---
title: "Architecture"
description: "834 posts about Architecture, summarised, each linking to the original."
---

# Architecture
> 834 posts about Architecture, summarised, each linking to the original.

## Articles

### [Turbo-Charging ML Development](https://yomu.fyi/post/turbo-charging-ml-development.md)
- Company: [Ramp](https://yomu.fyi/company/ramp.md)
- Author: Ryan Stevens, Ryne Carbone
- Published: Feb 10, 2025
- Type: Problem & solution

Ramp describes Turbo, a YAML-based configuration system created to reduce the time and engineering effort required to deploy machine-learning models while preserving reproducibility and explainability. Its abstraction represents end-to-end feature and model pipelines, datasets, and shared train and predict jobs; Python entities and aggregates built with Pydantic are materialized through JobSpec and executed locally or remotely before models are stored. A developer can run a training workflow with a YAML file and a few lines of code, then adapt the same schema for prediction by changing a few configuration lines. The first Credit Risk model required nearly four months and more than 3,000 lines of deployment code; with Turbo, new models deploy in under five minutes using about 40 YAML lines on average. The system also standardizes practices such as holiday alignment in time-series models and supports nearly 20 deployed models built by nine developers.


### [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
- Type: Announcement

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.


### [Image replacement in Canva designs using reverse image search](https://yomu.fyi/post/image-replacement-in-canva-designs-using-reverse-image-search.md)
- Company: [Canva](https://yomu.fyi/company/canva.md)
- Author: Sam Jacobs
- Published: Jan 28, 2025
- Type: Problem & solution

Canva needed an automated way to replace media in design templates, such as when third-party licensing partnerships expire across more than 150 million images. Existing recommendation engines, perceptual hashing, and text metadata searches failed to capture visual similarity hierarchies or ensure replacement relevance. To build a reverse image search system, engineers evaluated embedding models including CLIP, ViTMAE, DreamSim, CaiT, and DINOv2 alongside an external vector database supporting metadata filtering. Evaluation on sample datasets identified DINOv2 as the best model for preserving subjects, background context, and color tones in photos. Integrated into the Template Assistant as a human-in-the-loop tool, the automated suggestions increased image replacement speeds by 4.5 times during initial pilot testing.


### [Five years of React Native at Shopify](https://yomu.fyi/post/five-years-of-react-native-at-shopify.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Jan 13, 2025
- Type: Explainer

Shopify reviews five years of using React Native (RN) as its mobile strategy, adopted to avoid duplicating features across iOS and Android, improve talent portability, and ship more value. Over that period, all of its apps migrated to RN through team-led, non-uniform plans, while native code remained part of the architecture rather than an alternative to eliminate. The company reports sub-500ms P75 screen loads in the Shopify app, similar performance across its apps, and more than 99.9% crash-free sessions, while noting that performance depends on applying sound patterns. Its experience credits hot reloading and TypeScript with developer productivity and cross-platform staffing, but identifies debugging, RN upgrades, and third-party dependency maintenance as costs. Shopify now emphasizes shared libraries, native expertise for platform-specific work, continued New Architecture adoption, and collaboration with the RN ecosystem.


### [The foundations of Canva’s continuous data platform with Snowpipe Streaming](https://yomu.fyi/post/the-foundations-of-canva-s-continuous-data-platform-with-snowpipe-stre.md)
- Company: [Canva](https://yomu.fyi/company/canva.md)
- Author: Jack Caperon
- Published: Jan 6, 2025
- Type: Problem & solution

As Canva expanded to over 200 million monthly active users, ingestion throughput reached 25 billion records daily, causing AWS Data Firehose costs to consume nearly half of the product analytics platform budget. To reduce these expenses and eliminate intermediate file staging, the engineering team integrated Snowflake's Snowpipe Streaming directly with their Java-based Kinesis Data Streams pipeline. The architecture streams records directly into Snowflake tables using logical channels with offset checkpoints while configuring client buffering up to a five-minute maximum lag. In handling Kinesis Client Library edge cases, record processors coordinate with the LeaseCoordinator to drop leases when channels become unhealthy. Operating in production for over six months, the system ingested more than 20.35 petabytes of data, decreased query latency to roughly ten minutes, and reduced overall cloud spend by 45 percent.


### [Developing a modern architecture for energy utilities with embedded finance](https://yomu.fyi/post/developing-a-modern-architecture-for-energy-utilities-with-embedded-fi.md)
- Company: [Stripe](https://yomu.fyi/company/stripe.md)
- Author: Rajan Patel
- Published: Dec 17, 2024
- Type: Explainer

Energy utilities can use embedded finance to create marketplace-like experiences for tariffs, solar installations, smart-home devices, storage, and related services while capturing more energy-related revenue. The proposed foundation combines Stripe Online Payment Flows, Billing, Payments, Connect, and Data Pipeline with AWS serverless services, including Lambda, EventBridge, DynamoDB, Redshift, S3, and QuickSight. A tariff enrollment or payment can trigger webhooks and real-time event processing, while transaction and customer data support dashboards, usage insights, personalized recommendations, subscriptions, and broader partner offerings. The architecture also describes PCI Level 1 security, encryption, Radar, Strong Customer Authentication, AWS IAM, KMS, Shield, WAF, Config, Security Hub, and CloudWatch for compliance and monitoring. It concludes that this integrated payment, analytics, and security foundation can help utilities improve customer engagement, support sustainable programs, and develop new revenue streams.


### [How do I store inventory data in my Stripe application](https://yomu.fyi/post/how-do-i-store-inventory-data-in-my-stripe-application.md)
- Company: [Stripe](https://yomu.fyi/company/stripe.md)
- Author: Ben Smith
- Published: Dec 16, 2024
- Type: Tutorial

The DevRel Swag Store uses Stripe payments and AWS services to keep product inventory accurate and visible in near real time. Stripe products retain core payment information, while Amazon DynamoDB stores inventory and other attributes, keyed by Stripe product ID and store ID; EventBridge routes payment events to Lambda, which atomically decrements stock and publishes updates through AWS IoT Core to the frontend. DynamoDB condition expressions prevent decrements when stock is insufficient, while post-payment validation and refunds address the delay before a Stripe Payment Link is disabled, although Stripe fees may be non-refundable. A custom Payment Intent flow can check stock before payment, authorize funds with manual capture for up to seven days, update inventory after payment success, and then capture the charge.


### [The science of routing print orders](https://yomu.fyi/post/the-science-of-routing-print-orders.md)
- Company: [Canva](https://yomu.fyi/company/canva.md)
- Author: Constantinos Kavadias
- Published: Dec 10, 2024
- Type: Problem & solution

Canva's global print network requires selecting optimal suppliers to balance delivery times, packaging counts, and environmental emissions. To resolve these challenges before user checkout, the engineering team designed a modular routing architecture that decouples graph construction, decision logic, and path traversal. During graph traversal, the system generates action objects capturing forward paths and decision query results, which are compiled into timestamped routing logs in blob storage for asynchronous auditing. Utilizing preprocessed graph queries alongside ElastiCache, Redis, and database read replicas, the infrastructure sustains high-throughput evaluation without coupling cost logic to traversal code. As a result, print routing completes within an average of 50 milliseconds at the 99th percentile during peak usage while maintaining 99.999% data availability.


### [Growing your Stripe integration With Event Destinations](https://yomu.fyi/post/growing-your-stripe-integration-with-event-destinations.md)
- Company: [Stripe](https://yomu.fyi/company/stripe.md)
- Author: Ben Smith
- Published: Oct 31, 2024
- Type: Explainer

Stripe Event Destinations, now in general availability and rolling out to all accounts, lets companies extend payment workflows without changing existing integrations. The post explains how Stripe events can be sent either to an AWS account through Amazon EventBridge or to a webhook endpoint, with EventBridge routing selected events to services such as AWS Lambda, Step Functions, and SQS. Event filtering, logging, transformation, and built-in security reduce the need to operate webhook servers and verify signatures in application code. Serverless Lambda functions can add custom logic and connect to DynamoDB, S3, or SNS, supporting examples including date-limited memberships, partial student payments, and real-time tipping broadcasts through AWS IoT Core and WebSockets. The resulting architecture is presented as flexible and scalable for variable or growing event volumes while preserving the underlying Stripe integration.


### [Managing SaaS access control with Stripe’s Entitlements API](https://yomu.fyi/post/managing-saas-access-control-with-stripe-s-entitlements-api.md)
- Company: [Stripe](https://yomu.fyi/company/stripe.md)
- Author: Hidetaka Okamoto
- Published: Oct 31, 2024
- Type: Tutorial

Managing access rights across multiple SaaS pricing plans can require maintaining feature lists, subscription and pricing relationships, and related database resources as plans or features change. The post presents Stripe’s Entitlements API as a way to register features, associate them with Stripe Products, and retrieve active entitlements for a customer’s subscriptions. Its example defines Free, Personal, and Business monthly products priced at $0, $98, and $980, then maps article-viewing and business-report features to those products using Stripe CLI commands in Workbench. Customer entitlement checks can support application authorization, while entitlements.active\_entitlement\_summary.updated webhooks expose before-and-after permission data for workflows triggered by plan changes or cancellations.


### [How we reduced peak memory and CPU usage of the product configuration management SDK](https://yomu.fyi/post/how-we-reduced-peak-memory-and-cpu-usage-of-the-product-configuration.md)
- Company: [Grab](https://yomu.fyi/company/grab.md)
- Author: Ram Dilip Pradhan
- Published: Oct 30, 2024
- Type: Problem & solution

GrabX’s product configuration SDK used substantial memory and CPU because every client downloaded, decoded, and loaded a single JSON file containing configurations for all services, even when it needed only a small subset. The design also regenerated and fetched complete files every minute, while decoding a file larger than 100 MB could starve request handling and increase P99 latency. The proposed redesign partitions data by service, stores each configuration in its own JSON file and S3 prefix, and adds service-level changelogs so SDKs subscribe only to required services and apply targeted updates. Benchmarking across varied configuration sizes found potential reductions of up to 70% in memory utilisation and more than 50% in maximum CPU utilisation. Further work is planned to reduce SDK initialisation time.


### [How We Built the BFCM 2023 Globe](https://yomu.fyi/post/how-we-built-the-bfcm-2023-globe.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Oct 30, 2024
- Type: Explainer

The 2023 BFCM Globe is a real-time visualization of purchases made through Shopify-powered merchants worldwide, with animated arcs, city dots, fireworks, camera movement, atmospheric noise, stars, and a custom material. Performance was a central concern because the earlier approach used a separate mesh and draw call for every arc, causing more than 1,000 simultaneous arcs to slow some mobile devices. The revised arc system uses instancing, interleaved per-arc attributes, and vertex-shader Bézier deformation, allowing tens of thousands of arcs in one draw call and an initial benchmark of up to one million arcs on an M1 laptop. Other effects were similarly consolidated, including billboarded point particles for cities and single-draw-call fireworks, while 2D psrdnoise and a stripped-down shader reduced rendering cost. The result combines richer visuals with substantially greater rendering capacity.


### [Improving Compute Sustainability: A Case Study](https://yomu.fyi/post/improving-compute-sustainability-a-case-study.md)
- Company: [Two Sigma](https://yomu.fyi/company/two-sigma.md)
- Author: Emily Majewski
- Published: Oct 7, 2024
- Type: Problem & solution

Two Sigma's large computing footprint drives significant energy consumption and carbon emissions, particularly across live trading applications that require continuous real-time market data caching. To address this overhead without sacrificing performance, engineering teams used a routine hardware refresh to transition from legacy single-process machines to denser multi-core server configurations. By replacing roughly 60 legacy hosts with 28-core processor hardware, the team distributed baseline power draw over more cores and eliminated underutilized compute capacity. This architectural consolidation reduced absolute power consumption across production hosts by 66%, dropping electricity usage from 27 MWh in January 2023 to 10 MWh in January 2024. The initiative subsequently established an annual sustainability rationalization practice for hardware budgeting across the organization.


### [Evolution of Catwalk: Model serving platform at Grab](https://yomu.fyi/post/evolution-of-catwalk-model-serving-platform-at-grab.md)
- Company: [Grab](https://yomu.fyi/company/grab.md)
- Author: Vishal Sharma
- Published: Oct 1, 2024
- Type: Problem & solution

Grab developed and scaled Catwalk, an internal machine learning model serving platform, to address operational bottlenecks, low resource utilization, and deployment friction between data scientists and backend engineers. The platform transitioned from an admin-managed TensorFlow Serving setup into a low-code self-service system supporting PyTorch and ONNX, before replacing complex Helm charts with Kubernetes Custom Resource Definitions for declarative, blue-green deployment orchestration. To support complex business workflows and multi-model applications, Grab subsequently introduced Catwalk Orchestrator with bundled deployments that allow individual services to scale independently. Across two years, the orchestrator architecture expanded to 200 deployed applications serving approximately 1,400 production machine learning models.


### [Choosing the right sandbox strategy for your organization](https://yomu.fyi/post/choosing-the-right-sandbox-strategy-for-your-organization.md)
- Company: [Stripe](https://yomu.fyi/company/stripe.md)
- Author: Ben Smith
- Published: Sep 26, 2024
- Type: Explainer

Stripe sandboxes provide isolated environments for testing Stripe features without affecting a live integration, with access controls for the people who use them. Each live account can have up to five sandboxes, which admins can create, name, configure by copying selected live-account settings, and delete when no longer needed. The guide describes a staged setup for startups and small teams, using separate environments for development, integration testing, user acceptance testing, and spare capacity, while larger organizations may assign sandboxes to departments and rotate them between projects. It also presents an iterative model in which teams prototype, collect stakeholder feedback, retest changes, and document results. The recommended strategy depends on team size, organizational structure, workflow, and development methodology.


### [Bringing Grab’s Live Activity to Android: Enhancing user experience through custom notifications](https://yomu.fyi/post/bringing-grab-s-live-activity-to-android-enhancing-user-experience-thr.md)
- Company: [Grab](https://yomu.fyi/company/grab.md)
- Author: Jessica Sean
- Published: Sep 23, 2024
- Type: Problem & solution

Grab designed an equivalent to iOS Live Activities for Android to provide real-time order tracking outside the app. Because Android lacks Apple's native ActivityKit push token system, the team substituted push tokens with placeholder values to maintain technical consistency across platforms and preserve backend push targeting via their Hedwig service. For the user interface, engineering selected custom notifications over floating views because custom notifications avoid intrusive screen usage and do not require the 'Draw over other apps' permission. The client implementation separates responsibilities across dedicated classes: LiveActivityIntegrationManager handles token registration across business verticals, LiveActivityAttributes encapsulates UI configuration, and LiveActivityManager maps payloads to Android NotificationManager instances. The solution launched for Food, Mart, Express, and Transport verticals.


### [Unveiling the process: The creation of our powerful campaign builder](https://yomu.fyi/post/unveiling-the-process-the-creation-of-our-powerful-campaign-builder.md)
- Company: [Grab](https://yomu.fyi/company/grab.md)
- Author: Jie Zhang
- Published: Sep 10, 2024
- Type: Explainer

Grab details the event processing architecture behind Trident, its internal marketing campaign platform that evaluates If This, Then That (IFTTT) logic over Kafka streams. The core processing unit is a treatment consisting of an event, optional conditions, and actions. Complex campaign capabilities—such as counters, limits, and delays across multiple hours via recursive SQS message scheduling—are assembled from multiple coordinated treatments. To simplify campaign creation, Grab introduced a flowchart-like visual builder represented as a JSON node tree that compiles recursively into treatments while persisting node-to-treatment mappings to reconcile edits over time.


### [Tinder API Style Guide — Part 1](https://yomu.fyi/post/tinder-api-style-guide-part-1.md)
- Company: [Tinder](https://yomu.fyi/company/tinder.md)
- Author: Tinder
- Published: Sep 6, 2024
- Type: Explainer

Tinder’s rapid growth and expansion into domain-centric teams produced inconsistent API practices across services, including mixed error conventions, fragmented schemas, uneven versioning, unclear URIs, and weak API contracts. Part 1 presents standards for the RESTful APIs used across the platform, beginning with the URI pattern https://service-mesh-host-name/\[version\]/\[service-name\]/\[resource\]/\[sub-resource\] and guidance on concise, plural, kebab-cased paths. It defines path-prefix versioning, retaining the previous version until clients migrate and creating new versions only for breaking changes such as removing fields, changing types, or renaming fields. The guide also covers HTTP methods, standard and custom request headers, the X-Tinder- naming convention, and request tracing through MDC-populated identifiers and centralized logging. Request and response bodies, status codes, and enforcement tools are reserved for Part 2.


### [Iterating with shadow workspaces](https://yomu.fyi/post/iterating-with-shadow-workspaces.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Arvid Lunnemark
- Published: Sep 1, 2024
- Type: Explainer

Cursor’s shadow workspace addresses the problem of letting AI agents iterate on code without disrupting a developer’s active workspace. The design prioritizes LSP usability—especially lints, definition navigation, and language-server interaction—while also requiring independence, privacy, concurrency, universality, maintainability, and speed. A copied in-memory TextModel was rejected because sharing the user’s language server could introduce copied files into references, duplicate declarations, or miss errors. The implemented approach uses a reusable hidden Electron window for the workspace, routing AI edits through Cursor’s processes and returning lints independently of the visible editor. The post treats runnability as a harder future extension, with folder-proxy designs, platform limitations, and network-level independence still open questions.


### [Peeking under the hood of Stripe Invoicing](https://yomu.fyi/post/peeking-under-the-hood-of-stripe-invoicing.md)
- Company: [Stripe](https://yomu.fyi/company/stripe.md)
- Author: David Edoh-Bedi
- Published: Aug 26, 2024
- Type: Tutorial

Stripe Invoicing’s no-code workflow hides the API calls and invoice state transitions that developers may need to inspect when debugging payment failures. Using Stripe Workbench’s Inspector, Logs, and Events tabs, the walkthrough maps object hierarchies, requests, event payloads, and previous\_attributes across an invoice lifecycle. Creating an invoice in the Dashboard produces a draft Invoice, a separate Invoice Item, an automatically generated Invoice Line Item, and related creation or update events. Sending it creates a Payment Intent and finalizes the invoice from draft to open; charging captures the Payment Intent, creates a Charge, and changes the invoice to paid. Draft invoices can be deleted, while open invoices can be voided, preserving the record and canceling the Payment Intent, and the same Workbench method can be applied to other Stripe API areas.


[Newer posts](https://yomu.fyi/topic/architecture/page/28.md) · [Older posts](https://yomu.fyi/topic/architecture/page/30.md)