How to Set Up H2 In-Memory Database in a Spring Boot CRUD App

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A developer building a Spring Boot CRUD application switched from using a linked list to a database to enable persistent data storage. They chose the H2 in-memory database as a beginner-friendly option that requires no separate installation or configuration of heavier systems like MySQL or PostgreSQL. The setup involves configuring three key sections in the application.properties file: H2 database connection details, JPA settings, and the H2 web console. JPA, or Jakarta Persistence API, allows developers to interact with the database using Java code instead of writing raw SQL queries. The guide also notes that the Spring Data JPA dependency must be added to the project's pom.xml file for the integration to work.

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How to Properly Back Up a Self-Hosted Spliit Instance Using PostgreSQL and S3

Self-hosting the expense-splitting app Spliit requires backing up three distinct components: a compressed PostgreSQL database dump, a copy of the S3 or MinIO bucket storing receipt images, and the environment file holding credentials and configuration. The PostgreSQL database contains all groups, expenses, participants, and splits, making it the most critical backup element, while receipt image blobs stored in S3 cannot be recreated from memory. A lesser-known data loss risk is the browser's local storage, which holds group link indexes and is entirely separate from the database. Backup needs vary by use case — casual users may need only nightly database dumps, while heavy users scanning receipts should prioritize bucket backups with dated retention windows. Experts recommend logical pg_dump over Docker volume snapshots for portability across version upgrades, and stress that any backup plan must include a rehearsed restore procedure to be considered reliable.

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ProgrammingDEV Community ·

Playwright's Built-In API Testing Tool Eliminates Need for Separate Frameworks

Playwright, primarily known as a browser automation framework, includes a built-in HTTP client called APIRequestContext that allows teams to run API tests without a separate testing tool. It supports standard HTTP methods, authentication, header configuration, and response assertions, all within the same test suite used for end-to-end browser testing. Teams benefit from shared authentication state, a unified test runner, and consistent debugging workflows through Playwright's HTML report and Trace Viewer. Setup requires installing Playwright via npm, configuring a base URL, and using the built-in request fixture — no additional libraries needed. This makes Playwright a practical all-in-one option for teams looking to consolidate their UI and API testing into a single CI pipeline.

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ProgrammingDEV Community ·

Cloudways to Retire Legacy API Keys by October 2026, Urges Token Migration

Cloudways is phasing out its legacy API Key authentication in favour of API Access Tokens, with an end-of-life date set for October 15, 2026. Existing integrations can continue using API Keys during the transition period, but Cloudways recommends migrating to Access Tokens before the retirement deadline. Access Tokens offer improvements over the old system, including per-integration tokens, configurable permissions, expiration periods, and independent revocation. For teams using GitHub Actions to deploy Laravel applications on Cloudways, the migration involves replacing the email-and-API-key credential pair with a Bearer token passed directly to the Cloudways REST API. The core deployment architecture remains largely unchanged, with only the authentication method needing to be updated.

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ProgrammingDEV Community ·

Go Pipeline Hits 4x Speedup Using Lock-Free and Cache-Line Optimization Techniques

A software engineering walkthrough published on DEV Community demonstrates how replacing a mutex-based Go pipeline with lock-free alternatives can dramatically improve throughput. The naive implementation, using a shared mutex queue, channel semaphore, and buffered file I/O, processed around 821,000 events per second on an 8-core machine. An optimized version employing sharded SPSC ring buffers, a Chase-Lev work-stealing deque, cache-line-padded atomic semaphores, and mmap zero-copy storage raised throughput to roughly 3.3 million events per second — a 4x improvement. A focused micro-benchmark further showed that simply padding struct fields to separate cache lines reduced execution time from 543ms to 157ms, a 3.46x gain from a single layout change. The author notes that all six techniques covered — cache-line padding, atomic semaphores, sharding, ring buffers, work stealing, and zero-copy I/O — apply equally to C++, Rust, Java, and other performance-critical environments.

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