Stop Hardware Failures
From Ruining AI Training.
When a single broken cable or overheating GPU crashes your entire cluster, you lose time and money. Telemetray detects hardware issues before they happen and automatically reorganizes your training run to prevent downtime.
$ ./telemetray_rs/target/release/broker --port 8000
[Broker] Listening on 127.0.0.1:8000
[Broker] Dynamically registered Node node-1 -> GPU UUID-1
[Broker] Dynamically registered Node node-2 -> GPU UUID-2
[Broker WARNING] Broadcasting NODE_ENDANGERED for node-2
[Scheduler] Triggering Forward Recovery. Evicting node-2 seamlessly.
[Scheduler] Rebuilding NCCL communicator ring...
[Scheduler] Training resumed. 0 crashes.Predictive Issue Detection
Continuously monitors the physical health of your network switches, cables, and GPUs to spot tiny anomalies before they trigger a catastrophic system crash.
Zero-Downtime Eviction
Instantly quarantines failing servers from the cluster. The remaining healthy machines automatically resume the workload seamlessly, without requiring manual restarts.
Automated Re-integration
Once a broken server is repaired or cools down, Telemetray automatically adds it back into the active training pool, ensuring you get maximum performance from your hardware.
Ready for resilient training?
We are currently granting early access to infrastructure teams running distributed PyTorch workloads at scale.
Thank you! We'll be in touch shortly.