Page 179 - Maxim Mironjuk

A slow GraphQL query is rarely GraphQL's fault. The real problems sit deeper: N+1 patterns in resolver chains, EAV tables that produce dozens of joins per product, and queries without complexity limits that can load the server arbitrarily. This article shows where to look and what actually helps.

Cross Site Request Forgery is considered a solved problem by many teams the moment an application moves to a single page architecture with fetch instead of classic forms. In reality the risk merely shifts as long as session cookies are involved in authenticated API calls, and it stays real, requiring a deliberate combination of double submit cookie, the SameSite attribute and custom headers.

Classic unit tests check individual, hand-picked examples. Property-based testing flips that around: instead of writing examples, you define properties that must hold for every valid input, then let fast-check generate thousands of random cases to uncover exactly the edge cases a human writing tests by hand tends to overlook.

File management tasks are part of everyday automation: sorting hundreds of log files by date, renaming export files to match a naming convention, cleaning up temporary build artifacts. With the right mv patterns, rename for bulk renaming and find for sorting and filtering, these tasks can be solved safely, traceably and reversibly.

Every click that only shows a visible effect after a server round trip feels sluggish to users, even when the request objectively only takes two hundred milliseconds. Optimistic UI updates solve this perception problem by having the Alpine state show the expected change immediately, with the actual server request only running afterward in the background. Using a like button as an example, this article shows how to implement such a pattern cleanly, which rollback strategy kicks in for a failed request, how to avoid race conditions across several fast interactions, and in which cases optimistic updates should deliberately be avoided.

A template gets edited, but the change never shows up in the frontend. The cause is almost always somewhere in the fallback chain between module, theme, and parent theme, and hunting for it without the right tools wastes real time. This article walks through a systematic debug workflow.

Setting up a new replica for a large Magento database used to mean either an hours-long mysqldump import or reaching for an external tool like xtrabackup. Since MySQL 8.0.17, the built-in clone plugin handles this task directly inside the server: a physical, page-based copy process that turns hours into minutes on databases hundreds of gigabytes in size.

Anyone who only knows a DI container from a framework's documentation rarely understands why it is designed the way it is designed. In this article we build a minimal, PSR-11-compliant DI container from the ground up in plain PHP 8.4: with reflection-based autowiring, recursive dependency resolution, cycle detection, and clearly defined bindings between interface and implementation. What comes out is not production code, but a tool for understanding, one that shows what PHP-DI, Symfony DependencyInjection, and the Laravel container actually do under the hood.

Vue memory leaks almost always originate in the same three places: forgotten event listeners, timers that never get stopped, and watchers without cleanup when a component unmounts. Chrome devtools heap snapshots let you confirm any suspicion with solid evidence, instead of changing code based on guesswork that does not even touch the actual leak.

Who deployed what to production, and when? In e-commerce, that's not an academic question, it's a compliance requirement. GitLab provides the tools to make deployments traceable, from audit logs through protected branches to enforced review processes.