Scale of Networks

Let's take a look at how the scale of the organization's network affects automation.

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The size and scale of the modern network have grown exponentially to accommodate the needs of organizations. Networks that started out as just a few switches and a router are now large-scale enterprise networks. While logical networks evolve and grow, the tools used to manage physical devices remain stagnant. On the campus, we now see VoIP phones, wireless access points, IoT, security cameras, print fleets, desktop fleets, and meeting room equipment. In the data centers large physical and virtual footprints are not uncommon. Worldwide WANs, with switching and routing in each remote office, are now commonplace. The device is not slowing down. Even more devices are being added to networks every day in the absence of appropriate centralized, and automated management solutions.

Network management starts with the console cable and a local CLI. Administrators must enable remote access to the CLI over a management IP address. Now, imagine network technicians still needing to go to the physical console of every device to manage it. It sounds unreasonable, but only remote access to the CLI has been centralized. The same methodology of logging into the CLI to manage the device is followed as if the operator is virtually at the console. In fact, these remote connections are known as virtual teletypes, or VTY lines. At the scale of today’s networks, connecting to the CLI of every device to manage the enterprise is simply unachievable. Even with a large, capable network operations team, everyone is going to operate, configure, and manage each device their own way. This leads to configuration drift and a lack of consistency at scale.

Automated solutions scale with the network as device configurations are templated. Small, feature-specific, and modular templates ensure each device is standardized. When new feature requirements arise, the configuration commands are templated and released at scale, updating the network standards uniformly. Unique, device-specific, and meaningful information is modeled in a data dictionary. This dictionary holds all the variables used to compile a unique configuration for each device. Code can be written modularly to match the topology of the network. By creating playbooks specific to the environment, such as campus, data center, WAN, or cloud, Ansible playbooks ensure code simplicity, readability, and development flexibility.

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