The Customer: Who they are
A national telecom operator generating massive volumes of network performance data across its mobile infrastructure.
The Challenge: Identifying the villain
On-premises infrastructure couldn’t keep pace with network data volumes — analysis of network degradation events happened hours after the fact, long after the issue affected customers. “We were doing forensics, not monitoring,” said the Head of Network Operations.
The Journey: The search for a solution
The operator considered a generic infrastructure-only cloud migration, but a vendor assessment showed it would move the same batch-oriented bottleneck to more expensive infrastructure without solving the latency problem.
The Discovery: Finding IDS
The operator engaged IDS as a Google Cloud Partner specifically for data-intensive workload migration experience, not generic infrastructure consulting.
The Solution: The hero arrives
IDS architected a cloud-native network analytics platform on BigQuery and Dataflow, built for streaming ingestion at telco scale, replacing nightly batch loads with near-real-time processing of network events.
The Implementation: The battle
Migration ran region by region, validating latency and accuracy at each stage before expanding. The obstacle: legacy network monitoring tools produced inconsistent event formats across equipment vendors; IDS built a normalization layer at ingestion to unify them.
The Results: The happy ending
- Network event detection latency: hours → minutes
- Infrastructure cost per TB processed: reduced 28%
- Uptime of the analytics platform: 99.9%
- Network incidents identified proactively vs. reactively: significant increase
“We see problems before customers start calling about them.” — Head of Network Operations
Technologies used: Google BigQuery · Google Dataflow (Google Cloud Partner delivery)