Published 5 May 2026
Duration: 00:30:49
A deep dive into microservices challenges, server-driven contract testing via Spring Cloud Contract, AI-driven contract generation with human oversight, observability strategies, and balancing automation with foundational knowledge and community feedback to avoid tooling pitfalls.
This interview was recorded for GOTO Unscripted. https://gotopia.tech Marcin Grzejszczak - Software Engineer at HeroDevs & Java Champion Jakub Pilimon...
The podcast episode features an interview with Marcin Grzejszczak, a software developer with extensive experience in open-source projects, distributed systems, and microservices architecture. He discusses his work on tools like Spring Cloud Contract, initially named Accurist, which addresses challenges in consumer-driven contract testing for microservices. Grzejszczak highlights the importance of server-driven contracts to ensure consistency between client and server behaviors, automating validation of breaking changes, and leveraging foundational texts like Building Microservices by Sam Newman. He also reflects on past projects, including a notable mistake where a minor API typo caused production issues, emphasizing the need for robust testing and pipelines. The conversation delves into the evolution of Spring Cloud Contract, challenges in balancing public contributions with personal growth, and the role of community feedback in refining open-source tools.
Technical themes include the limitations of manual contract testing, the cognitive load of managing contracts with diverse tools, and proposals for AI-assisted contract generation using production traffic as a data source. Grzejszczak advocates for human oversight in AI-generated contracts and outlines a three-pillar approach to observability: logs, metrics, and traces, stressing the need to correlate them rather than analyze them in isolation. He also explores the potential of AI to reduce the burden of contract management, shifting from developers writing contracts to AI proposing them for review. The discussion underscores the importance of context in system analysis, the impact of poor design choices (e.g., a poorly structured class in Spring Cloud Contract), and the value of learning from both successes and failures in software development. Observability tools like Micrometer and the transition of Spring Cloud Sleuth to micrometer are also mentioned as key contributions.
8 May 2026 Java Cookbook Ian Darwin & Jeanne Boyarsky
Java's evolution through features like Records and Switch Expressions, career transitions from Fortran, integration with R for data analysis, AI's role in coding, structured learning resources, open-source contributions, and concerns about AI's impact on education and intellectual property are explored.
1 May 2026 Learning API Styles Lukasz Dynowski & Sam Newman
This exploration of API design delves into networking fundamentals, communication paradigms, protocol mechanics, trade-offs in security and performance, data formats, microservices communication patterns, emerging technologies like Web Transport and gRPC, and the critical role of secure, documented, and reproducible frameworks aligned with architectural and use-case demands.
28 Apr 2026 A Common-Sense Guide to AI Engineering Jay Wengrow & Kris Jenkins
Structured educational resources are crucial for practical AI implementation, addressing LLM system prompts, guardrails, task delegation challenges, orchestration vs custom solutions, and real-world examples like AI-driven podcast creation, while balancing timeless principles with rapid tech evolution.
24 Apr 2026 Beyond the Hype: What AI Actually Can (and Can't) Do Jodie Burchell & Michelle Frost
The discussion covers AI's evolution, generative models' dominance, ethical and technical challenges, the need for scientific rigor, critiques of overreliance on generative models, practical applications, and debates on AGI versus narrow AI.
21 Apr 2026 Kubernetes at the Edge Charles Humble & Hannah Foxwell
Edge computing explores localized processing tiers (far, device, near edge), challenges in remote resilience, sector-specific applications in military and renewables, sustainability through reduced data center energy use, ethical AI governance, and the balance of innovation with responsible, user-centric deployment.