---
title: "Latest reads"
description: "The engineering internet, summarised so you can actually read it."
---

# Latest reads
> The engineering internet, summarised so you can actually read it.

## Articles

### [Typeahead Search at Nextdoor](https://yomu.fyi/post/typeahead-search-at-nextdoor.md)
- Company: [Nextdoor](https://yomu.fyi/company/nextdoor.md)
- Author: Jerry Tian
- Published: Jul 6, 2022
- Type: Problem & solution

Nextdoor built a proximity-based autocomplete service to power typeahead search and mention features across its hyperlocal platform for hundreds of millions of entities, including users and businesses. The system shards geographic data using Uber's open-source H3 geohashing library and stores prefix indexes in memory using Redis sorted sets. By adopting a Command Query Responsibility Segregation architecture, ingestion writes are processed on Redis primary nodes and replicated to read-only search nodes with under 10 milliseconds of replication lag. Dedicated APIs handle indexing, typeahead lookups, and ranking before returning hydrated results. Operating since August 2021, the service processes hundreds of millions of monthly typeahead queries while maintaining a P95 search latency below 30 milliseconds.


### [Supabase Beta June 2022](https://yomu.fyi/post/supabase-beta-june-2022.md)
- Company: [Supabase](https://yomu.fyi/company/supabase.md)
- Author: Ant Wilson
- Published: Jul 6, 2022
- Type: Announcement

Supabase released its Beta June 2022 updates covering developer tooling, authentication, and infrastructure changes. The team decoupled Supabase Auth Helpers into dedicated packages for Next.js and React, while introducing project pause and restore features to enable unlimited free projects. Developers can now initiate project creation directly through the Supabase CLI and toggle realtime updates from the table editor side panel. Authentication updates include exposing client IP addresses in audit logs, introducing an auth.jwt function, bubbling PostgreSQL errors from GoTrue, and deprecating older authentication functions. Additionally, infrastructure migrations are underway to support multiplayer features, accompanied by community-led tutorials, sponsorships, and platform growth reaching fifty thousand GitHub stars.


### [Shopify and Open Source: A Mutually Beneficial Relationship](https://yomu.fyi/post/shopify-and-open-source-a-mutually-beneficial-relationship.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Jul 6, 2022
- Type: Explainer

Shopify describes its relationship with Ruby, Rails, and the open-source community as mutually beneficial, linking the company’s success to its Rails foundation and its engineering culture to the Rails Doctrine. It frames a 100-year company ambition around making Ruby and Rails viable for large teams, mature codebases, millions of lines of code, and billions of web requests through production performance, architecture guidance, upgrades, tooling, and selective typing. To support that goal, Shopify contributes projects and initiatives spanning developer tooling, gradual typing, VS Code support, automated upgrades, YJIT, Ruby performance work, TruffleRuby collaboration, $500,000 in research funding, Bundler and RubyGems, and RubyGems.org security. The post argues that company participation improves engineering skills, application longevity, and influence over foundational software, while describing contributors who range from occasional participants to full-time maintainers.


### [The Story Behind Shopify’s Isospin Tooling](https://yomu.fyi/post/the-story-behind-shopify-s-isospin-tooling.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Jul 5, 2022
- Type: Explainer

Shopify’s Isospin is the systemd-based core of Spin, its in-house cloud development platform, designed to run multiple applications inside a single Linux VM. The earlier implementation relied on shell scripts, but growing application counts made it difficult to split applications into components, express dependencies, schedule jobs, and isolate processes. Isospin uses systemd unit graphs, targets, template units, and generators to create service configurations dynamically, including per-application copies of dependencies such as MySQL and Elasticsearch. Additional tooling assigns semi-stable ports by hashing service names and uses systemd readiness notifications, including a notify-port wrapper that checks HTTP availability; the resulting system reuses systemd’s dependency and health mechanisms, with more complex cross-application relationships under investigation.


### [Flutter Tutorial: building a Flutter chat app](https://yomu.fyi/post/flutter-tutorial-building-a-flutter-chat-app.md)
- Company: [Supabase](https://yomu.fyi/company/supabase.md)
- Author: Tyler Shukert
- Published: Jun 30, 2022
- Type: Tutorial

Developers can construct cross-platform real-time chat applications for iOS, Android, and web by pairing Flutter with Supabase. The architecture relies on Supabase to manage authentication and provide direct SDK access to a Postgres database without requiring custom backend server code. The database schema defines profiles with regex validation constraints and a messages table configured for live subscriptions through Postgres publication settings. Flutter clients capture user input, insert new records into the messages table, handle database exceptions, and format chat bubbles with dynamic timestamps. While this initial setup implements user registration and message broadcasting in a shared room, securing chat rooms requires subsequent row-level security configuration.


### [Graph Networks - 10X investigation with Graph Visualisations](https://yomu.fyi/post/graph-networks-10x-investigation-with-graph-visualisations.md)
- Company: [Grab](https://yomu.fyi/company/grab.md)
- Author: Fujiao Liu
- Published: Jun 30, 2022
- Type: Problem & solution

Fraud detection traditionally required investigators to manually combine large datasets from disparate anti-fraud systems using statistical methods, which proved slow and inefficient. Grab built an interactive Graph Visualisation platform to transform raw records into connected visual maps without requiring manual queries or switching tools. The platform manages over three billion nodes and edges, allowing investigators to selectively expand data points and replay chronological events using temporal filters. Visual relationship mapping helps teams verify account appeals, uncover device-sharing rings, and spot anti-money laundering behavior through transaction density patterns.


### [The Serverless Server](https://yomu.fyi/post/the-serverless-server.md)
- Company: [Fly.io](https://yomu.fyi/company/fly-io.md)
- Published: Jun 30, 2022
- Type: Explainer

The post explains what “serverless” means by reconstructing the machinery beneath a Lambda-like platform. It starts with bare-metal x86 servers, a Type 1 hypervisor, and services for placement, VM management, request forwarding, and function execution; dedicated customer workers, shared warm pools, rate limits, and container-style isolation address multitenancy, cold starts, and bursty demand. The runtime design uses object storage for function code, chroot, privilege dropping, namespaces, seccomp, cgroups, and freezing to constrain idle instances and workloads. Its limits on initialization, invocation duration, and idle lifecycles support migration away from unhealthy instances but disadvantage applications with expensive startup, dynamic local caches, or uncertain response times.


### [How to Build Trust as a New Manager in a Fully Remote Team](https://yomu.fyi/post/how-to-build-trust-as-a-new-manager-in-a-fully-remote-team.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Jun 30, 2022
- Type: Tutorial

The post explains why building trust as a new manager in a fully remote organization differs from joining a team with established relationships: passive cues and casual interactions are harder to observe, so remote work requires intentionality. The proposed 90-day plan focuses on the environment during the first 30 days, the team during the next 60, and the manager thereafter. Early actions include pairing sessions, one-on-ones, peer-group sessions, understanding the wider organization, setting up remote tools, and building cross-company relationships. Team leadership emphasizes spending time with members, using asynchronous communication for productivity and synchronous meetings for connection, and creating psychological safety through open communication and transparent discussion of failures. The final phase addresses FOMO, workday design, and experimentation through feedback and reflection.


### [Policy Gradient with PyTorch](https://yomu.fyi/post/policy-gradient-with-pytorch.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Thomas Simonini
- Published: Jun 30, 2022
- Type: Tutorial

Policy gradient algorithms optimize reinforcement learning policies directly without learning intermediate action-value functions. Instead of assigning discrete Q-values to actions, these methods parameterize a stochastic policy and apply gradient ascent on an objective score function. This setup eliminates manual exploration tuning, resolves perceptual aliasing in identical states, and naturally accommodates continuous or high-dimensional action spaces. The Reinforce Monte Carlo policy gradient algorithm operationalizes this approach by collecting full episodic trajectories and adjusting parameters along the gradient of the log-action probabilities scaled by return. Practitioners implement this algorithm using PyTorch to evaluate agent robustness across environments like CartPole-v1, PixelCopter, and Pong.


### [Visualizing Supabase Data using Metabase](https://yomu.fyi/post/visualizing-supabase-data-using-metabase.md)
- Company: [Supabase](https://yomu.fyi/company/supabase.md)
- Author: Ant Wilson
- Published: Jun 29, 2022
- Type: Tutorial

Organizations seeking to analyze database records can bypass code-heavy Python visualization libraries by connecting a Supabase backend directly to Metabase. Deploying the open-source Metabase Docker container exposes an initial setup interface on default port 3000, allowing administrators to input PostgreSQL connection credentials retrieved from Supabase database settings. Once connected, Metabase automatically surfaces table insights and automated x-rays across the public schema, exposing metrics such as inventory count ranges, price distributions, and column-specific statistics without requiring manual queries. For specialized analytics, users can execute custom SQL joins across relational tables like Product and Vendor to render tailored visual dashboard formats, including configurable bar charts mapped to designated axis fields.


### [Navigating Recurring Payments in India: A Backend Perspective](https://yomu.fyi/post/navigating-recurring-payments-in-india-a-backend-perspective.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Jun 29, 2022
- Type: Explainer

India’s October 2021 Reserve Bank of India (RBI) directive required recurring payments to use payer-authorized e-mandates, Additional Factor of Authentication (AFA), and pre-debit notifications at least 24 hours before charges. Shopify’s billing platform therefore had to model e-mandates, support recurring and one-time payments across cards and Unified Payments Interface (UPI), and integrate a local payment provider. The payment service reused its source object for the e-mandate token, recorded the temporary authorization as a charge for auditability, and refunded it asynchronously. To avoid two consecutive card authentication flows, the team used recurring-payment tokenization for both payment paths, accepting an atypical notification experience as a short-term trade-off; UPI required asynchronous webhook-driven handling and a hard mandate limit. After the beta launch, billing-payment success rates in India increased from pre-project levels, and the team said it would soon make UPI generally available to Indian merchants.


### [Liftoff! How to get started with your first ML project 🚀](https://yomu.fyi/post/liftoff-how-to-get-started-with-your-first-ml-project.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Nima Boscarino
- Published: Jun 29, 2022
- Type: Tutorial

Beginners in machine learning frequently face difficulties when selecting a framework and defining the scope of their initial hands-on project. Sentence Transformers provides an accessible starting point by computing dense vector representations for sentences, paragraphs, and images, enabling semantic search through cosine similarity. A structured four-step strategy guides practitioners through listing library capabilities, identifying compelling datasets, selecting a familiar secondary tool, and brainstorming project concepts. Applying this framework, a song lyrics dataset was paired with Gradio Blocks to build a prompt-based playlist generator. Developing this application required evaluating pre-trained models, hosting generated embeddings on Hugging Face Spaces, and utilizing multi-processor support to accelerate embedding generation.


### [Partial data dumps using Postgres Row Level Security](https://yomu.fyi/post/partial-data-dumps-using-postgres-row-level-security.md)
- Company: [Supabase](https://yomu.fyi/company/supabase.md)
- Author: Paul Copplestone
- Published: Jun 28, 2022
- Type: Tutorial

Dumping full production databases onto local development machines creates severe security issues once applications hold real user data. To safely generate local seed data, developers can leverage PostgreSQL Row Level Security to restrict data access. The process involves provisioning a dedicated database user with select privileges on the target schema and tables. Next, administrators enable row-level security policies on those tables to filter records using criteria such as specific primary keys, email domain patterns, date intervals, or boolean flags. Finally, running pg\_dump with the restricted user credentials and the --enable-row-security flag produces a sanitized seed.sql file containing only approved records.


### [Accelerate Large Model Training using DeepSpeed](https://yomu.fyi/post/accelerate-large-model-training-using-deepspeed.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Sourab Mangrulkar, Sylvain Gugger
- Published: Jun 28, 2022
- Type: Tutorial

Training large models on hardware with limited GPU memory frequently causes out-of-memory errors when using standard Distributed Data Parallel. To solve this bottleneck, Hugging Face Accelerate integrates DeepSpeed ZeRO data parallelism to shard optimizer states, gradients, and model parameters across workers. For a 900-million-parameter DeBERTa model, ZeRO Stage 2 increased the maximum per-device batch size from eight to forty while achieving a 3.5-fold training speedup over DDP without degrading accuracy or F1 score. Advanced configurations allow sequence-to-sequence chatbot finetuning and full ZeRO Stage 3 CPU offloading for models like the 1.5-billion-parameter GPT-XL, enabling batch size 16 training where DDP fails. Accelerate enables these memory optimizations through simple configuration files and the accelerate launch command with minimal or zero code modifications.


### [Announcing Evaluation on the Hub](https://yomu.fyi/post/announcing-evaluation-on-the-hub.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Lewis Tunstall, Abhishek, Tristan Thrush, Sasha Luccioni, Leandro von Werra, Nazneen Rajani, Aleksandra Piktus, Omar Sanseviero, Douwe Kiela
- Published: Jun 28, 2022
- Type: Announcement

Hugging Face introduced Evaluation on the Hub, a no-code tool designed to streamline the evaluation of machine learning models across diverse datasets. Traditional evaluation approaches often suffer from reproducibility issues, implementation inconsistencies, and cumbersome workflows across varied metrics and datasets. Powered by AutoTrain and Hugging Face Spaces, the service allows users to configure tasks, map dataset columns, select evaluation metrics, and run tests directly from dataset pages. Completed evaluations automatically open pull requests on the respective model cards to encode standardized verification metadata and update public dataset leaderboards. This system establishes consistent benchmarking pipelines across tasks like image classification, text summarization, and named entity recognition without requiring local code execution.


### [Perspectives on Onboarding: Joining Shopify as an Engineering Leader](https://yomu.fyi/post/perspectives-on-onboarding-joining-shopify-as-an-engineering-leader.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Jun 27, 2022
- Type: Explainer

Shopify’s onboarding program is presented as an alternative to the common first-day experience of receiving a laptop, documents, and a team without enough context. It gives new engineers, including engineering leaders, a structured period of roughly six weeks to learn the product, merchants, engineering practices, and company values, including by creating test shops and using the admin. Avanti Ketkar and Maria Robledo describe how this preparation helped them connect onboarding content to later work, ship a pull request after using a test shop, and build relationships and trust in a remote environment. Their accounts also cover the adjustment to learning before delivering impact, moving from a .NET background to Ruby and Rails, managing time zones, and keeping technical craft relevant while leading teams.


### [Logbook - 2022-06-23](https://yomu.fyi/post/logbook-2022-06-23.md)
- Company: [Fly.io](https://yomu.fyi/company/fly-io.md)
- Published: Jun 23, 2022
- Type: Announcement

Fly.io's June 23, 2022 logbook records a broad set of platform, dashboard, and flyctl updates. It announces YUL (Montreal, QC, Canada), adds Laravel and Laravel Octane detection to fly launch, and improves plain Docker build output when NO\_COLOR=1 is set. Backend work optimizes API queries, reduces repeated app-image loads, moves app-discard cleanup into a retryable job, and adds SQL comments to help investigate database data-lock issues. The release also documents diagnostics, makes compliance documents public to prospective customers, and improves fly-proxy’s Rust coverage and PROXYPROTO v2 TLV support. Fixes address fly.toml environment variables, organization deletion, password-reset redirects, app secrets listing, metrics after fly apps move, dashboard errors, malformed SSL TLVs, and overzealous email risk checks.


### [Getting Started With Embeddings](https://yomu.fyi/post/getting-started-with-embeddings.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Omar Espejel
- Published: Jun 23, 2022
- Type: Tutorial

Embeddings represent unstructured information such as text and images as numerical vectors in a shared semantic space. To demonstrate their utility, a simple semantic search engine is built over US Social Security Medicare frequently asked questions. The system generates 384-dimensional vector representations for thirteen FAQ entries by dispatching POST requests to the Hugging Face Inference API using the sentence-transformers/all-MiniLM-L6-v2 model. Incoming user queries are converted into matching vector representations and evaluated against stored dataset vectors using the util.semantic\_search function from the Sentence Transformers library. By calculating cosine similarity scores, the system retrieves and ranks the five most semantically relevant questions without requiring custom keyword rules or massive labeled training sets.


### [How We Built Hydrogen: A React Framework for Building Custom Storefronts](https://yomu.fyi/post/how-we-built-hydrogen-a-react-framework-for-building-custom-storefront.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Jun 22, 2022
- Type: Explainer

Hydrogen is a React framework for building custom Shopify storefronts, created to help merchants use the Storefront API without giving up capabilities associated with Liquid storefronts. Shopify built it around React Server Components and React 18’s streaming server-side rendering, using component-level data fetching, a preload cache to parallelize nested queries, and experimental loggers for query waterfalls and unused GraphQL properties. The framework evolved through more than 1,200 pull requests and 3,000 commits, with rigid components removed after feedback and nearly all exported GraphQL fragments eliminated to make queries more discoverable. The post reports that some demo store routes cut load time in half and that Hydrogen is used in production at Allbirds, Shopify Supply, Shopify Hardware, and Shopify, while future plans include a new router and incremental adoption from Liquid storefronts.


### [Introducing ShopifyQL: Our New Commerce Data Querying Language](https://yomu.fyi/post/introducing-shopifyql-our-new-commerce-data-querying-language.md)
- Company: [Shopify](https://yomu.fyi/company/shopify.md)
- Author: 2023-10-18
- Published: Jun 22, 2022
- Type: Announcement

Shopify introduces ShopifyQL, a commerce-focused querying language intended to make data exploration accessible to Shopify Plus merchants without data science or coding backgrounds. It addresses the limits of dashboards and reports, which show what happened but may not explain why, and simplifies access to modeled commerce datasets that would otherwise require SQL and data-lifecycle knowledge. Its syntax uses clauses such as FROM, SHOW or VISUALIZE, BY, WHERE, SINCE, UNTIL, ORDER BY, COMPARE TO, and LIMIT, with direct charting, commerce-specific date ranges, and planned native period comparisons. ShopifyQL is available through the ShopifyQL Notebooks first-party app, while GraphQL APIs let partners submit queries and receive results from the underlying datasets. Shopify says it will use the language across Shopify Admin analytics and plans features including more visualizations, pivoting, and aggregate conditions.


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