How To Overcome The Challenges To True End-To-End Automation?

Digital transformation is to be viewed as a holistic approach for improving the overall efficiency of business operations. For it to be regarded as truly holistic, the network should also be included. To increase the effectiveness of the transformation, the initial discussions should include network automation strategies. They should cover the entire planning, analysis, and execution of digital transformation deployments rather than merely focusing on implementing and activating use cases.

You are not doing a disservice to the network, the IT teams that are obliged to support it, the company that runs on the network, and the customers that your decisions are going to impact when you decide to focus on a small aspect of network automation while planning digital transformation and executing it. Here are the limitations of most network automation implementations.

Limited reach: The difficulty in interacting with multiple parts of the network, along with Basic Service Set (BSS) systems and Operations Support Systems (OSS) can limit how far the automation can extend.

Data management: As information is stored throughout the network, it has become extremely difficult to manage everything with a single information source.

Usability: To work in most automation platforms, engineers have to learn to code. This limits their ability to make powerful automation without having to invest valuable time and effort into learning an entirely new skillset.

When we study a little deeper about these challenges, we can figure out the methods and initiatives that would help overcome them when a company treats network automation as a priority.

Realizing The Importance Of End-To-End Automation

According to Metcalfe’s law, the value of a communication network is proportional to the square of the number of nodes in the network. The law explains the exponential growth of the value of a network with every new connection. This is not only seen in communication networks but in other networks as well. For example, the platform Facebook had limited value at the start when it had a less number of users and data but when the users increased, there was a dramatic increase in the value of the platform. Although the mathematical precision of Metcalfe’s law is debated, the basic idea of the law is evident-when the number of connections increases the value increases.

The network automation industry has to realize how relevant Metcalfe’s law is to network automation and how it is will help address the challenges of implementing automation.

Expanding The Reach Of Automation 

Integration increases value. When an automation platform connects to more systems, it can be part of more activities. Each of these connections can be used as a replacement for one or more manual steps that an engineer has to perform on separate systems. The steps include the collection of appropriate data and using that to perform important tasks.

Cost and complexity are two gating factors that stand as barriers to mass integration in most environments. The developers have to develop and maintain integration code for integrations. High integration costs are putting organizations in a position to make difficult choices that make them prioritize the systems they can integrate immediately.

However, when it comes to network automation, costs do not really play any role in determining priorities. Now, organizations have to understand that integrations will drive the future of automation. Integrations require reprioritizing initiatives that promise better flexibility and that happens to be the only way for extending the scope of automation initiatives appropriately.

Federation As A Way To Manage Data 

Data federation can be defined as the ability to harmonize and aggregate data from multiple sources like inventory management systems, network controllers, orchestrators, and performance systems. How good is the data and decide how good the automation is. Hence federation is necessary for managing the large volume of diverse data that is part of large-scale integration.

Aggregating data using a federated system is quite different from the way information is collected by traditional management systems. Traditional systems create a master database by copying bulk amounts of data. This causes issues regarding the timelines and quality of data along with the continuing synchronization challenges.

Federation helps address those concerns with the objective of eliminating them. It accommodated the fast changes to the network by developing a meta-map of the systems and then making real-time queries while executing the workflows.

Attaining Data Transformation

Extracting information from a source, modifying it to make it suitable to be sent to a target device had been tasks that weren’t that easy earlier. Even when it comes to simple use cases, making a change to a service often requires information obtained from different sources including an inventory system, ordering system, and IP address management system. This data is likely to have very different formats as well as native structure, so an engineer has to invest some time and effort in determining relevant fields and the fields that data should be mapped to. After that, they should create a script or any other code for parsing the data, restructuring it, and composing the payload. The process takes a lot of time and involves a high level of complexity.

Complete data manipulation is suggested as the solution to address this challenge. It is a necessity to format and manipulate data in the right way without having to work on extensive coding, thereby ensuring that all integrated systems speak the same language.

Organizations have to address the challenges discussed in the article to extend the scope of their network across, devices, systems, and teams. True end-to-end automation becomes possible only when you recognize the obstacles and implement effective mitigation strategies.