How Yanxuan Boosted Development Efficiency with a Unified DevOps Toolchain
This article explains how Yanxuan tackled growing development demands by redesigning its DevOps toolchain—covering CMDB, monitoring, CI/CD challenges, and a unified efficiency platform—to improve delivery speed, reduce collaboration costs, and support a container‑based, cloud‑native architecture.
Background
Yanxuan has grown over several years, serving thousands of services and expanding its R&D staff from dozens to hundreds. The increasing pressure on project delivery efficiency made improving development efficiency through DevOps unavoidable.
Why Rebuild the DevOps Toolchain (2019)
Rapid requirement changes intensified efficiency challenges.
Legacy processes and documentation degraded, raising collaboration costs.
The shift toward a container‑based micro‑service architecture required tools that fit containers and the cloud.
Where to Start
DevOps is a continuous loop of culture and tools. Building a toolchain must consider the entire chain, ensuring interoperability between stages such as Plan, Build, Test, Release, and Monitor, and aligning the responsibilities of PM, QA, SRE, and developers.
Core Stages
Plan : project‑management function.
Build (Code): development function.
Test : quality‑assurance function.
Release (Deploy): QA and operations function.
Monitor : shared by developers, QA, and operations.
CMDB
The CMDB manages relationships among products, resources, and personnel, providing a unified model for tools and aligning terminology across development, QA, and SRE.
Monitoring System
Three‑layer monitoring ensures comprehensive coverage:
Resource Monitoring : uses open‑falcon (with Grafana visualisation) to track runtime resources.
Application Monitoring : a custom Caesar system (based on Pinpoint) monitors full‑stack call traces.
Business Monitoring : a real‑time data‑lake platform provides massive data ingestion, custom dashboards, and alerting.
CI/CD Challenges and Solutions
Key issues were inconsistent branch‑management strategies, fragmented CI/CD tools (GitLab‑CI vs. Jenkins), and insufficient automated‑test coverage. The solution centers on a product‑oriented “artifact” concept, moving artifact generation to the CI stage, standardising pipelines with GitLab‑CI, using a quality‑management platform for automated testing, and employing the Opera release platform for deployment.
R&D Efficiency Platform
Overmind provides a one‑stop, visualised, end‑to‑end continuous‑delivery pipeline with metric analysis, allowing teams to focus on value flow rather than isolated tasks.
Future Directions
The toolchain will evolve in a spiral manner: first deepening domain‑specific capabilities, then building cross‑domain collaboration platforms to reduce usage costs and address gaps such as risk control, environment governance, and plugin standardisation.
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Yanxuan Tech Team
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