The New Era of Operational Support Systems

What Are OSS?

Operational Support Systems (OSS) are software systems that assist companies in monitoring, managing, and controlling Telecommunications Networks and services.

OSS plays a crucial role as it enables companies to ensure service continuity, network maintenance, and efficient resource management, thereby delivering highly reliable and quality services to end customers.

Typical characteristics of OSS systems include:

Resource Management: monitoring and management of network resources such as servers, routers, switches, and other network devices;

Service Activation: the process of activating new services for customers, such as creating new phone lines or activating internet services;

Performance Monitoring and Diagnostics: real-time network performance monitoring, anomaly detection, and network issue diagnostics to enable timely interventions;

Order and Customer Management: workflow management for new service orders, modification of existing services, and customer request management.

These systems are essential for modern telecommunications companies and communication networks as they allow for effective and reliable management of complex and extensive network environments.


An OSS system can be designed using microservices, where each microservice handles a specific phase within the entire chain. One of the most interesting chains involves network equipment alarms. Telecommunications companies manage a vast number of network devices, which can experience various malfunctions, such as a network interface going offline, a router's processor overheating, or a Key Performance Indicator (KPI) falling below a certain threshold. Each time one of these events occurs, an alarm is generated and must be conveyed to the operator. Therefore, several microservices are involved in this chain, including the one responsible for interfacing with and receiving alarms from network devices. At this point, there are other microservices that enrich and correlate the received alarms, while others handle database management and data aging.

At this stage, we can consider creating an OSS system using the Cloud. Thanks to the Cloud, there are several advantages that OSS systems can obtain:

Flexibility and Agility: This is useful in OSS systems because new interfaces often need to be added for new devices. These interfaces may not always be built using the same technologies.

With the Cloud, it's possible to create new containers on-demand with different configurations, allowing for interfacing with new devices;

Cost Reduction: the Cloud offers cost savings by eliminating the need to purchase hardware and manage it. With the Cloud, you pay for the resources you use;

Security and Reliability: since OSS systems require high levels of reliability and cannot tolerate down time, the security and reliability provided by the Cloud through replication and backups play a crucial and fundamental role.

There are various challenges in creating a distributed OSS system, as using the Cloud necessitates making the system distributed. One significant challenge is ensuring that alarms are received in the correct order, which becomes more difficult to implement when the system scales and has multiple parallel instances of the same microservice.

Case Study

One of the leading national Telco Operators already leverages the Cloud for its OSS systems. This system is used for its business customers, namely those who pay millions to access connectivity services. This helps convey the idea of security and reliability achievable through the Cloud.

In an OSS system, the main services utilized include:

Kubernetes: used for creating containers to run micro-services, the front-end interface, and Kafka, which is used for message exchange between micro-services;

Monitoring and logging service: employed to monitor and manage any issues encountered by the system;

Reporting services: utilized to generate dashboards and charts regarding device Key Performance Indicators (KPIs);

Storage and database services: used to store all data produced by the systems

User management and authentication services: Used to oversee access to cloud resources and control who can do what within the system.

Machine Learning and OSS

Machine learning doesn't directly integrate into OSS but leverages data from network devices. Network devices continuously send alarms, which are saved and stored in databases.

These alarms often indicate malfunctions or Key Performance Indicators (KPIs) falling below threshold values, sometimes with the corresponding KPI value. Machine learning models or artificial intelligence can be developed to use these alarms as input.

There are various use cases:

Fault Prediction: using alarms that also contain the identifier of the device generating them, it's possible to develop a model capable of predicting faults in devices based on the incoming alarms;

Churn Prediction: in this case, the goal is to predict when a customer is about to terminate their contract based on service disruptions. This type of prediction is highly valuable for businesses as it allows them to intervene promptly to prevent cancellations.

Currently, these are just potential applications of machine learning and AI in the world of OSS, as they may not yet be in production.


In conclusion, OSS plays a crucial role in various telecommunications companies and is considered a mission-critical system. It serves as the primary means through which a company becomes aware of faults and issues on the network.

The features of the cloud offer many critical advantages for systems of this type, as mentioned above, and there is an ongoing migration to the cloud for legacy systems and direct cloud-based development for new systems.

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