The AWS Developers Podcast

Amazon Web Services

Stay updated on the latest AWS news and insights for developers, wherever you are, whenever you want.

  1. The Hard Lessons of Cloud Migration: inDrive's Path from Monolith to Microservices

    25 MAR

    The Hard Lessons of Cloud Migration: inDrive's Path from Monolith to Microservices

    Join us for a fascinating conversation with Alexander 'Sasha' Lisachenko (Software Architect) and Artem Gab (Senior Engineering Manager) from inDrive, one of the global leaders in mobility operating in 49 countries and processing over 8 million rides per day. Sasha and Artem take us through their four-year transformation journey from a monolithic bare-metal setup in a single data center to a fully cloud-native microservices architecture on AWS. They share the hard-earned lessons from their migration, including critical challenges with Redis cluster architecture, the discovery of single-threaded CPU bottlenecks, and how they solved hot key problems using Uber's H3 hexagon-based geospatial indexing. We dive deep into their migration from Redis to Valkey on ElastiCache, achieving 15-20% cost optimization and improved memory efficiency, and their innovative approach to auto-scaling ElastiCache clusters across multiple dimensions. Along the way, they reveal how TLS termination on master nodes created unexpected bottlenecks, how connection storms can cascade when Redis slows down, and why engine CPU utilization is the one metric you should never ignore. This is a story of resilience, technical problem-solving, and the reality of large-scale cloud transformations — complete with rollbacks, late-night incidents, and the eventual triumph of a fully elastic, geo-distributed platform serving riders and drivers across the globe.

    1hr 14min
  2. Episode 200: Java & Spring AI Are Winning the Enterprise AI Race — with James Ward & Josh Long

    18 MAR

    Episode 200: Java & Spring AI Are Winning the Enterprise AI Race — with James Ward & Josh Long

    It's a milestone — episode 200! And to mark the occasion, we're doing something we've never done before: hosting two guests at the same time. James Ward (Principal Developer Advocate at AWS) and Josh Long (Spring Developer Advocate at Broadcom, Java Champion, and host of 'A Bootiful Podcast') join Romain for a wide-ranging conversation about why Java and Spring AI are becoming the go-to stack for enterprise AI development. We kick off with Spring AI's rapid evolution — from its 1.0 GA release to the just-released 2.0.0-M3 milestone — and why it's far more than an LLM wrapper. James and Josh break down how Spring AI provides clean abstractions across 20+ models and vector stores, with type-safe, compile-time validation that prevents the kind of string-typo failures that plague dynamically typed AI code in production. The numbers back it up: an Azul study found that 62% of surveyed companies are building AI solutions on Java and the JVM. James and Josh explain why — enterprise teams need security, observability, and scalability baked in, not bolted on. We dive into the Agent Skills open standard from Anthropic and James's SkillsJars project for packaging and distributing agent skills via Maven Central. We also cover Spring AI's official Java MCP SDK (now at 1.0) and how MCP and Agent Skills complement each other for building capable, composable agents. The performance story is striking: Java MCP SDK benchmarks show 0.835ms latency versus Python's 26.45ms, 1.5M+ requests per second versus 280K, and 28% CPU utilization versus 94% — with even better numbers using GraalVM native images. Josh and James also walk us through Embabel, the new JVM-based agentic framework from Spring creator Rod Johnson, featuring goal-oriented and utility-based planners with type-safe workflow definitions built on Spring AI foundations. We close with a look at running Spring AI agents on AWS Bedrock AgentCore — memory, browser support, code interpreter, and serverless containers for agentic workloads.

    52 min
  3. Mike Chambers: From OpenClaw to AI Functions — What's Next for Agentic Development

    25 FEB

    Mike Chambers: From OpenClaw to AI Functions — What's Next for Agentic Development

    Mike Chambers is back — calling in from the other side of the globe — and he brought a lot to unpack. We pick up threads from our first conversation and follow them into genuinely exciting (and occasionally mind-bending) territory. We start with OpenClaw, the open-source agentic framework that took the developer world by storm. Mike shares his take on why it happened now — not just what it is — and why the timing was almost inevitable given how developers had been quietly experimenting with local agents for the past year. Then we go deep on asynchronous tool calling — a project Mike has been working on since mid-2024 that finally works reliably, thanks to more capable models. The idea: let your agent kick off a long-running task, keep the conversation going naturally, and have the result arrive without interrupting the flow. Mike walks through how he built this on top of Strands Agents SDK and why he's planning to propose it as a contribution to the open-source project. We also explore Strands Labs and its freshly released AI Functions — a genuinely new way to think about embedding generative capability directly into application code. Is this Software 3.1? Mike makes the case, and Romain pushes back in the best way. The episode closes with a look ahead: agent trust, observability with OpenTelemetry, and a thought experiment about what software might look like in five years if the execution environment itself becomes a model.

    1hr 19min

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Stay updated on the latest AWS news and insights for developers, wherever you are, whenever you want.

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