Name: How to build a scalable, secure, and AI-ready container platform
Start: 2024-11-04T19:38:00Z
End: 2024-11-04T19:38:14.000Z
Location: BrightTALK
Rating: 4.5

Watch the latest Infrastructure and App Modernization news and innovations as we help customers 
innovate faster with the most productive and open cloud platform.

This deep dive into Google Cloud's Ironwood, our seventh-generation Tensor Processing Unit (TPU), explores how Ironwood's architecture provides the foundational infrastructure for enterprises to build, train, and deploy transformative AI capabilities faster and more cost-effectively than ever before.

We'll cover how to:
- Accelerate the entire AI workflow
- Solve for inference at scale
- Enable sustainable scale
- Integrate seamlessly with your ecosystem

Powering AI inference at scale: a deep dive into Ironwood TPUs

In an era marked by the rapid adoption of AI and LLMs, organizations face a critical inflection point. Success depends on underlying infrastructure, yet legacy systems struggle to meet AI's demands for specialized GPUs, dynamic scale, and modern architecture. Without a modern platform, businesses risk being outpaced by high costs and the inability to capitalize on AI's promise.

Join us for an in-depth webinar exploring Google Kubernetes Engine (GKE), the production-ready platform purpose-built for modern, cloud-native applications. We'll guide you through migrating workloads to GKE from on-premises infrastructure, VMs, or other Kubernetes providers.
In this session, you will learn:
• Key use cases from stateless web applications to AI/ML pipelines, and how GKE's automation reduces total cost of ownership • GKE's differentiators, including Autopilot mode for hands-off cluster management and hardened security on Google's private network
• Migration best practices through a clear, phased approach covering discovery, assessment, tool selection, modernization, and seamless cutover with minimal downtime 
• Performance and cost optimization using native observability, auto-scaling, and integrated Google Cloud services

This webinar provides actionable insights and a strategic framework to confidently plan and execute your GKE migration, building a foundation that accelerates your AI strategy with efficient resource use, developer velocity, and enterprise-grade security.

Modernize & Scale: Why and How to Migrate Your Workloads to Google Kubernetes Engine

Watch this webinar for a practical, step-by-step guide to modernizing your IT environment. We’ll cover our proven methodology for a smooth transition, whether you're planning a full data center exit or a targeted move of key workloads. Learn how to leave legacy constraints behind and build a flexible, future-ready foundation that unlocks the full potential of AI.

BUILD Your Migration for the AI Era: Tools, Systems, and Implementation Steps

Watch this webinar to discover how a strategic migration can position your enterprise at the forefront of innovation.
We go beyond the basics of "lift-and-shift" to show you how to truly modernize your infrastructure. You’ll learn how to accelerate AI adoption, significantly reduce costs, and empower your teams to build faster than ever.

Attend this webinar to discover how to accelerate your AI initiatives, fund your innovation, empower your teams, and modernize with confidence

PLAN Your Migration for the AI Era: Strategy, Pain Points, and Executive Alignment

Explore how organizations can unlock enhanced agility, substantial cost savings, and unparalleled AI acceleration by implementing successful migration to the cloud. Learn how to modernize infrastructure, foster collaboration with open-source technology, and reduce costs by up to 30%. This transition gives your business a strategic advantage in the new era of AI.

Block storage is fundamental to your compute workloads. Join our webinar to understand Google Cloud's Hyperdisk workload-optimized block storage solution that complements your compute infrastructure. We'll explore the various Hyperdisk "flavors," from Hyperdisk Balanced for general use to Hyperdisk Extreme for high-performance databases, and show you how to lower costs and simplify management using Hyperdisk Storage Pools. Understand how you can get workload-optimized data protection with Hyperdisk. Learn how to select the best Hyperdisk option to meet your specific performance and cost requirements.

Deep-dive on selecting the right block storage to complement your compute with Google Cloud Hyperdisk

Join us for a comprehensive webinar where we will unveil our new GKE AI Inference Reference Architecture, a powerful solution designed to accelerate your machine learning deployments on Google Cloud. We'll guide you through the seamless process of deploying this architecture, showcasing how it incorporates best practices for performance and scalability. In this session, you will learn how to:

Deploy with Confidence: Understand the step-by-step process for deploying the AI Inference Reference Architecture in your environment.

Leverage Built-in Best Practices: Discover the default components and configurations that ensure your deployments are optimized and secure.

Customize for Your Needs: Learn how to tailor the architecture to meet the specific requirements of your workloads.

Integrate with Your Network: Explore the options for deploying the reference architecture within your existing networking infrastructure.
Witness live demonstrations of deploying cutting-edge models, such as large language models (LLMs) and Stable Diffusion XL (SDXL) on Cloud TPUs, and see how the environment is pre-configured for immediate use.

Effortless AI Inference: Deploying and Scaling with GKE Reference Architecture

Agentic AI isn't just a buzzword; it's a fundamental shift in software. These intelligent, goal-driven applications operate autonomously, presenting unprecedented challenges for infrastructure teams. The old ways of building and running apps simply won't scale.

Join us for this technical deep dive where we'll explore how to harness the power of Kubernetes and modern platform engineering principles to create a scalable, resilient, and observable foundation for your next-generation intelligent applications.

In this webinar, you'll learn:
- The Shift: Understand why agentic apps require a new approach to infrastructure.
- Kubernetes as the Orchestration Layer: See how core Kubernetes primitives can be used to manage the complete, often complex, lifecycle of AI agents.
- The Power of a Platform Mindset: Discover how building an internal platform streamlines workflows, ensures security, and empowers developers to build and deploy intelligent software faster than ever.

Building and running agentic AI platforms on Kubernetes

Are you truly measuring the impact of your AI investments in software development?
While AI coding assistants are a game-changer for productivity and code quality, many organizations struggle to quantify their true value. Without a clear measurement framework, you can't optimize your AI strategy or justify the return on investment.



Join Nathen and PB for a practical, data-driven webinar on how to measure and maximize the benefits of AI in your development pipeline. Drawing on real-world insights, you'll learn how to go beyond basic adoption metrics and measure what truly matters.



In this webinar, you will discover how to:

· Establish a baseline: Understand your team's current performance before you implement AI.

· Track what matters: Identify and measure key metrics like development velocity, code quality, and developer satisfaction.

· Compare and analyze: Use a proven cohort-based methodology to compare AI-assisted teams with traditional workflows.

· Get a holistic view: Balance quantitative data with qualitative insights to build a complete picture of AI's impact.

Learn how Harness AI Productivity Insights—built in collaboration with Google Cloud—provides the comprehensive framework you need to make informed, data-driven decisions and drive lasting improvements in your software delivery.

Measuring the Impact of AI in Software Development: A Data-Driven Approach

Achieve superior price-performance for your most demanding workloads by migrating to Google Cloud's innovative infrastructure. This webinar will provide an in-depth look at the latest innovations in Compute Engine, including new VM families purpose-built for enterprise applications, databases, AI workloads and more. We'll explore the power of our Titanium architecture and high-performance Hyperdisk storage, and demonstrate how these differentiators across compute, storage, and networking translate into tangible cost savings and performance gains. Through concrete workload examples, you’ll learn why picking the right VM for your specific needs matters. We'll also share customer success stories and best practices to help you operate and optimize your Compute Engine environment, ensuring you can unlock unmatched value and performance.

Unlock compelling price-performance by migrating to Google Cloud’s workload-optimized infrastructure

Based on extensive research with thousands of professionals, this webinar explores how AI both accelerates success and amplifies existing system bottlenecks. We will help you determine if your team is a "Harmonious High-Achiever" or facing "Foundational Challenges" and provide a clear path forward. Learn how to leverage AI for a competitive edge, expose your organization's pain points, embrace a quality internal platform as a key success factor, and move from AI augmentation to AI-native evolution.

State of AI-Assisted Software Development: 2025 DORA Report

Moving your most demanding workloads to the cloud requires more than just a lift and shift—it requires a platform built for enterprise scale. Join us to discover how Google Cloud infrastructure can unlock the performance required for your mission-critical applications. We'll take a deep dive into our powerful compute and storage solutions, including the groundbreaking Titanium architecture, a variety of optimized Compute Engine families, and the high-performance Hyperdisk storage.


Through real-world workload vignettes, you'll learn how to leverage these technologies for specific use cases, from running high performance computing workloads on our compute optimized machines, commercial databases like SAP on our memory-optimized machines to running scale-out analytics workloads on our storage-optimized machines.

Migrate to Google Cloud's Infrastructure for your most demanding workloads with Specialized Compute

A Practical Guide to Platform Engineering

Shift Down: A Practical Guide to Platform Engineering

AI-assisted coding is revolutionizing software development. This session moves beyond theory to showcase the practical applications of AI-assisted coding within large enterprise teams, highlighting the specific ways developers are utilizing Gemini Code Assist - Google’s AI coding assistant - to streamline workflows. 
 
You will learn from this session how to successfully gain buy-in from both management and engineering teams by demonstrating the tool's value and addressing potential concerns. Learn when and how to integrate new AI technologies while prioritizing security, responsible usage, and alignment with existing development processes.

Gaining buy-in: A guide to successful AI adoption in development

Ten years ago, Google Kubernetes Engine (GKE) was born! Since then, it has become the industry-leading managed Kubernetes platform, powering mission-critical workloads across all industries. But the innovations have just begun. Join this session to learn about the latest GKE features and upcoming innovations – such as next-generation autoscaling, lightning-fast node startup, and multi-cluster fleet management – that make GKE the best Kubernetes platform for the next generation of AI and modern workloads.

GKE turns 10 and looks to the future of Kubernetes

Tired of juggling disparate tools and processes in your software development life cycle (SDLC)? This session explores how a multi-agent platform powered by AI can streamline your workflow and boost productivity. We’ll dive into how specialized agents for code review, testing, documentation, and modernization work together to enhance code quality, accelerate delivery, and free your developers to focus on what matters: creativity and innovation. Discover how this approach can transform your SDLC for the better.

Accelerate your software development lifecycle with agents

Building AI solutions on Google Cloud? This session demystifies our AI infrastructure stack, from pretrained models like Gemini to the Vertex AI managed platform, and all the way down to DIY container runtimes and virtual machines (VMs). Learn how to choose the right level of abstraction for your AI and machine learning (ML) workloads, and leverage the full power of Google Cloud’s AI ecosystem.

Connect the dots with Google Cloud AI: From models to machines

Unlock the power of AI with Google Cloud VMware Engine. Migrate your existing VMware workloads to Google Cloud and integrate with cutting-edge AI services like BigQuery and Cloud AI. Benefit from a fully managed service, high-speed connectivity, and enterprise-grade security. Reduce operational costs and accelerate your digital transformation. Learn more about building an AI-ready infrastructure with Google Cloud.

Google Cloud VMware Engine: An On-Ramp to AI-Ready Infrastructure

Google Fellows are some of our longest tenured and most innovative technical leaders. Join this session for a rare look at the lessons they've learned, the cutting-edge innovations they're developing, and how you can translate those experiences into actionable strategies for your own organization.

Google Fellows Panel – Lessons from our history

There are many ways to build AI-enabled applications without the usual training and development process. Learn how to focus on fine-tuning and deploying open Gemma models using Google Kubernetes Engine (GKE) and Cloud GPUs. We will also demonstrate how to access open models and datasets on Kaggle, so your team can experiment and build new AI solutions.

How to fine-tune AI models in your environment using Google Cloud and Kaggle

Driving application innovation is a priority for many, however, managing costs and optimizing existing resources is just as important. Learn how to strike that perfect balance by leveraging Gemini Code Assist and other SDLC tools for your developers.

How to set your app development team for success with AI

Technology teams are under immense pressure to deliver AI-powered applications quickly and efficiently, but complex infrastructure often hinders innovation and delays time to market. Your organization can unlock the full potential of serverless computing, accelerating AI-powered app deployments without sacrificing performance.

How to turn code into AI inference apps in minutes with serverless architecture

Enhance your applications with AI! Learn the technical aspects of integrating publicly available AI models like Gemma for cutting-edge customer experiences. Explore practical techniques for fine-tuning, optimizing performance, and ensuring safe AI usage. Seamlessly embed AI capabilities like personalized recommendations, intelligent chatbots, and content generation to create applications for users.

How to build AI-powered applications that improve customer experiences

Building, deploying, and scaling software for thousands of clusters can be challenging. Managing hardware and software to support use cases like fast transactions, predictive analytics, and visual inspections, add to the complexity. Leverage AI-enabled cloud infrastructure, AI models, and on-premises computing to unlock business.

How to deploy AI-enabled apps from cloud to on-premises

App sprawl and migration to multiple clouds can degrade app performance for customers and internal teams. Google's Cross-Cloud Network can ease the pain with secure and scalable cloud networks to prioritize critical traffic, boost reliability, and control costs.

How to optimize hybrid and multicloud networks for distributed apps

Empower your organization by migrating VMware to Google Cloud. Learn how you can realize significant cost efficiencies, accelerate innovation cycles, and simplify IT management to free your business from the constraints of on-premises infrastructure.

How to optimize costs and fuel innovation by moving VMware to Google Cloud

Did you know a ton of the Fortune 100 is using our next-gen IaaS for traditional workloads like SAP, Oracle, and Microsoft? It's true. Come learn why they're choosing Google and how they're optimizing for resilience and performance as a result.

How to optimize your traditional workloads on next-generation IaaS

Many technology teams are navigating a dual challenge: adopting the innovations of AI while ensuring efficiency and optimal utilization of existing infrastructure. Learn how to manage costs while enabling rapid prototyping and building AI applications for inference based on real-life Salesforce examples.

How to optimize your infrastructure for cost-efficient AI, learn from Salesforce

Architecting for long-term success is a massive balancing act – using new generative AI functionality for productivity, while optimizing your core applications for customers, and modernizing existing infrastructure to keep pace. Glean insights from Google leaders who have navigated this complex path firsthand. Discover the lessons they've learned, the cutting-edge innovations they're developing, and how their experiences become actionable strategies for your own organization.

Building the Enterprise of Tomorrow - Lessons from Google’s own experience

Google Cloud App Dev & Infrastructure Summit

TPUs, GPUs, oh my! Build a scalable container platform for AI and all workloads, delivering value to your customers. Learn how our container platform delivers AI-optimized compute, storage, and network infrastructure fueling successful projects.

How to build a scalable, secure, and AI-ready container platform

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How to build a scalable, secure, and AI-ready container platform

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