Apps & SaaSCase study
Real-Time Mobile Tower Management
A multi-tenant, real-time SaaS platform monitoring equipment across close to 60,000 mobile towers, with predictive maintenance to reduce downtime.
Before
- Remote monitoring across a huge tower network
- Streaming data to process at scale
- Insights hard to extract and present
- Equipment failures causing downtime
After
- Real-time ingestion from ~60,000 towers
- A secure multi-tenant SaaS platform
- Real-time analytics and reports
- Predictive maintenance reducing downtime
01 · The challenge
Where they started
A telecommunications provider wanted to monitor and maintain its mobile tower infrastructure remotely: diesel generators, air conditioners, electricity boards and battery banks.
Multi-tenant complexity
Monitoring devices for many tenants while keeping data isolated and secure.
Real-time at scale
Processing streaming data from close to 60,000 towers needed a scalable, responsive architecture.
Analytics
Turning streaming data into real-time insight, presented clearly.
Predictive maintenance
Preventing equipment failures before they caused downtime.
02 · The solution
What we built
DATA LEAGUE designed a scalable, real-time platform with predictive analytics built in.
How it fits together
- ~60,000 towersGenerators, AC, power, batteries
- Azure QueuesStreaming ingestion
- Background workersMicroservices on Azure
- Elasticsearch and SQL ServerAnalytics store
- Web clientMonitoring and predictions
Real-time ingestion
An architecture to ingest and process streaming data from close to 60,000 towers.
Multi-tenant SaaS
Tower-specific monitoring and analytics for each tenant, with data isolation and security.
Microservices on Azure
Microservices and background workers for responsive processing.
Predictive analytics
Predictive maintenance for tower equipment to minimise unplanned downtime.
03 · Delivery
How we delivered it
- 1
Select the stack
Knockout.js, WCF, managed SQL Server, Elasticsearch, Azure Queues, Blobs, App Services, Quartz.NET, reporting and load-testing tools.
- 2
Process in real time
Message ingestion and processing for up-to-the-moment monitoring.
- 3
Build the SaaS
A responsive web client backed by microservices and background workers.
- 4
Predict
Predictive analytics for proactive equipment maintenance.
04 · Results
What changed
Predictive maintenance
Failures pre-empted and tower operations optimised.
Reduced downtime
Measurably less tower downtime and more reliable service.
Responsive at scale
Monitoring thousands of towers simultaneously.
Operational efficiency
Real-time monitoring and analytics for timely decisions.
05 · Technology
Built with
- Azure App Services
- Azure Queues
- Elasticsearch
- SQL Server
- Quartz.NET
- Knockout.js
- WCF
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