The march toward greater automation will likely continue unabated, although it might not be as easy, or as straightforward, as it seems.
Today’s networks are required to support a much higher volume of data than ever before. Internet of Things (IoT) and cloud-focused digital transformation are pushing network limits. With so many unique data sets, automation could be the difference between network outages and network connectivity.
Understanding the critical role automation plays in responding to future business and market changes, Ciena recently sponsored an independent research report by ACG Research to highlight the current state of adaptive networking and further explore service provider motivations and implementations as they transform their networks to meet customer demands.
Overall, the study found that network automation investments are expected to grow by approximately 30 percent between now and 2021, with 75 percent of respondents expecting to achieve full or significant network automation in the next 5 years, driven by demands for faster service delivery, improved customer satisfaction, and increased agility. The two critical elements of an effective network automation stack are analytics and security. Other factors such as programmability and access to performance data rate higher in some organizations than others. But more than half of the survey field considers openness and interoperability as very important to their automated environment, and more than 80 percent plan to use open source software in some capacity.
Network automation is a meaningful step toward AI that can provide enhanced mission delivery today. By leveraging automation capabilities within the network, immediate efficiencies can be realized.
Automated processes give IT professionals back the time needed to proactively focus on efforts like improving cyber security and mission deliverables, rather than on day-to-day break-fix events. Network automation improves operational efficiency across the entire enterprise and can address current IT maintenance spending concerns that constrain most budgets.
IoT orchestration solutions can help facilitate these automation efforts. Organizations can automate the entire network lifecycle by integrating workflows across multiple IT domains for end-to-end automation. It allows companies to improve their IT operations and drive greater business agility. What used to require any number of server, storage, and network administrators to provision and troubleshoot services can now be orchestrated with tools, using programmatic languages that can utilize Application Programmatic Interfaces (API) to effect changes based on pre-built workflows that trigger on specific events without human intervention. These automation capabilities are the precursor to AI across the enterprise.
At first blush, the fact that network automation is also taking place alongside other significant changes to infrastructure, namely hyperconvergence and hyperscalability, may appear to be a significant challenge. But if handled properly, the enterprise may be able to turn this to its advantage. Emerging hyperconverged platforms may provide the means to implement network automation far more quickly compared to legacy infrastructure.
Ultimately, there is not much of the network stack that automation will not be able to touch. But that does not mean the enterprise can simply add an automation layer on top of existing management platforms and then let it go to work. With the kinds of advanced, intelligent automation systems entering the channel, it is best to take a gradual approach – automating the most routine, predictable aspects of network management first before moving on to higher-order functions.
Working together, automation and orchestration simplify network operations involving complex configurations and devices’ management while providing business agility to adapt to an ever-changing environment. Automation is thought of as accomplishing repeatable tasks without human intervention, and orchestration as the process of stringing together a series of these tasks to accomplish a process or workflow.
Driving network automation is the rapid expansion of network infrastructure required to support the exponential growth of network traffic generated by video, social media, data, and applications’ usage. Additionally, as computing power continues to decline in cost and virtual computing continues to grow, network automation becomes more available to many businesses. Various types of network automation can apply to local area networks, virtualized environments, data centers, and public and private clouds.
For many organizations, the lack of agility to adopt to network changes has become a bottleneck, preventing those companies from deploying a robust and highly responsive data center infrastructure. For service providers, automation is the cornerstone strategy to focus on to increase network agility and reliability while controlling operational expenditures (OpEx) and capital expenditures (CapEx). To improve operational efficiency, margins, and customer satisfaction, service providers can automate routine and complex tasks that may be time-consuming, repetitive, or error-prone. The openness and interoperability of automation support APIs, standards-based protocols, and open-source automation frameworks. Service providers and enterprises can leverage those automation frameworks to expedite their network automation migration.
Automation could simplify many networking tasks – but it also poses new risks for massive errors that replicate at scale. New platforms are rolling out at a steady clip. They promise the eventual transition from simple automation to intelligence-driven autonomy, but this should not blind networking executives to the fact that these technologies must be deployed carefully with safeguards in place to prevent potentially catastrophic disruption to data operations.
And despite the steadily advancing technology, automation cannot be expected to be the cure-all for enterprise networking woes. Juniper’s James Kelly uses an old adage to point out one potential flaw: To err is human; to propagate errors massively at scale is automation. In other words, when mistakes are built into network processes to begin with, they can lead to massive failures once the repetitive nature of automation kicks in. One of the biggest mistakes network engineers make is to identify a key problem and then attempt to hack it with automation. This is a sure way to produce conflict and confusion with the broader data environment since it is likely that other engineers are doing the same thing to solve their problems. The smart approach is to step back from the day-to-day and develop automation in a strategic fashion, targeting enterprise-wide objectives. Once that is in place, automating specific tasks becomes easier because it takes place within a properly defined framework.
Putting autonomous bots in charge of network provisioning and management can also lead to unintended complications if they are not subject to adequate auditing and compliance. Bots have already infiltrated social media, ecommerce, and a host of other digital functions, so there is no reason to suspect they will stay clear of the enterprise network much longer. But as with most technologies, success is usually a matter of proper execution, which in turn requires a clear understanding of the goals and objectives to be met.