The monorepo vs microservices debate usually centers on build performance, deployment independence, and team autonomy. These are valid concerns. But there's a dimension that nobody discusses: knowledge management.
In a monorepo, all code is in one place. This means:
The downside: the knowledge surface area is enormous. A monorepo with 500K lines of code is too large for any individual to understand completely. Developers develop deep expertise in their area and shallow familiarity with the rest.
In a microservices architecture, code is distributed across 10-50+ repositories. This means:
The knowledge cost: every cross-service interaction requires a developer to understand two or more codebases, their contracts, and their implicit assumptions.
For a complex, cross-cutting feature:
Monorepo: Developer traces the full implementation in one repo. Understanding Tax: 30-60 minutes. Can see all affected code in one PR.
Microservices: Developer traces implementation across 3 repos. Must understand 3 different codebases, 3 API contracts, and 3 deployment pipelines. Understanding Tax: 2-4 hours. Changes require 3 coordinated PRs.
The microservices approach trades individual service simplicity for system-level complexity. For cross-cutting work, the knowledge overhead is 3-5x higher.
Code intelligence tools can bridge the microservices knowledge gap:
With these tools, the knowledge properties of microservices approach those of a monorepo — you get the deployment independence of microservices with the discoverability of a monorepo.
The architecture decision shouldn't be about which is "better." It should be about which knowledge properties your team can support — and whether tools can compensate for the gaps.
The monorepo vs microservices decision has a hidden dimension: the Understanding Tax. Microservices multiply context boundaries, making cross-cutting work 3-5x more expensive to understand.
For the remote work angle on knowledge distribution, read Remote Engineering Teams: Solving the Knowledge Transfer Problem.
Pre-code intelligence from Glue bridges the microservices knowledge gap — providing cross-repo dependency graphs, unified search, and feature maps that span service boundaries.