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Designing developer productivity metrics with MongoDB

In this conversation, Tara Hernandez and Stacey King Poling discuss their roles in developer productivity at MongoDB and the challenges they face.

About Tara Hernandez and Stacey King Poling:

Tara is VP of Developer Productivity at MongoDB. Tara has spent nearly thirty years evolving ways for companies to develop and ship software. She helped launch and has been a firm proponent of open source ever since.

Stacey is Director of Engineering for Developer Productivity at MongoDB, previously led Developer Productivity at Elastic. Stacey is passionate about improving the quality of engineering productivity, and building bridges between the silos of engineering.

Stacey on Linkedin

Tara on Linkedin

Jobs in Dev Productivity at MongoDB:

Senior Software Engineer, Developer Productivity, US
Senior Software Engineer, Developer Productivity, CA
Software Engineer 3, Developer Productivity, US

00:00 Dev productivity at MongoDB
07:38 Find the right Dev productivity metrics
22:55 Dev Productivity Surveys
29:05 Recommendations for new Dev productivity teams
33:09 Convincing Leadership to Invest in Developer Productivity
36:38 Maturity of Dev productivity at MongoDB
46:47 Rapid Fire questions
53:00 Recommended Books and Excitement About the Future of DX and DevEx Space

In this conversation, Tara Hernandez and Stacey King Poling discuss their roles in developer productivity at MongoDB and the challenges they face. They talk about the structure of their teams, the variety in build and release processes, and the importance of metrics in measuring productivity. They emphasize the need to consider context when analyzing metrics and the potential pitfalls of certain measurements. They also discuss the role of surveys in understanding developer sentiment and the people aspect of developer productivity. Tara and Stacey discuss the need for early investment in developer productivity, the role of empathy and understanding in DX engineering, and the value of customization in developer tools. They also touch on the potential of AI and machine learning in improving DX and recommend books like 'Accelerate' and 'The Unicorn Project' for further reading.

Developer productivity, MongoDB, team structure, build and release processes, metrics, surveys, context, outcomes, people aspect, developer experience, DX culture, developer productivity, empathy, customization, AI, machine learning.


  • Developer productivity at MongoDB is supported by various functions, including CI systems, release tooling, performance testing, and analytics.

  • The team structure is distributed, with different frameworks and testing methods in place for different products and release channels.

  • Metrics should be used with caution and in context, as they can be easily misinterpreted or incentivize the wrong behaviors.

  • Surveys are valuable for understanding developer sentiment, but qualitative data and feedback should also be considered.

  • The focus should be on outcomes and meeting goals, and managers should prioritize deliverables and create a positive culture.

  • Building a developer productivity organization requires understanding the business value, educating oneself, and getting buy-in from senior leaders and engineers. Early investment in developer productivity and building good habits is crucial for scaling a company's engineering team.

  • To change the culture internally, start by identifying and improving one specific area that needs attention.

  • A good DX engineer is empathetic, understands the frustrations of developers, and cares about the domain and the teams they work with.

  • Customization and flexibility in developer tools are important for meeting specific product needs.

  • AI and machine learning have potential in improving developer experience, but it's still early days and requires careful consideration.

  • Recommended books for further reading: 'Accelerate' and 'The Unicorn Project'.

Hangar DX
Hangar DX Podcast
The Hangar DX podcast focuses on developer experience and learning how different companies solve developer productivity challenges at scale.