Introduction

The realm of digital has become essential to our daily lives. As the IT industry advances at a breathtaking pace, the need to revolutionize networking as it were is at its peak. We transcended beyond clunky, traditional networks to an age of customer-focused solutions, and Network Operation Centres (NOC) have been at the center of this transformation. 

To put it simply, the NOC is the central nervous system of the mobile network infrastructure. It is not only the first line of defense against potential threats but also ensures seamless data inflow and outflow. However, the idea that this is all driven by machines is a misconception, for if the NOC is the brain of the entire operation, then NOC operators are its heart.

Problem Statement

Simplifying NOC Operations and network states through automated, deep insight-driven AI-ML systems

Network Operation Centres are hubs of bustling activity when it comes to monitoring transactions, traffic, and user patterns. The NOC operator acts as a liaison between the customer and the network infrastructure to solve any issues related to the above. They are an invaluable resource in the technology puzzle, but are also amongst the most overburdened, owing to inefficient process management, lack of agile working environments, and pre-existing redundancies. 

The traditional NOC system involves multiple dashboard screens parallelly in use, with each individual request catered separately. This involves a massive investment of time and effort for the operator, often coupled with a slow delivery and issue resolution.  

Overview: Multitasking like a Pro

NOC engineers may find themselves juggling hundreds of requests at the same time. These ticketing requests are often unrelated to each other and would need immediate resolution. Faults may range from server issues, software bugs, or physical defects at the site of the network tower. Thus, the requirement for an automated, agile, and intuitive NOC system is increasingly apparent in a digital-first era.  

The key requirements of a modernized NOC setup include:

NOC engineers may find themselves juggling hundreds of requests at the same time. These ticketing requests are often unrelated to each other and would need immediate resolution. Faults may range from server issues, software bugs, or physical defects at the site of the network tower. Thus, the requirement for an automated, agile, and intuitive NOC system is increasingly apparent in a digital-first era.  

The key requirements of a modernized NOC setup include:

NOC operators working in a centralized location struggle to keep track of time, incident management, and service resolution 24×7, and this is where the need for an end-to-end dissolution model comes in. Here is where the Design Thinking approach can make a world of difference. A human-centric approach to solving these complex problems not only enables deeper customer engagement but also allows for creative, critical solutions that go beyond just usability.  

This is why AI & ML techniques come in handy – to reduce not just the number of tickets created per problem, but also dispatching them on time. Rule mining, problem classification techniques, and time series predictions have been able to successfully decrease the time to dispatch requests. 

Keeping this in mind, the iauro team has developed a state-of-the-art application to digitize network operations effectively. With microservices at its core, this application will be used by NOC operators and decision-makers to primarily deal with identity management and email servers effectively. In this particular case, the approaches for each problem are tentative and would be finalized post the data analysis for alarms raised, incident management, and KPI-related requirements.  

App and Data Architecture

What efficiency is made of 

Well-built mobile and web apps are defined by the easy accessibility and stability of their individual components. Thus, creating this skeleton in a manner that allows for both cost and resource efficiency becomes imperative at every step of the way.  

In this case, the front end of the application consists of DAAIP applications and component libraries. The DAAIP unit consists of the following modules: 

The application’s backend is microservices-based, and runs on a combination of LDAP platform authentication mechanisms and reporting services. This provides NOC operators with a real-time view of current issues in the network, with cohesive email updates and notifications along with an audit trail. A microservices-enabled environment tackles complexity by decomposing applications into smaller, more manageable clusters that are easier to maintain. It also enables independent development and delivery at the ease of the developer, with more accurate error detection, readable programs, and reusable codes.  

Data Model

The foundation that holds it all together 

In any modernized application, the main role of a data model is to support the development of information systems by providing the system with the correct definition and format of data, such that there is no lag between its inflow and outflow.

The app functions on five data processing pipelines including the following: 

Data Toolset

Open Source Bigdata Toolset