# Tinder
> Dating and social discovery application that allows people to discover and connect with potential matches.

## Articles

### [How We Decomposed Tinder’s Monolith](https://yomu.fyi/post/how-we-decomposed-tinder-s-monolith.md)
- Company: [Tinder](https://yomu.fyi/company/tinder.md)
- Author: Tinder
- Published: May 23, 2025

Tinder faced significant agility and build performance challenges caused by an iOS codebase monolith containing over 1,000 files and 150,000 lines of code. Manual extraction efforts risked creating massive, unmanageable pull requests that would require constant rebasing against the main branch. To systematically decompose the target into Swift sub-modules, the team mapped declarations and references via the Swift compiler into a directed graph. They iteratively extracted leaf nodes with an in-degree of zero across sequential phases and automated common code adjustments, including module dependencies, imports, access control levels, and dependency injection. The automated decomposition completed in under six months with zero P0 incidents, reducing monolith build times by 78% and disallowing future additions to the monolith target.


### [How On-Device AI Models Find Your Best Tinder Profile Photos](https://yomu.fyi/post/how-on-device-ai-models-find-your-best-tinder-profile-photos.md)
- Company: [Tinder](https://yomu.fyi/company/tinder.md)
- Author: Tinder
- Published: Apr 28, 2025

Tinder developed an on-device AI Photo Selector to recommend compelling profile photos directly from a user's camera roll without exposing private assets. To establish a reference face, the system extracts facial landmarks via Apple's Vision framework and normalizes the crop using affine transformations. To prevent funnel drop-offs from mandatory selfies, the architecture includes a fallback mechanism that detects a single recognizable face in existing profile photos. Processing workflows execute concurrently across thousands of local assets while downloading and initializing TensorFlow Lite models in parallel using Combine. A dedicated analytics queue synchronizes operation counts with DispatchGroup to ensure accurate metric capture before the global rollout.


### [Tinder’s migration to Elasticsearch 8](https://yomu.fyi/post/tinder-s-migration-to-elasticsearch-8.md)
- Company: [Tinder](https://yomu.fyi/company/tinder.md)
- Author: Tinder
- Published: Apr 1, 2025

Tinder modernized its recommendation system by migrating its core Elasticsearch infrastructure from an end-of-life Elasticsearch 6 deployment to Elasticsearch 8 on Kubernetes. The legacy setup relied on manual EC2 provisioning and custom scripts, preventing the engineering team from utilizing modern vector search capabilities while incurring substantial operational overhead. Tinder implemented Elastic Cloud on Kubernetes integrated with its in-house Infrastructure as Code framework, Scaffold, while refactoring custom Java ranking plugins to handle Elasticsearch 8 breaking changes like prohibited negative scoring. The migration was validated through offline benchmarking, online verification, and a three-wave A/B testing rollout. This transition completed with zero outages and under 0.2% data discrepancy, reducing p99 search latency by 12% to 56% and cutting annual infrastructure costs by over one million dollars.


### [How the Tinder iOS App reduced the size of our localizations by 95% using Emerge](https://yomu.fyi/post/how-the-tinder-ios-app-reduced-the-size-of-our-localizations-by-95-usi.md)
- Company: [Tinder](https://yomu.fyi/company/tinder.md)
- Author: Tinder
- Published: Feb 26, 2025

Supporting over 50 languages across numerous statically linked targets led to a substantial build size footprint in Tinder's iOS application. Because Apple's code signing mandates a minimum 4KB per file, shipping dozens of localized files per target inflated the final application package. Tinder addressed this by stripping comments and whitespace, merging localized strings into a single file per language via custom Bazel rules and Aspects, and compressing the strings using Emerge's SmallStrings tool into LZFSE files. The runtime decompresses these files dynamically through existing code-generated string accessors. Consequently, Tinder reduced download size by 10.7MB and install size by 51.3MB with no impact on developer workflows.


### [Sharing Tinder’s latest contributions to the open source community](https://yomu.fyi/post/sharing-tinder-s-latest-contributions-to-the-open-source-community.md)
- Company: [Tinder](https://yomu.fyi/company/tinder.md)
- Author: Tinder
- Published: Jan 29, 2025

Tinder open-sourced several iOS development repositories, including Layout, Nodes Architecture Framework, and CombineUI, to share the engineering patterns supporting its iPhone application. As the app expanded across diverse device profiles and scale, engineering teams faced reliability, consistency, and memory challenges under their legacy architecture. In response, Tinder developed Nodes, a plugin-based architecture framework using compile-time dependency injection and lifecycle hooks that enforce complete memory release upon feature dismissal. For interface construction, Tinder created Layout, a domain-specific Auto Layout wrapper offering declarative syntax for UIKit views to eliminate storyboard merge conflicts while preserving native capabilities. The resulting stack enables isolated testing of business logic, native reactive event binding, and incremental adoption of SwiftUI across the codebase.


### [How Tinder Eased Development Pain With Ignis](https://yomu.fyi/post/how-tinder-eased-development-pain-with-ignis.md)
- Company: [Tinder](https://yomu.fyi/company/tinder.md)
- Author: Tinder
- Published: Nov 15, 2024

Managing hundreds of microservices with disparate configurations forced Tinder engineers to deploy code to staging environments to verify every change, slowing development velocity. To shorten feedback loops, the team created Ignis, a Go-based CLI tool that lets engineers run an isolated service locally while proxying ingress and egress traffic through a multi-tenant development Kubernetes cluster. Ignis pairs with an API gateway for client testing and uses a custom Smart Router proxy to dynamically intercept downstream gRPC and HTTP requests via Kubernetes informers and header propagation. Since launching in 2019, the tool enabled Tinder to eliminate a dozen staging environments, decrease cloud spend, and accelerate onboarding, followed by a V2 release adding remote IDE support and monitoring.


### [Identifying vulnerabilities in GitHub Actions & AWS OIDC Configurations](https://yomu.fyi/post/identifying-vulnerabilities-in-github-actions-aws-oidc-configurations.md)
- Company: [Tinder](https://yomu.fyi/company/tinder.md)
- Author: Tinder
- Published: Apr 18, 2023

In 2021, GitHub released OpenID Connect support for GitHub Actions to let workflows retrieve short-lived cloud session tokens instead of storing static secrets. Tinder Security Labs discovered widespread IAM role misconfigurations that allow external repositories to assume target roles and access AWS resources. The primary issue stems from IAM trust policies that authenticate the GitHub identity provider but omit strict validation on the subject claim. Researchers located exposed role identifiers via public workflow searches and confirmed that arbitrary external GitHub Actions workflows could assume them, including roles within AWS official repositories. Remediation requires configuring trust policies to restrict the audience and validate repository namespaces, while unauthorized assumptions can be detected in CloudTrail logs.


### [Building Obsidian, Tinder’s Design System](https://yomu.fyi/post/building-obsidian-tinder-s-design-system.md)
- Company: [Tinder](https://yomu.fyi/company/tinder.md)
- Author: Tinder
- Published: Jan 9, 2023

As Tinder scaled over a decade, maintaining visual consistency across its client applications became unsustainable and increased engineering overhead. To address this, the UI Platform team developed Obsidian, a unified design system combining design tokens, reusable components, and documentation. Designers define base and context tokens in Figma using the Tokens Studio plugin, which are then transformed by Style Dictionary into native artifacts for iOS, Android, and Web. Web developers integrate these tokens using Atomizer to generate static stylesheets, while a Zeroheight documentation portal and a custom token lookup tool assist legacy migrations. The ongoing migration has streamlined collaboration between designers and engineers, resolved styling ambiguities, and improved color contrast accessibility across platforms.


### [How to Categorize and Prevent Risks of Sensitive Links in URLScan](https://yomu.fyi/post/how-to-categorize-and-prevent-risks-of-sensitive-links-in-urlscan.md)
- Company: [Tinder](https://yomu.fyi/company/tinder.md)
- Author: Tinder
- Published: Nov 7, 2022

Security integrations with URLScan can accidentally index sensitive links when API calls are executed with public visibility. Tinder Security Labs constructed targeted queries to uncover exposed links across file-sharing services, enterprise ticketing platforms, and single sign-on portals. Investigations revealed that exposed links included document magic links containing contracts and bank details, as well as active new-hire registration links that allowed attackers to complete registration workflows and configure two-factor authentication. In one SSO query alone, researchers discovered 1,300 indexed invitation links, with 20 to 50 new links appearing daily. The researchers collaborated with URLScan to purge the exposed indexes from public searches and advised organizations to configure security scanning tools to use private or unlisted visibility settings.