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The article explains that although IO multiplexing can improve performance, database access in Java typically relies on JDBC and connection pools, which are built on blocking I/O, making it difficult to combine DB connections with IO multiplexing without major architectural changes.
After a sudden traffic surge exposed severe latency in a 15‑year‑old multi‑service web system, the team identified a DB connection leak in a health‑check probe, and through load testing, monitoring, logging, and dedicated SRE effort, they derived key operational lessons on performance optimization and maintenance of legacy applications.
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 why simple sharding and database partitioning cannot achieve unlimited scaling in backend systems, analyzes the problem of excessive RPC‑to‑DB connections, and proposes a unitization approach that limits each service to a single database to enable true horizontal expansion.
The article examines why traditional sharding and database partitioning cannot alone achieve limitless scaling, explains the problem of excessive RPC‑to‑DB connections, and proposes a unitization approach that limits each service to a single database shard to enable true horizontal expansion.
The article traces the evolution of backend services from monolithic applications through RPC-based scaling and database sharding, explains why sharding alone cannot achieve unlimited scalability due to connection limits, and proposes a unitized architecture that partitions databases per service to overcome these constraints.