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network automation

What is network automation?

Network automation is a methodology in which software automatically configures, provisions, manages and tests network devices. It is used by enterprises and service providers to improve efficiency, reduce human error and lower operating expense (Opex).

Network automation tools support functions ranging from basic network mapping and device discovery to more complex workflows, like network configuration management and the provisioning of virtual network resources.

Network automation also plays a key role in software-defined networking (SDN), network virtualization and network orchestration, enabling automated provisioning of virtual network tenants and functions, such as virtual load balancing.

How does network automation work?

Network automation is similar to software programming because it uses comparable logic and frameworks to manage and schedule the automation of various tasks. Common "if X, then Y" decision statements are used to program automation into the network.

Administrators can use tools that are integrated into the networking platform. Alternatively, they can create and execute automation scripts for network components by using first- or third-party software.

Modern SDN platforms use a centralized control plane and often have commonly used and pre-built automation tasks that can be adjusted and scheduled. Alternatively, network teams can use external tools to create scripts and execute them via command-line interface (CLI) or application programming interface (API).

Common examples of network automation tasks used in production environments include the following:

  • bandwidth forecasting for internet and wide area network (WAN) links;
  • network and device inventory and monitoring;
  • service-level agreement monitoring and alerting;
  • automated network configuration backups;
  • mass configuration changes across multiple networks and clouds; and
  • access port turn-ups and turn-downs based on employee onboarding and offboarding information.

Types of network automation

Automation can be employed in any type of network, including local area networks, WANs, data center networks, cloud networks and wireless networks. In short, any network resource controlled through a CLI or an API can be automated.

1. Script-driven network automation

Script-driven network automation employs scripting and programming languages to execute tasks, ideally those with precise triggers and consistent procedures. Legacy languages, such as Perl and Tcl, remain prevalent in network automation due to their familiarity.

As networks continue to become more complex, newer open source programming languages, such as Ansible, Python and Ruby, have grown in popularity for their ease of use and flexibility. Other programming languages for network automation include Bash and Go.

2. Software-based network automation

Software-based network automation, often referred to as intelligent network automation, is coordinated through an administrative portal that eliminates the need to script commands manually. These platforms typically provide templates for creating and executing tasks based on plain language policies.

3. Intent-based network automation

The latest network automation includes the use of artificial intelligence (AI) and machine learning to understand user and business intent and automatically modify how network policy is enforced based on this knowledge. Network administrators create performance service levels for applications and users. When these service levels are not met, the network automatically adjusts -- as best it can -- to bring business-critical application performance levels back in line.

Steps to get started with network automation
Network teams can use these three steps to get started with network automation.

Benefits of network automation

Some common benefits of network automation include the following.

1. Improved efficiency and network optimization

By automating functions on network devices, humans no longer have to perform time-consuming and rudimentary tasks.

2. Reduced likelihood of human error

Manual tasks are prone to human error, which can cause network outages and revenue loss. The consequences of a miscalculation or incorrect entry can be significant. Setting up a task for automation means it only needs to be entered correctly once. Network engineers can easily revert automated changes in case of error and adjust as needed.

3. Lower Opex

By eliminating certain manual tasks for network management and device provisioning, businesses can operate with greater speed and agility. For example, automated provisioning may save a network engineer from having to travel to a new branch office to establish network connectivity, thus enabling employees at that site to get to work faster.

Network automation tools and languages

Several interfaces, platforms and protocols are available for enterprise network teams to implement network automation.

The CLI is the most traditional vehicle for deploying network automation. Though freely available, time-tested and highly customizable, it requires proficiency in CLI syntax and doesn't scale well in certain distributed infrastructure environments.

A variety of open source tools -- including Ansible, Chef and Puppet -- offer network automation frameworks. These tools typically offer a library of common commands or workflows that can easily be repeated.

Commercial network automation tools are also available. Most network infrastructure vendors have developed software-based platforms that provide automation capabilities, typically for their own products, through a specialized API. More recently, however, network manufacturers are offering open API access to their network equipment hardware and software. Thus, many third-party tools can now be used to automate networks in multivendor environments.

Network automation challenges

For some IT shops, network automation can be a serious undertaking. Some examples include the following:

  • Network device incompatibility. Many legacy network devices are locked into proprietary ecosystems and cannot tap into APIs. This limits the types of automation tools that can be used, as well as the effectiveness of network automation capabilities.
  • Tool complexity. Automation tools can create added complexity, especially when AI and machine learning are added to the mix.
  • Distributed networks. Hybrid and multi-cloud environments that are incompatible with certain automation tools can hinder efficiency and scalability.

But perhaps the biggest challenge to overcome is the cultural change that is required for any network automation program to be successful. In many ways, network automation is a bit terrifying to administrators as it takes away control from those who are paid to manage it. While automation can eliminate human error in many cases, it can also cause major outages when not properly calibrated. That means that complete understanding and buy-in are required.

Best practices for network automation

The implementation of network automation into production networks isn't something that should be taken lightly. Instead, some careful planning must ensure the right policies, tools and mindset are in place before automated processes can commence. Best practices for network automation integrations include the following:

  • Perform a thorough network device inventory.
  • Identify processes that can be automated.
  • Research the automation tools that work best in a given infrastructure.
  • Start with basic network automation processes, and then slowly add more complex tasks.

Future of network automation

Network automation is one of the key methodologies supporting the evolution of intent-based networking and network validation. These concepts use software to map how enterprises can harness their resources to meet the business demands their networks need to support.

Automation is increasingly enabled through a graphical user interface (GUI). Engineers use a GUI to determine how their network operations should run to meet a particular objective. A GUI can then automatically run configuration and other management changes made to network components, regardless of vendor. Automation frequently incorporates AI and machine learning tools to analyze the network, suggest troubleshooting steps and validate network intent.

See also: IT automation, Automated provisioning, business process automation

This was last updated in March 2022

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