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# How Cisco embraced a DevOps culture within its network engineering team

Cisco slashed hardware provisioning from 36 hours to 10 minutes by treating network configuration as software development. Discover how GitOps and CI/CD transformed their fragile engineering workflows.

- **Speakers:** Stuart Clark
- **Event:** WeAreDevelopers LIVE
- **Published:** December 10, 2020
- **Duration:** 39:38
- **URL:** https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team

## Summary

Traditional network engineering often relies on fragile, manual configurations, forcing engineers into endless cycles of troubleshooting and restrictive CLI tasks. For Cisco’s globally distributed network team, scaling expanding data centers exposed the critical flaws in this reactive box-by-box management approach—namely unpredictable human error, delayed hardware provisioning, and the dangerous accumulation of untracked snowflake configurations from late-night emergency fixes. Recognizing the team was caught in a trap of being too busy to improve, engineering leadership pivoted from waterfall operations to an agile workflow directly inspired by internal Site Reliability Engineering (SRE) practices. To accomplish this, the team embraced a NetDevOps culture driven by GitOps principles, extracting configurations from device-specific syntax and translating them into machine-readable Infrastructure as Code (IaC) using JSON, YAML, and XML. Establishing GitHub as the single source of truth empowered engineers to replace manual SSH changes with structured, model-driven API programmability. This new CI/CD pipeline introduced rigorous pre-flight validations and automated QA testing via Jenkins, resolving potential network issues on virtual devices before production deployment. Ultimately, treating network configuration as standard software development transformed deployment speeds, cutting 36 hours of manual data center wait times down to a 10-minute automated hardware provisioning cycle. Asserting a continuous desired state eradicated undocumented configuration drift and guaranteed reliable, instantaneous rollbacks during system failures. By sharing version-controlled code, the team successfully bridged the operational language gap, allowing developers and SREs to request, audit, and collaborate on network resources natively.

**Keywords:** infrastructure as code, network automation tools, netdevops implementation, gitops principles, configuration management, SRE methodologies, machine-readable IaC, model-driven telemetry, automated QA validation, CI/CD deployment pipelines, API programmability, JSON and YAML code, version-controlled infrastructure, snowflake configuration removal, agile operational workflows, hardware provisioning automation

## Chapters

1. **Scaling global network engineering through DevOps culture** (00:00) — Adopting a DevOps culture resolves the scaling bottlenecks faced by geographically dispersed networking teams during data center expansions.
1. **Defining critical tasks for network agility and scale** (03:18) — Moving away from traditional manual approaches enables teams to support rapid service provisioning and dynamic traffic spikes.
1. **Uncovering the risks of manual deployment workflows** (05:41) — Consolidating manual actions prevents obscured system visibility and simplifies root cause analysis during critical service disruptions.
1. **Transitioning device configurations to infrastructure as code** (11:06) — Migrating from proprietary snapshots to versioned repositories enables rigorous unit testing and automated peer reviews.
1. **Utilizing self-service monitoring and telemetry for rapid diagnostics** (13:11) — Correlating code deployment logs with network traffic irregularities drastically speeds up the troubleshooting process.
1. **Adopting agile practices to overcome operational bottlenecks** (14:46) — Transitioning to agile methodologies allows overwhelmed engineers to implement permanent solutions rather than constantly firefighting.
1. **Implementing GitOps principles for predictable code deployments** (18:02) — Centralizing configurations in version control while leveraging programmatic APIs ensures secure and predictable system updates.
1. **Managing consistency and scale with declared configuration states** (22:32) — Establishing benchmark standards across diverse geographical deployments simplifies device upgrades and clarifies service ownership.
1. **Accelerating physical server deployments with localized automation** (29:08) — Executing comprehensive quality assurance scripts reduces new server staging times and dramatically cuts technician wait cycles.
1. **Eliminating ad hoc snowflake modifications from production instances** (33:14) — Routing emergency fixes through formal integration pipelines guarantees long-term stability and removes undocumented network behavior.
1. **Realizing the operational advantages of versioned system control** (36:01) — Establishing machine-readable deployment practices democratizes infrastructure improvements and actively prevents localized security breaches.
1. **Expanding practical knowledge with community sandboxes and resources** (38:08) — Leveraging dedicated practice environments and active advocacy communities accelerates continuous learning for modern engineering techniques.

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- [Overcoming cultural friction and scaling DevOps team practices](https://www.wearedevelopers.com/videos/855-fast-flow-not-fast-fluff-embracing-an-eclectic-devops-coaching-approach) (from "Fast Flow, Not Fast Fluff: Embracing an Eclectic DevOps Coaching Approach")
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- [Origins of adopting DevOps and overcoming infrastructure bottlenecks](https://www.wearedevelopers.com/videos/338-demystifying-devops-pros-cons-dos-don-ts) (from "Demystifying DevOps—Pros, cons, dos & don'ts")
- [Introduction to cloud native infrastructure and platform engineering](https://www.wearedevelopers.com/videos/885-platform-engineering-vs-devops-why-not-both) (from "Platform Engineering vs. DevOps Why not both?")
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