The article traces the evolution from monolithic Java apps to RPC services, explains why sharding and database partitioning cannot alone achieve limitless scaling due to connection limits, and introduces unitization—assigning each application to a specific database shard—to overcome the bottleneck.
Facing rapid growth of the KuaiPin hiring platform, the team tackled labor‑intensive image and AIGC template creation by building the Fuxi Workbench, which automated template production, introduced D2C conversion, a DSL editor, and layered architecture, ultimately boosting efficiency, scalability, and stability while reducing costs dramatically.
WeChat safeguards its billion‑user microservice platform by detecting overload when average queue wait exceeds 20 ms and applying a two‑dimensional priority system—business and hourly‑hashed user priorities—adjusted via histogram‑based admission controls and upstream back‑pressure, ensuring stable service during massive traffic spikes.
Baidu’s Search Architecture team evolved compute management from static physical‑machine deployment to cloud‑native mixed deployment, employing a governance system that combines elastic containers, Service Mesh, and committee‑driven operations, while leveraging tidal scaling, container tiering, performance‑curve‑based VPA/HPA, and fine‑grained traffic scheduling to deliver cost‑effective, flexible, and performance‑driven resource allocation across both temporal and task‑type dimensions.
This article explains how Zhaozhuan uses Nginx load‑balancing, the dyups module, and a custom deployment workflow to achieve zero‑downtime service upgrades, dynamic scaling, and graceful reloads without losing any requests.
The article traces the evolution of backend services from monolithic applications through RPC-based scaling and sharding, highlights the limitations of database connection counts, and proposes a unitized architecture that partitions databases per service to achieve true unlimited scaling while acknowledging added complexity.
The article explains how traditional scaling methods like sharding and RPC eventually hit connection limits, and introduces unitization as a strategy to achieve unlimited service expansion by limiting each application to a single database instance.
The article explains that database read/write separation offers limited performance gains and mainly serves data safety, while true scalability for read operations comes from caching and server clusters, and that write operations require a single dedicated server and actor‑model programming for safe concurrency.
