Core network visibility. Finally structured.

Wirelake decodes GTP-U and GTP-C tunnels at 100Gbps and delivers subscriber-level flow analytics as structured Parquet — directly into your data lake, without probes, without sampling, without custom pipelines.

The RAN is visible. The internet edge is visible. The core is a black box.

Mobile network teams have invested heavily in RAN analytics and edge monitoring. But the mobile core — where GTP tunnels carry subscriber traffic between the RAN and the packet gateway — remains largely opaque. Existing approaches involve expensive dedicated probes, point-in-time sampling, or custom ETL pipelines that require constant maintenance. The result: subscriber-level analytics that are delayed, incomplete, or impossible to query at scale. Wirelake changes this. It runs directly on your capture hardware, decodes GTP-U and GTP-C natively, and writes per-subscriber flow records to Parquet — ready for your analytics stack the moment they hit disk.

Use Cases

What becomes possible with structured core network data.

Subscriber experience analytics

Per-subscriber flow records keyed by TEID, IMSI, and APN. Build session-level analytics across your entire user base without sampling or probe infrastructure.

Capacity planning

Aggregate traffic volumes, peak throughput, and per-APN demand trends from the same Parquet data your operations team already queries.

Incident investigation

When a degradation event is reported, query the exact GTP tunnel records for the affected TEID or IMSI at nanosecond resolution — not a rolling average.

Regulatory reporting

Structured, auditable per-subscriber records ready for lawful intercept metadata and regulatory data retention requirements.

Network planning

Understand protocol distribution, subscriber density, and interface utilisation across your core to plan capacity and routing changes with confidence.

GTP-native decoding at carrier scale.

  • → GTP-U and GTP-C (full tunnel decode including inner IP headers and TEID extraction)
  • → 100Gbps sustained
  • → Per-subscriber records (keyed by TEID, IMSI, and APN)
  • → Hive-partitioned Parquet
  • → On-premises deployment
  • → Arrow Flight SQL federation
  • → Open query layer

Bring structure to your core network data.

We work with carrier data engineering teams to scope and run a proof of concept. Contact us to discuss your GTP environment and data volumes.

Get a Demo →