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Streamlining AI/ML Workloads on Kubernetes with Pulumi and Google Cloud. Kubernetes has become the de facto platform for AI/ML workloads, offering the flexibility, scalability, and resource efficiency that modern machine learning models demand. In this session, you'll learn how to deploy and scale AI/ML workloads on Kubernetes with Pulumi, using Google Cloud infrastructure. Get the details here: https://www.pulumi.com/blog/ai-ml-on-... What You'll Learn: ✅ How Kubernetes simplifies AI/ML workload management ✅ Deploying an open-source LLM with RAG on Kubernetes ✅ Building a framework for training & serving ML models ✅ Leveraging Google Cloud Kubernetes Engine (GKE) for AI workloads ✅ Using Pulumi and Python for infrastructure as code This hands-on session demonstrates Pulumi's Python support, making infrastructure automation more accessible to ML engineers and data scientists. Whether you're serving AI models or training ML workflows, you'll see how Kubernetes, Pulumi, and Google Cloud can power your machine learning pipelines. 👨💻Source Code: https://github.com/jasonsmithio/pulum... ▬▬▬▬▬▬ More Hands-On Kubernetes & AI/ML Content ▬▬▬▬▬▬ Explore more deep-dive workshops, demos, and best practices in these playlists: 🔹 Google Cloud for AI & Infrastructure → • Pulumi and Google Cloud: A Winning Combina... 🔹 Kubernetes for AI & Cloud-Native Workloads → • Pulumi and Kubernetes - Better Together | ... 🔹 AI/ML Engineering & Hands-on Demos → • Deploy a LangChain/LangServe Chatbot App u... ▬▬▬▬▬▬ Want to learn more? ▬▬▬▬▬▬ 🎓 Register for live workshops and Q&A: https://pulumip.us/Upcoming-Workshops 🚀 Get Started with Pulumi: https://pulumip.us/Get-Started 🤖 Try Pulumi AI: https://www.pulumi.com/ai/ 💬 Talk with us: https://slack.pulumi.com/