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This article explains how the Android department uses Ansible to automate server deployment, detailing installation, inventory setup, playbook structure, and example configurations for Cockpit monitoring and GitLab Runner, including command snippets and code examples to streamline operations.
This article explains the concepts, key characteristics, terminology, and practical steps of dimensional modeling—including star and snowflake schemas—and demonstrates how to apply the methodology to a real‑world sales analysis scenario, while also discussing common challenges in building star‑schema models.
This article explains the transition from StoreKit 1 to StoreKit 2 for iOS in‑app purchases, detailing the limitations of applicationUsername, the new appAccountToken mechanism, updated purchase and order‑recovery flows, enhanced notification handling, and references to Apple’s server APIs.
This article explains why and how to upgrade a production iOS app from StoreKit 1 to StoreKit 2, outlines the new purchase flow, compares the two APIs, shares real‑world issues encountered during migration, and provides Swift code snippets and work‑arounds for each challenge.
This article introduces HTML5 Canvas, explains its advantages over SVG, and provides comprehensive guidance on using the Canvas API—including context acquisition, drawing shapes, paths, arcs, gradients, pixel manipulation, state management, transformations, and a complete clock example—illustrated with code snippets and visual demos.
This article outlines the background, technical analysis, and step‑by‑step practical migration of multiple Fluently Speaking Android applications to Android 12, covering environment upgrades, Gradle and JDK changes, CI/CD runner configuration, API adjustments, UI updates, and future outlook.
This article explains the concept of Lifetime Value (LTV), presents a two‑step estimation method based on purchase pathways, evaluates model accuracy with real data, and discusses practical applications such as acquisition guidance, fine‑grained operations, and product iteration decisions.
This article describes Liulishuo's migration to a Flink‑based real‑time data warehouse, covering background, benefits, technology selection (storage, Flink platform, dimension table connectors), overall architecture, concrete Hudi and Elasticsearch ingestion examples, processing SQL, and future outlook for unified batch‑streaming storage.
This article outlines the design and implementation of a near‑real‑time metric management platform at Liulishuo, detailing its data flow—from Kafka ingestion through Flink‑SQL processing into Hudi tables, Trino querying, metric configuration, lineage, visualization, alerting, scheduling, and future optimization plans.
The article describes the motivation, requirements, and architectural design of a highly available, scalable, low‑cost distributed time‑series database built on Mimir, detailing write and read paths, multi‑tenant isolation, compaction, and the performance and cost improvements achieved after deployment.
