Modern networks are moving away from statically configured, hardware-focused architectures to flexible, software-focused systems. This move highlights the need for a pairing between DevOps and network administration. Network teams are organically moving to a NetOps workflow model to keep up with rapid advancements and deployments of new applications in the enterprise.
A typical NetOps strategy centers around three themes: virtualization, automation and AI-backed monitoring.
Virtualization in a NetOps framework
NetOps frameworks use virtualization to speed up deployment time. Traditional network functions, like routing, switching and network security, no longer need to be deployed as physical hardware appliances, so network teams can combine virtual appliances and virtual network overlays to deploy physical network components centrally.
Teams use these virtual services to reach various critical junctions of a network, saving both time and money in deploying physical devices. As a result, NetOps teams can focus more on deploying and managing virtual networks within public and private clouds.
Automation as a linchpin
Automation is another key component to a successful NetOps strategy. Applications are now deployed with continuous improvement in mind, so networks must be able to support newly added application features and services just as quickly.
One setback of traditional networking is teams aren't designed to handle rapid change because manual network equipment still requires manual configuration in many cases. This is where the flexibility of software-driven networks and automation come into play.
Network automation can take numerous forms, from self-service portals -- where application administrators can spin up ports and virtual LANs without network admins -- to AI that identifies new services and applies quality of service policies. More recently, network overlay platforms enable the centralized deployment and management of network policy across private and public data centers.
Automation is the linchpin to ensuring networks can keep up with Agile-deployed apps. Network administrators must learn how to set up prepackaged automation tools and script new automation processes with APIs.
The use of AI to monitor networks
The emergence of AI-backed network monitoring tools aids NetOps teams with identifying and remediating network performance and security issues. IT networking is a reactionary field in that teams must rectify security and performance issues quickly to avoid any major disruptions. With traditional networking, teams would use tools to manually sift through network events and identify any potential problems. The first step was to pinpoint the issue and then figure out how to fix it.
While traditional network tools provide visibility by identifying performance and security incidents, manual processes are slow to keep up with modern infrastructures where continuous change is constant. Tools like AI for IT operations, or AIOps, and network detection and response have gained tremendous traction within the world of NetOps to speed up troubleshooting processes.
Modern NetOps requires a shift in culture
Traditional network methodology placed network operations in a silo, as developers and application administrators could only add or change requests between their groups. Modern networking is shifting into a DevOps-like role and, as such, needs a culture of sharing information between IT departments.
Network teams must gain an improved understanding of the applications used in their networks and how to optimize their networks for ideal performance. It's also important for developers and application administrators to have a basic understanding of network performance. This level of skill crossover leads to teams with vastly improved communication, creating a system where changes occur both quickly and accurately.
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