Documentation Index
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Rituals Performed
Oracle’s Case Studies page presents Alex Weaver’s most significant engineering challenges as ancient rituals documented on aged parchment. Each case study appears as a scroll card with a paper-texture background, a wax-sealed category badge, and a difficulty rating expressed in moon-phase circles — a new phase filled in for each point of complexity, from crescent (1/5) to full moon (5/5). Clicking a card unfurls it to reveal the full ritual record.Case Study 1: The Great Migration of Legacy Systems
Category: Architecture Ritual — Difficulty: 🌕🌕🌕🌕🌕 (5 / 5)The most complex engagement in the grimoire. This ritual required meticulous preparation, a steady hand, and absolute zero tolerance for downtime.
The Challenge
A production monolith that had grown organically over several years was becoming a liability: deployments took over an hour, a bug in one domain risked cascading failures across the entire system, and onboarding new engineers required weeks of context-building before a single line could safely be changed. The mandate was clear — decompose the monolith into autonomous microservices — but the system could not be taken offline. Customers depended on it around the clock.The Approach
Step 1 — Circle of Protection: End-to-End Test Suite
Step 1 — Circle of Protection: End-to-End Test Suite
Before any code was touched, a comprehensive end-to-end test suite was written to document the existing system’s behavior. Framed as a “circle of protection,” these tests became the single source of truth for what must not change during the migration. Every new microservice had to pass the full suite before a single route was re-pointed.
Step 2 — Strangler Fig Pattern
Step 2 — Strangler Fig Pattern
Rather than rewriting the monolith in one large-bang release, the strangler fig pattern was applied: new microservices were built alongside the monolith, and traffic was routed to them one domain at a time. The monolith continued serving untouched domains until every route had been migrated and validated.
Step 3 — New Conduits with Node.js and GraphQL
Step 3 — New Conduits with Node.js and GraphQL
Each extracted service exposed its data through a GraphQL API built with Node.js, providing a clean, typed interface for the frontend acolytes to consume without requiring client-side changes.
The Result
60% reduction in average server response time after full migration.0 minutes of unplanned downtime across the entire migration period.
Case Study 2: Binding the State with Redux
Category: Frontend Sorcery — Difficulty: 🌕🌕🌕🌕🌑 (4 / 5)A demanding ritual requiring deep knowledge of React’s rendering model and Redux’s incantation patterns to bring order to chaotic state.
The Challenge
A large React application had grown without a centralized state strategy. Component trees were deeply nested, and critical data was passed through five or more levels of props to reach the components that needed it. The prop-drilling created invisible coupling: changing a component’s interface rippled changes upward through unrelated ancestors, slowing development to a crawl and making refactors unpredictable.The Approach
Step 1 — The Central Grimoire: Redux Toolkit
Step 1 — The Central Grimoire: Redux Toolkit
Redux Toolkit (RTK) was introduced as the application’s single source of truth — a central grimoire holding all shared state. RTK’s
createSlice reduced the boilerplate ceremony of traditional Redux to a minimum, giving instant visibility into every dispatched action.Step 2 — Normalized State Shape
Step 2 — Normalized State Shape
All entity collections (users, products, orders) were stored in a normalized shape. Instead of nested objects that duplicated data, the store held flat lookup tables keyed by ID. This eliminated an entire class of consistency bugs where the same entity could diverge across different parts of the tree.
Step 3 — Strict Selectors
Step 3 — Strict Selectors
Every piece of derived data was encapsulated in a selector function. Components were forbidden from computing derived state inline. This made the data-access contract explicit and testable, and ensured that business logic lived in a single, predictable location.
Step 4 — Custom Middleware for API Side Effects
Step 4 — Custom Middleware for API Side Effects
A custom Redux middleware was implemented to handle side-effects (API calls) elegantly. This replaced an inconsistent tangle of
useEffect hooks scattered across the component tree with a single, predictable side-effect layer.Step 5 — Memoized Selectors with Reselect
Step 5 — Memoized Selectors with Reselect
High-frequency selectors were wrapped with Reselect to memoize their output. Components now re-rendered only when their specific slice of state actually changed — not on every root store update. This eliminated the majority of unnecessary re-renders and brought perceived UI responsiveness back to near-instant.
The Result
Prop-drilling eliminated across the entire component tree — no component passes state more than one level it doesn’t own.Unnecessary re-renders reduced to near zero through memoized selectors and strict component subscriptions.Predictable, testable state logic consolidated into slice files — new features can be added without touching unrelated components.