Scaling productivity with Service Runtimes at Confluent

About Cody Ray:

Cody is a Senior Engineering Manager at Confluent, setting your data in motion. He joined in 2017 to build and launch Confluent Cloud. Prior to Confluent, Cody helped bootstrap an adtech SaaS company and briefly worked in finance. Outside of work, Cody is an active real estate investor, a digital nomad, and an avid adventurer who likes diving with sharks, jumping off mountains, hiking Macchu Picchu and Kilimanjaro, and hanging with his wife and 8 month old.

Cody on Linkedin

Chapters
00:00 Introduction and Background
06:24 The Role of Service Runtimes in Developer Productivity
14:36 Showing impact and storytelling
24:15 The Impact of Testing Initiatives at Confluent
28:50 Roadmap and Future Challenges in Dev Productivity
31:14 Rapid fire

Summary
In this podcast episode, Cody Ray, a Senior Engineering Manager at Confluent discusses the evolution of developer productivity and platform engineering at Confluent. He shares how his team has grown and the scaling challenges they faced. Cody explains the concept of service runtimes and how they provide a structured framework for developers to create new services. He also talks about the challenges of migration and the importance of getting code across the network divide. Cody emphasizes the need for empathy and the ability to synthesize requirements in a good engineer working in dev productivity. He also discusses the impact of AI-powered coding assistants and the use cases for LLM in developer productivity.

Keywords

Developer productivity, platform engineering, Confluent, scaling challenges, service runtimes, migration, code coverage, testing, AI-powered coding assistants, LLM.

Takeaways

• Developer productivity and platform engineering are crucial for scaling a company like Confluent.

• Service runtimes provide a structured framework for creating new services and improving productivity.

• Migrations can be challenging, but isolating code into service runtimes can make them easier.

• Testing should be done as much as possible locally to reduce feedback loops.

• Storytelling and showcasing impact are effective ways to evangelize dev productivity initiatives.

• Empathy and the ability to synthesize requirements are important qualities for engineers in dev productivity.

• AI-powered coding assistants and LLM can potentially improve productivity and code quality.

• Code recommends the book “Release It” for understanding design patterns and building resilient systems.