studio AI Toolkit. Each 30-minute episode consists of: 5-min Highlights. Catch up on top model-related news from the previous week. 15-min Spotlight. Get a deep dive into a specific model, model family, or related tool. Q&A. Ask questions on chat during the livestream, or join the AMA on Discord on Friday. Register Now to Join Us for Season 2! Microsoft Build showed us that the model catalog is expanding quickly – and so are the tools that are available, to help you select, customize, and evaluate, your AI application. In Season 2, we’re going to dive deeper into advanced topics in models and tools. Some of the topics that we hope to cover include: Advanced Reasoning Models – Deep Research, Visual Reasoning and more. Model Context Protocol – What it is, examples of MCP Servers today. SLMs and Reasoning – We dive into the Phi-4 model ecosystem for insights. Foundry Labs – Explore projects like Magentic-UI and MCP Server. Open-Source Models – Explore the 10K+ community models from Hugging Face. Edge Models – Explore Foundry Local and the rise of on-device AI capabiltiies. Models for AI Agents – Explore the Agent Catalog samples like Red-Teaming Model Playgrounds – Explore Image, Video, Agent, Chat, Language playgrounds Advanced Fine Tuning – Learn to fine GPT models, and use the Foundry Portal AI Developer Experience – Get productive with AI Toolkit & VS Code Extension pack Our first three episodes below are open for registration right now! EP1: Advanced Reasoning Models: https://developer.microsoft.com/en-us/reactor/events/25905/ EP2: Model Context Protocol: https://developer.microsoft.com/en-us/reactor/events/25906/ EP3: SLMs (and Reasoning): https://developer.microsoft.com/en-us/reactor/events/25907/ Let's build our model IQ and get starting developing AI applications on Azure! Want to Build AI Apps - and need resources to accelerate your journey? Chat with us on Azure AI Foundry Discord - https://aka.ms/aifoundrydiscord Provide feedback on our Discussion Forum - https://aka.ms/aifoundryforum Skill up with the Azure AI Foundry Learn Course - http://aka.ms/learnatbuild Review the Azure AI Foundry Documentation - http://aka.ms/AzureAI Download and explore the Azure AI Foundry SDK - http://aka.ms/aifoundrysdk
