How Network Automation Will Shape the Future of Enterprise Data Center Operations

How Network Automation Will Shape the Future of Enterprise Data Center Operations
How Network Automation Will Shape the Future of Enterprise Data Center Operations

Enterprises in all verticals are moving fast to embrace digital transformation and distributed cloud applications. The technologies driving these trends promise to help enterprises innovate, compete and keep pace with evolving customer demands. But they also ratchet up pressure on enterprise data center networks to become more efficient, scalable and reliable.
 
To realize the full promise of digitalization and the cloud, enterprises need better ways to manage their data center networks. Network automation can play a critical role in helping enterprises reshape their data center operations to position themselves for success today and in the future.


Challenges for data center network teams

Pressure on data center networks and operations teams comes in multiple forms.

For example, cloud and digital applications tend to be data-intensive, so data center networks must be ready to scale. Likewise, customers and internal users want more speed, lower latency and 24/7 access to get the most from their applications, so data center networks need to deliver higher performance and reliability. Similarly, user requirements can change quickly as new applications emerge, so data center networks need to be more efficient and agile, too.
 
Digitalization and cloudification also make data center networks more complex to operate and manage. And the consequences of problems, outages and downtime are bigger than ever. Network teams need to reduce their reliance on manual provisioning, configuration, upgrades and patches, all of which are expensive, time-consuming and error prone.


Network automation to the rescue?

Enterprises recognize that network automation would boost their efforts to address these challenges. With automation, they could provision, operate and manage complex data center network infrastructures with greater efficiency and precision. They could also reduce manual effort, avoid human errors and give skilled engineers more opportunities to tackle important strategic initiatives.
 
It's no surprise that enterprises are working hard to make these possibilities a reality.
 
For example, some have embraced software architectures that support microservices, containers and DevOps using CI/CD methods to speed up innovation. Others have deployed highly scalable spine–leaf data center fabric architectures that can handle more devices, workloads, sites and traffic.
 
Data center network solution vendors are also trying to lend a hand by adding some automation capabilities, opening up parts of their proprietary platforms and supporting some third-party applications.
 
But partly open, partly automated data center network solutions designed before the rise of the cloud, won’t allow enterprises to adapt to new demands with the speed and confidence required for the digital age.


Fully open and automated data center fabrics change the game

Enterprises want the data center vendors to provide an open and flexible network automation platform (NAP), though a NAP can only be powerful and extensive if the underlying network operating system (NOS) is designed for automation.
 
The foundation for a modern enterprise data center fabric is a fully open and automated NOS.
 
This NOS should be designed to remove the constraints and barriers presented by legacy, closed or partly open data center networks by enabling seamless integration with existing data center environments and new technologies; unrestricted extensibility and customization; visibility aligned with the needs of the enterprise; full automation capabilities; and easy testing and validation.
 
An ideal NOS for the cloud and digital era will allow network teams to apply the full range of innovative data center technologies—containers, microservices, model-driven approaches, on-change telemetry, standard interfaces, hardened routing capabilities and more—to achieve their automation ambitions.
 
Of course, the NOS can’t do it all.
 
Network teams also need cloud-native automation platforms to help them use the right technologies, simplify their operations and keep pace with escalating scalability and performance demands.
 
For example, tools that support declarative, intent-based automation can remove manual effort and errors from data center fabric design, deployment and operations. Tools based on open frameworks and microservices can make it easier to adopt NetOps approaches that improve service agility, scalability and operational efficiency and support CI/CD principles.
 
Effective risk management will be a critical capability for network teams as they introduce new automation capabilities to the data center fabric. Toolkits that include a fully emulated data center environment or “digital sandbox,” supporting an integrated network digital twin capability can provide a safe way to test and validate network changes before putting them into the live network.


Unlocking operational freedom with data center network automation

A data center fabric solution that combines a modern, open NOS with an intent-based NAP can provide an enterprise with the foundation for extending network automation to every phase of data center network operations.
 
These essential solution components unlock operational freedom and make data center fabrics more efficient, scalable and reliable. They can give any enterprise a competitive edge by ensuring that their data centers networks will be ready to adapt to any current or future customer demand.

About The Author


Charuhas Ghatge is a principal product and solutions marketing professional at Nokia. He is responsible for promoting Data Center Automation and SD-WAN/SASE products and solutions for service providers and enterprises. Charuhas has held a number of engineering, product management and product marketing roles during his 27 years in the networking industry at Cisco, Dell and Juniper Networks. He was educated at the University of Oklahoma with a master's degree in computer science.


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