| # Sustain Git repo performance under heavy load |
| |
| Over time we've become accustomed to taking for granted that Source Code |
| Management systems are always available. SCMs are a mission-critical part of any |
| software-related business. When they don't work as expected, whole organizations |
| come to a halt quicker than you would expect, therefore, efficient maintenance |
| of such systems is crucial to success. |
| |
| Git repositories that are under heavy load quickly become inefficient or even |
| inaccessible. This impacts client operations of all types (e.g., |
| git-upload-pack, git-receive-pack). Currently, the only countermeasures are a |
| full GC or a geometric repacking, either time or metrics-based. |
| |
| As the repositories grow, running a full GC takes longer, is more expensive, and |
| risks introducing additional workload at inopportune times (e.g., running GC |
| during a burst of repository activity may bring nodes to a standstill). In this |
| talk, we will introduce an AI-driven approach to maintaining the performance of |
| busy Git repositories that undergo heavy workloads. The AI model will explore |
| and learn different strategies, including partial repacking, bitmap |
| regeneration, empty directory removals, and more, by evaluating its success |
| using reinforcement learning. |
| |
| *[Daniele Sassoli, Senior Engineering Manager / GerritForge Inc.](../speakers.md#dsassoli)* |
| |
