Weather-related outages prediction
The time interval between the outage detection, its diagnosis and labeling, went from 20 minutes to less than 1 minute.
Effective outage prediction
SES delivers global content connectivity solutions and is one of the most important satellite operators in the world. SES was the first operator to deliver a differentiated and scalable GEO-MEO offering worldwide, with over 50 satellites in Geostationary Earth Orbit (GEO) and 20 in Medium Earth Orbit (MEO). We teamed up with them to build a MEO monitoring solution for the gateways and their customers' terminals.
Challenge
We were asked to implement intelligent methods for traffic control and rate limiting based on SES top clients' requirements, in the form of a Real-time Traffic Manager (RTM) application. As a network provider, this was a critical missing piece of SES global solution in order to ensure its customers have the best possible service at all times, regardless of the weather conditions.
Solution
With a predictive maintenance and a machine learning approach, now is possible to anticipate the outage, and manage it with the strategy that is best suited for the particular scenario. The system was deployed to be used in real-world production scenarios ensuring high quality Internet connections to SES clients.
Discover our approach
The RTM was built in Python, using the Flask stack to provide a RESTful API that exposes configurations and real time data.
Device connection
The app communicates with external services and uses networking protocols to talk to devices, from which it takes data used as input for the algorithms.
They were responsible for the software layer of an important part of our solution, implementing agile methodologies, great technical skills, daily communication and even on-site visits to our offices.
