Monitor your orchestrator

A running node isn’t the same as a healthy one. Missed reward calls, a saturated GPU, or an unredeemed-ticket backlog quietly cost you income and gateway reputation. This guide instruments your orchestrator so you see problems before they show up in your earnings.

Logs explain individual incidents; metrics show whether throughput, latency, capacity, and ticket flow are trending the right way. You want both.

1. Enable metrics

go-livepeer exposes a Prometheus endpoint when you start it with -monitor:

livepeer \
  -orchestrator -transcoder \
  -monitor \
  -metricsPerStream \
  -network arbitrum-one-mainnet \
  # ...your other flags

The metrics are served at http://localhost:7935/metrics — the same port as the go-livepeer CLI; -monitor just activates the /metrics path on it.

Flag	What it does
`-monitor`	Enables `/metrics`. Required for any Prometheus scraping.
`-metricsPerStream`	Breaks performance metrics out per stream — useful for diagnosing a single session.
`-metricsClientIP`	Adds the client IP to metric labels, so you can see which gateway is routing to you.

In a split orchestrator/transcoder setup, pass -monitor on both processes — each exposes its own /metrics on its own CLI port.

2. Stand up a dashboard

Fastest: Docker stack
Existing Prometheus

Livepeer maintains an image bundling Prometheus, Grafana, and starter dashboards:

docker pull livepeer/monitoring

docker run --net=host \
  --env LP_MODE=standalone \
  --env LP_NODES=localhost:7935 \
  livepeer/monitoring:latest

Then open Grafana at http://localhost:3000 (default login admin / admin). For multiple nodes, pass a comma-separated list: LP_NODES=node1:7935,node2:7935. LP_MODE also supports docker-compose and kubernetes. Source and dashboards: livepeer/livepeer-monitoring.

Already running Prometheus? Add the node as a scrape target:

# prometheus.yml
scrape_configs:
  - job_name: 'livepeer-orchestrator'
    static_configs:
      - targets: ['localhost:7935']
    scrape_interval: 15s
    metrics_path: /metrics

Reload with kill -HUP <prometheus-pid> or the reload API at http://localhost:9090/-/reload. Add Node exporter (host) and the NVIDIA DCGM exporter (GPU) for full hardware coverage.

3. Watch the signals that matter

Monitor across five layers — the last two are where money is won or lost:

Layer	What to watch	How
Hardware	GPU utilization, VRAM, temperature	`nvidia-smi`, DCGM exporter
Application	Segment / job success rate, session capacity	`/metrics`, dashboard
Network	Latency, packet loss	host monitoring
On-chain	Active-set status, bonded stake, reward calls	Explorer
Economics	ETH fees, LPT rewards	Explorer, `/metrics`

The metrics you’ll actually act on:

Metric	Signal
`livepeer_current_sessions_total` vs `livepeer_max_sessions`	How close to capacity you are (idle → lower price; maxed → add GPU)
`livepeer_segment_processed_total` / `livepeer_segment_errors_total`	Core transcoding health. Rising errors → gateways deprioritize you
`livepeer_transcode_latency_seconds`	GPU saturation or a slow pipeline — both hurt gateway scoring
Winning tickets received vs redeemed	A growing gap means an ETH-balance or redemption problem
Round number & reward-call status	Whether you’re claiming inflation every round

The single highest-value alert: a missed reward() call. Miss a round and that round’s LPT is gone permanently — there’s no catch-up. Alert on it, and keep enough ETH on Arbitrum for gas. See Activate on Arbitrum.

4. Monitor the AI runner (if you serve AI)

AI inference runs in a separate ai-runner container, so watch it independently for a faster signal:

docker ps --filter name=livepeer-ai-runner   # status
docker logs -f livepeer-ai-runner             # live logs
docker stats livepeer-ai-runner               # CPU / mem / GPU usage

Log lines worth alerting on:

Message	Meaning
`Loaded model <id>`	Model is warm in VRAM, ready to process
`Error loading model`	Bad model ID or not enough VRAM
`CUDA out of memory`	VRAM exhausted — lower `capacity` in `aiModels.json` or the model count
`Container health check failed`	Alive but not responding

Confirm your pipelines are actually advertised to the network:

curl http://localhost:7935/getNetworkCapabilities | jq

Cross-check network-wide at tools.livepeer.cloud/ai/network-capabilities.

5. Capture logs

By default logs go to stdout only. For a production node, persist them and know the two debug levers:

# Keep a log file while still printing to the terminal
livepeer -orchestrator -transcoder -monitor ... 2>&1 | tee /var/log/livepeer/livepeer.log

# -v 6 prints per-segment activity — the fastest way to confirm you're receiving work
livepeer -orchestrator -transcoder -v 6 ...

grep -i "reward" /var/log/livepeer/livepeer.log   # confirm reward calls are happening

Also on the Explorer

Even without a metrics stack, explorer.livepeer.org shows your active-set status, bonded and delegated LPT, reward-call history, fee earnings, and historical performance — the fastest external gut-check that your node is healthy and earning.

Configure your orchestrator

The flags these metrics reflect — sessions, GPUs, pricing.

Activate on Arbitrum

Reward calling and the ETH balance your alerts depend on.

Not receiving jobs?

When the dashboard says idle, work through the four causes.

Hardware & GPU

VRAM and session-limit context for capacity metrics.

Get started

Tutorials

How-to guides

Explanation

Reference

Monitor your orchestrator

1. Enable metrics

2. Stand up a dashboard

3. Watch the signals that matter

4. Monitor the AI runner (if you serve AI)

5. Capture logs

Also on the Explorer

Configure your orchestrator

Activate on Arbitrum

Not receiving jobs?

Hardware & GPU

​1. Enable metrics

​2. Stand up a dashboard

​3. Watch the signals that matter

​4. Monitor the AI runner (if you serve AI)

​5. Capture logs

​Also on the Explorer

​Related

Configure your orchestrator

Activate on Arbitrum

Not receiving jobs?

Hardware & GPU

1. Enable metrics

2. Stand up a dashboard

3. Watch the signals that matter

4. Monitor the AI runner (if you serve AI)

5. Capture logs

Also on the Explorer

Related