Code migration sounds like a technical task, but it’s a strategic minefield.

In this episode, we explore how code migration projects fail not because of bugs, but because of broken decision-making and unclear architecture.

You’ll hear about raw stories from engineers at Slack, Datadog, and other world-class teams who’ve battled through the chaos of code migration under pressure.

If you’re relying on AI to do the thinking for you, this episode will make you rethink everything.

Whether you’re planning a rewrite or deep in the trenches, you’ll learn how to survive your next code migration, and maybe even lead one right.

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Code migration sounds like a technical task, but it’s a strategic minefield.

In this episode, we explore how code migration projects fail not because of bugs, but because of broken decision-making and unclear architecture.

You’ll hear about raw stories from engineers at Slack, Datadog, and other world-class teams who’ve battled through the chaos of code migration under pressure.

If you’re relying on AI to do the thinking for you, this episode will make you rethink everything.

Whether you’re planning a rewrite or deep in the trenches, you’ll learn how to survive your next code migration, and maybe even lead one right.

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Code migration doesn’t have to be slow and painful. In this episode, Madeline and I break down a proven method to speed up your code migration process without sacrificing code quality or stability.

You’ll learn actionable insights from a real-world team who successfully tackled code migration at scale, and did it faster than most thought possible!

If you’re planning a code migration, currently in one, or trying to avoid the common pitfalls, this episode is packed with the perspective you need.

Let's break down a real world example with Madeline, which is a smarter way to approach your code migration strategy and accelerate delivery without cutting corners!

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Connect with Madeline!

➡️ https://www.linkedin.com/in/madelineshortt/

Tom Elliott joined Yext in 2015 as an iOS developer. Within a year, both his mobile projects were canceled.

But Tom's career crisis was nothing compared to what was happening with Yext's infrastructure. 

The company was hitting the limits of homegrown tools built by ex-Google engineers who had recreated their own version of Borg called Khan. It worked when Yext was small. Now they were running thousands of microservices—Tom calculated they had a higher microservice-to-employee ratio than Uber.

The real breaking point? Server upgrades. Every time the infrastructure team needed to upgrade a machine, they had to manually edit code to move services off, do the upgrade, then edit code again to move everything back.

"Everything was manually configured as to where things lay," Tom recalls.

Khan had been built by "one or two people" as a coalition of the willing.

Now Yext had grown past 20 teams, and adding the features they desperately needed—like automatic workload migration—would require massive investment in a homegrown system.

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Connect with Tom! : https://www.ocuroot.com/

IBM was dropping RethinkDB support. No migration path. No alternatives. Just an end date.

Andy Monroe's team at LaborChart had five engineers and an entire construction scheduling platform built on a database that was already dead. They'd watched every other RethinkDB hosting provider shut down, leaving only Compose.io.

When IBM acquired Compose, they knew it was just a matter of time.

Andy's air conditioning had died two hours before our interview. It was 90 degrees in Kansas, and as we talked about this moment, the irony wasn't lost on either of us.

The company he'd helped build solved scheduling problems for construction workers—the very people who might have fixed his AC. Now he had a different kind of emergency to handle.

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Connect with Andy! - andymonroe.dev

Back in 2011, PagerDuty had a problem that would make any infrastructure engineer wince: they were using MySQL as a queue. 

In this episode, we dive into the fascinating journey of using Cassandra as a queue, the challenges faced, and the lessons learned along the way.

Arup Chakrabarti, former Senior Director of Engineering at PagerDuty, shares his insights on the early days of the company, the technical decisions made, and how they navigated the complexities of using a NoSQL database in unconventional ways.

Check out Arup's work! ➡️ arupchak.com

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In this episode of Turn Stories, I dive deep into my experiences with Bobby Grayson, the first engineer at Quantierra, a YC-backed startup.

Bobby shares his journey from the chaos of WeWork to the unique challenges of a small startup, where he faced a messy codebase and low reliability. 

We discuss the impressive app he helped build, which aggregates vast amounts of data from New York City, and how he transformed the system to better support users' workflows.

If you're curious about the intersection of technology and real estate, or if you're an engineer looking for inspiration on tackling complex projects, this episode is a must-listen. Join us as we explore the future of software development and the exciting possibilities that lie ahead.

Connect with Bobby! ➡️ https://bsky.app/profile/bobbby.online

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In this episode, Cooper Bethea, a senior staff engineer at Slack, shares his journey of transforming Slack's architecture to a cellular model, allowing for more resilient operations.

Cooper recounts the frustrations of dealing with outages and the decision-making process that led to the migration to a cellular architecture. He explains how the initial struggles with service discovery and load balancing prompted a reevaluation of their infrastructure.

The key insight was that draining an AZ should not be a rare, high-stakes event but rather a routine operation that could be executed with confidence. Cooper discusses the importance of incremental changes and how they were able to practice draining traffic from AZs during peaceful times, ultimately leading to a more robust system.

This episode is a must-listen for anyone interested in infrastructure, reliability, and the challenges of scaling systems in a cloud environment.

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Connect with Cooper ➡️ https://www.linkedin.com/in/cooper-bethea-521936201/

In this episode of Tern Stories, I spoke with Maude Lemaire about a migration that started with SQL and ended with people taking shifts at dawn.  

She joined Slack less than two years out of college, and within months, she was leading a core part of the company’s efforts to keep up with their biggest customer, IBM. The project: unifying Slack’s channel membership model—one of the most central, performance-sensitive parts of the product.

At one point, the system was so fragile that engineers had to be in the office at 6 A.M. every day, just to watch IBM’s login spike and make sure the system didn’t collapse.  

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Go check out what Maude does! ➡️ https://maudethecodetoad.com/  

Her book, Refactoring at Scale, is available now 📖: https://www.oreilly.com/library/view/refactoring-at-scale/9781492075523/  

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If you’ve worked on more than one code migration, you already know the punchline: none of them are the same.  

Sure, it sounds like a React 17 → 18 upgrade should follow the same plan for everyone.   

But a real-world code migration always find a way to be uniquely painful. Your app uses different corners of the library.  

Your plugin stack has its own fingerprint.  

Your engineers wrote some “just for now” code that’s still running five years later.  

Whatever you thought the code migration would be, it won’t be.  

This was one of the biggest takeaways in a recent episode of Tern Stories, where we looked inward for once.  

My cofounder Ryan and I talked through what we’ve seen in our own migrations and the ones we’ve supported across companies.  

Despite the variety, a few consistent truths emerged.

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