A network team that had been writing Python and Ansible scripts for years turned that work into a shared, governed Center of Excellence – running 17 automation use cases in year one and taking BGP/BFD-related incidents from 11 per quarter to zero.
A small network team running essential infrastructure had years of DIY Python and Ansible automation in place – but the cost of maintaining and sharing those scripts had started to outweigh the value of running them.
A Center of Excellence model anchored on Itential – bringing siloed task automations into a single orchestration framework, with Itential Gateway preserving every script the team had already built.
Integration capabilities that connect every automation tool and third-party system, a gateway that standardizes execution across Python, Ansible, and Terraform, and a low-code canvas that lets coders and non-coders build together.
At this global pharmaceutical and medical technologies company, automation wasn’t a new idea. To keep up with their expanding infrastructure, the network team had been building task-based automations with Python and Ansible for years. Those task automations were essential – replacing routine manual actions with a single command, making the day-to-day of network engineers a little easier.
But as the library grew, so did the cost of maintaining it. The team found themselves spending more time managing and updating automation assets than actually executing them or building new ones. And the extra work required to share those automations with others – validations, access control, auditing – meant their reach was limited.
To increase the impact of the team’s automation work, leadership decided to pursue a Center of Excellence model. A CoE is a culture initiative – bringing automation to the forefront of how IT and network operations are done by changing mindsets, improving skills, and choosing the right platform. Done well, it brings people across teams together to build a cohesive strategy and standardize on a platform that enables scale.
Each one was manageable on its own. Together, they capped what DIY scripts could deliver – and pointed the team toward a platform layer that could absorb the maintenance and sharing burden.
The team spent more time managing and updating automation assets than actually executing them or building new ones – engineering time the small team did not have.
Sharing automations with other teams required validations, access control, and auditing – plumbing that had to be built every time, limiting how far any single automation could reach.
DIY automations stayed inside whichever team and toolchain originally built them – making standardization across infrastructure teams difficult, and a Center of Excellence model impossible without a shared platform.
Implementing a CoE meant selecting a platform that could orchestrate disparate automation tooling and integrate across multiple technologies and domains. Itential’s unique integration capabilities – connecting every automation tool and third-party system – made it the right fit. The team took a measured, incremental approach: pick four high-priority use cases, deliver them quickly with Itential, prove the model to every team that would touch it. Five capabilities anchored the choice.
Five capabilities sat at the center of the decision – together making it possible to centralize automation across infrastructure teams without forcing anyone into a single tooling choice.
Whether automations are built in Python, Ansible, Terraform, or another tool, Itential Gateway standardizes the execution layer – so automations are easier to share and execute without anyone having to abandon the tooling they prefer.
Existing Python and Ansible work can be attached to API endpoints – enabling those automations to participate in end-to-end orchestrated workflows alongside change management, security, and other third-party systems.
Comprehensive integrations generated using API documents with every network and IT system – extending the reach of the team’s automations into the broader IT ecosystem without per-system custom integration work.
An easy-to-use, low-code workflow building canvas – so coders and non-coders alike can participate in building orchestrations and contribute to the CoE on equal footing.
Automations exposed for self-serve consumption through methods like a ServiceNow catalog and CI/CD pipelines – so others can request and use automations without running scripts themselves or needing visibility into the underlying infrastructure.
The team launched with four high-priority use cases, proved the platform approach quickly, and built outward from there – turning DIY scripts into shared, governed workflows the whole organization can contribute to and consume.
A measured incremental approach: select four high-priority use cases, deliver them quickly with Itential, build familiarity, prove the platform approach to each team that would adopt it.
High-device-footprint use cases including automated patching, baseline compliance reporting, and CMDB accuracy enforcement – high-impact processes brought under one orchestrated model.
Routing-related operations brought under standardized orchestrated workflows – taking BGP/BFD-related network incidents from 11 per quarter to zero.
A standardized internal course (Python, JSON, APIs, Itential basics) – the gateway to CoE participation, so anyone interested in automation has a structured path to contribute.
The Center of Excellence model didn’t just deliver use cases – it built the operating muscle behind them. The team now ships a steady pipeline of orchestrated automations and onboards new contributors much faster than before.
The CoE roadmap continues at a steady cadence: at least five new use cases per quarter, deepening device-footprint coverage on existing automations, and onboarding more contributors through the standardized Python, JSON, API, and Itential course.
Continued focus areas include expanding self-serve consumption through ServiceNow and CI/CD, broadening the catalog of orchestrated infrastructure services, and extending the CoE participation model further across the IT organization – turning automation-first from a vision into the default operating model.
See how Itential connects AI reasoning to governed execution across your entire infrastructure.