3 ways to deploy your large language models on AWS
In this episode of the AWS Developers Podcast, we dive into the different ways to deploy large language models (LLMs) on AWS. From self-managed deployments on EC2 to fully managed services like SageMaker and Bedrock, we break down the pros and cons of each approach. Whether you're optimizing for compliance, cost, or time-to-market, we explore the trade-offs between flexibility and simplicity. You'll hear practical insights into instance selection, infrastructure management, model sizing, and prototyping strategies. We also examine how services like SageMaker Jumpstart and serverless architectures like Bedrock can streamline your machine learning workflows. If you're building or scaling AI applications in the cloud, this episode will help you navigate your options and design a deployment strategy that fits your needs.
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40:28
The golden jacket: a journey towards 12 AWS certifications
In this episode of the AWS Developers Podcast, we sit down with Ivan Casco, Principal Solutions Architect, AWS Community Builder, and one of the rare few to have earned all 14 AWS certifications—an achievement that earned him the coveted Golden Jacket. Ivan takes us through his remarkable journey, from his first certification back in 2017 to joining the Community Builders program in 2023, and finally reaching the full set of certifications in 2025. Based between Spain and Dublin, Ivan shares what drove him to pursue this challenge, how he stayed motivated, and which certifications pushed him the most—spoiler alert: networking and machine learning were no walk in the park. We also dive into his favorite study techniques, what it’s really like to sit through the exams, and how these certifications have impacted both his confidence and his career. If you're thinking about starting your own AWS certification path—or you're in the middle of one—this conversation is full of practical advice, community insight, and inspiration. Plus, find out what the golden jacket moment was really like.
Join us for an in-depth conversation with Rick Ochs from AWS as we explore the powerful capabilities of AWS Compute Optimizer. Discover how this free tool changes cloud resource management by leveraging machine learning to deliver precise recommendations for EC2 instances, EBS volumes, and more. Rick shares insights on how Compute Optimizer analyzes historical utilization data to help organizations optimize both cost and performance, while respecting customer privacy through opt-in features. Learn about the tool's evolution, its integration with auto scaling groups, and how it handles everything from basic resource sizing to complex performance management decisions. We also dive into the future of cloud optimization, exploring upcoming AI integrations and discussing how AWS builds trust in its recommendations. Whether you're managing a small deployment or a large-scale infrastructure, this episode offers valuable insights into maximizing your AWS resources while maintaining optimal performance and cost efficiency.
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45:17
The new stack: AI, Tools, MCP (& Amazon Bedrock)
In this episode of the AWS Developers Podcast, Sebastien Stormacq is joined by Giuseppe Battista and Kevin Shaffer-Morrison for a deep dive into Agentic AI and the Model Context Protocol (MCP). They explore how startups are rapidly adopting generative AI and the business and technical hurdles they encounter along the way. The conversation covers how AI agents are integrated into workflows, the role of orchestration technologies, and how tools enhance the planning capabilities of AI models. The trio unpacks the MCP framework and its potential to standardize communication between large language models and tools—drawing a compelling analogy to how USB transformed hardware interactions. They also discuss the complexities of tool orchestration, including resource management and security, and what the rise of ‘tool definition engineering’ means for the future. From integrating MCP with platforms like Amazon Bedrock to rethinking the role of software engineers, this episode looks at how AI is reshaping the foundations of modern software development.
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48:59
Behind the Scenes of AWS SDK Development
In this episode of the AWS Developers Podcast, we sit down with Trevor Rowe, Senior Manager of the AWS SDK team, for a deep dive into the evolution and inner workings of the AWS SDKs. We explore how the SDKs scale to support over 320+ AWS services, the importance of maintaining backward compatibility, and the role of developer experience in shaping the SDK design. Trevor explains how the team uses Smithy to automate code generation, ensuring consistency and efficiency across different programming languages. The conversation touches on the growing adoption of modular architecture, community contributions via GitHub, and the team's efforts to improve performance, define better schemas, and simplify migrations. Whether you're building cloud applications or maintaining complex integrations, this episode offers a behind-the-scenes look at how AWS builds and evolves its core developer tools.
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