Airbnb’s Open-Source GraphQL Framework with Adam Miskiewicz
Episode
55 min
Read time
2 min
Topics
Remote Work, Startups, Artificial Intelligence
AI-Generated Summary
Key Takeaways
- ✓Schema Stitching Evolution: Airbnb initially converted Thrift APIs to GraphQL automatically, creating service-oriented GraphQL with top-level fields per service rather than an entity graph. This approach enabled rapid client adoption across iOS, Android, and web without requiring backend engineers to learn GraphQL, protecting them during the microservice migration while establishing the typed API foundation clients demanded.
- ✓Hosted Business Logic Pattern: Viaduct runs counter to GraphQL best practices by encouraging teams to host business logic directly in the platform rather than separate microservices. This decision emerged from microservice fatigue at Airbnb, where developers struggled with slow iteration cycles. The platform organizes code into tenant modules with schema and implementation opinions, resembling small services hosted in one scalable platform.
- ✓Async Memoization Performance: Viaduct implements automatic async memoization to eliminate duplicate resolver execution within a single request. When multiple fields depend on the same data like firstName or lastName, the resolver executes once and caches results. This optimization proves critical for queries spanning 100,000 to 300,000 fields that return megabytes of data, addressing performance at extreme GraphQL scale.
- ✓Reentrancy Architecture: Developers declare data dependencies using GraphQL fragments within resolvers instead of making direct service calls. For example, a fullName field declares dependencies on firstName and lastName from the user entity, and Viaduct fetches or computes them automatically. This pattern scales effectively as the 25,000-type schema grows, enabling feature development without external service integration.
- ✓Engine-Tenant Separation: Viaduct Modern separates a lean execution engine from the strongly-typed tenant API, similar to kernel-user space boundaries. The engine handles high-performance execution, batching, and caching with raw data, while the tenant layer provides Kotlin type safety. This boundary enables independent tenant deployment and prevents typed information from propagating through the entire system, solving multi-tenant scaling challenges.
What It Covers
Adam Miskiewicz, principal software engineer at Airbnb, explains Viaduct, an open-source GraphQL platform that handles over one million queries per second. The discussion covers Airbnb's evolution from microservices fragmentation to a unified data graph, architectural principles behind scaling GraphQL to massive queries with 300,000 fields, and how AI agents may reshape backend development patterns.
Key Questions Answered
- •Schema Stitching Evolution: Airbnb initially converted Thrift APIs to GraphQL automatically, creating service-oriented GraphQL with top-level fields per service rather than an entity graph. This approach enabled rapid client adoption across iOS, Android, and web without requiring backend engineers to learn GraphQL, protecting them during the microservice migration while establishing the typed API foundation clients demanded.
- •Hosted Business Logic Pattern: Viaduct runs counter to GraphQL best practices by encouraging teams to host business logic directly in the platform rather than separate microservices. This decision emerged from microservice fatigue at Airbnb, where developers struggled with slow iteration cycles. The platform organizes code into tenant modules with schema and implementation opinions, resembling small services hosted in one scalable platform.
- •Async Memoization Performance: Viaduct implements automatic async memoization to eliminate duplicate resolver execution within a single request. When multiple fields depend on the same data like firstName or lastName, the resolver executes once and caches results. This optimization proves critical for queries spanning 100,000 to 300,000 fields that return megabytes of data, addressing performance at extreme GraphQL scale.
- •Reentrancy Architecture: Developers declare data dependencies using GraphQL fragments within resolvers instead of making direct service calls. For example, a fullName field declares dependencies on firstName and lastName from the user entity, and Viaduct fetches or computes them automatically. This pattern scales effectively as the 25,000-type schema grows, enabling feature development without external service integration.
- •Engine-Tenant Separation: Viaduct Modern separates a lean execution engine from the strongly-typed tenant API, similar to kernel-user space boundaries. The engine handles high-performance execution, batching, and caching with raw data, while the tenant layer provides Kotlin type safety. This boundary enables independent tenant deployment and prevents typed information from propagating through the entire system, solving multi-tenant scaling challenges.
Notable Moment
Miskiewicz reveals that Airbnb runs approximately 80 percent of all API traffic through Viaduct, making it too critical to fail. The platform serves over one million GraphQL operations per second across a codebase with millions of lines of tenant code, yet the team never forces engineers to rewrite. Instead, they plan AI-assisted migrations to transition from Classic to Modern architecture.
Episode Transcript
Are you passionate about software development and the tech industry? Software engineering daily is looking for a new podcast host to grow its hosting team. In this role, you'll help shape the show's editorial direction and interview engineers, founders, hackers, and tech leaders. Podcasting experience is a plus, but not required. Curiosity, great communication skills, and a genuine interest in the craft of building software are what matter most. If this sounds like you, reach out at editor@softwareengineeringdaily.com. Engineering teams often build microservices as their systems grow, but over time, this can lead to a fragmented ecosystem with scattered data access patterns, duplicated business logic, and an uneven developer experience. A unified data graph with a consistent execution layer helps address these challenges by centralizing schema, simplifying how teams compose functionality, and reducing operational overhead while preserving performance and reliability. Viaduct is Airbnb's open source, data oriented service mesh and GraphQL platform built around a single, highly connected central schema. It has played a major role in scaling Airbnb's engineering organization. Adam Miscovich is a principal software engineer at Airbnb, and he worked on Viaduct. He joins the podcast with Gregor Van to talk about how Viaduct originated inside Airbnb, the architectural principles that shaped it, the challenges of scaling GraphQL to millions of queries per second, and why the team decided to open source the platform. They also discuss the future of back end development in an AI driven world and how unified data layers may influence the next generation of engineering systems. Gregor Vand is a security focused technologist, having previously been a CTO across cybersecurity, cyber insurance, and general software engineering companies. He is based in Singapore and can be found via his profile at van.hk or on LinkedIn. Hello, and welcome to Software Engineering Daily. My guest today is Adam Miscavige. Hey. How's it going? Nice to be here. Yeah. Great to have you here. Today, we're gonna be talking about Viaduct and that is a spin out from Airbnb. So we're gonna still be understanding what happened there. But, yeah, Adam, I'd love you just to talk to us a bit about, first of all, just your journey to maybe to, like, to Airbnb, and then where did Vydot come from and how did that come about? Yeah. Absolutely. Yeah. So I have been a software engineer for gosh, it's pushing twenty years or something professionally these days. And I actually took a little bit of a non traditional path to kind of where I'm at at Airbnb, kind of working in big tech. I have done a lot of work at a lot of small companies. I ran an agency, like an interactive agency in Baltimore, Maryland for a while, building web and mobile apps for folks and interactive installations. Worked at a company called Expo. Some folks, some listeners might be familiar with, doing React Native tooling, and then eventually kind of ended up at Airbnb. So I kind of went from small …
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“Adam Miskiewicz, principal software engineer at Airbnb, explains Viaduct, an open-source GraphQL platform that handles over one million queries per second.”
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