Infrastructure as Code
5 products

Infrahub
OpsMill
·Infrastructure as Code
-

Red Hat Ansible Automation Platform
Red Hat
·Infrastructure as Code
-

HashiCorp Packer
HashiCorp
·Infrastructure as Code
-

HashiCorp Consul
HashiCorp
·Infrastructure as Code
-

HashiCorp Terraform
HashiCorp
·Infrastructure as Code
-

Infrastructure as CodeMain
Infrahub is a data management platform designed for network and infrastructure automation, integrating with AI workflows to enhance reliability and scalability. It unifies infrastructure data, supports automation at scale, and provides a robust foundation for AI-driven operations.
Features
- Unify fragmented infrastructure data from CMDBs, NSoTs, homegrown databases, and spreadsheets into a unified source
- Define custom data models with a flexible schema to match specific infrastructure needs
- Store complex infrastructure relationships in a graph database
- Integrate Git for versioned, traceable, and portable infrastructure data storage
- Capture and manage metadata for relationships, ownership, permissions, and change history
- Use AI schema tools to build custom schemas faster
- Run structured tests against data to enforce consistency and catch errors early
- Automate deployment across any infrastructure using service definitions

Infrastructure as CodeMain
Infrahub is a data management platform designed for network and infrastructure automation, integrating with AI workflows to enhance reliability and scalability. It unifies infrastructure data, supports automation at scale, and provides a robust foundation for AI-driven operations.
Features
- Unify fragmented infrastructure data from CMDBs, NSoTs, homegrown databases, and spreadsheets into a unified source
- Define custom data models with a flexible schema to match specific infrastructure needs
- Store complex infrastructure relationships in a graph database
- Integrate Git for versioned, traceable, and portable infrastructure data storage
- Capture and manage metadata for relationships, ownership, permissions, and change history
- Use AI schema tools to build custom schemas faster
- Run structured tests against data to enforce consistency and catch errors early
- Automate deployment across any infrastructure using service definitions