Exporting Turbo pipeline metrics to your own observability stack

Enterprise only. A dedicated Prometheus endpoint is available to enterprise customers who want to route Turbo pipeline metrics into their own observability stack. If you would like access, contact support@goldsky.com or reach out to your account manager.

Overview

If you already run your own observability stack (Datadog, Grafana Cloud, New Relic, etc.), you don’t need to build dashboards twice. Every enterprise Turbo project can be provisioned with a scrape-ready Prometheus endpoint that exposes the same streamling_* metrics that power the health dashboard — letting your existing alerting, dashboarding, and incident-response tools see Turbo pipeline health.

Goldsky  ──HTTPS /metrics──▶  your Prometheus-compatible agent  ──▶  Datadog / Grafana / New Relic / PagerDuty / …

Getting access

Contact support@goldsky.com to request the integration. You will receive:

A project-scoped scrape URL.
Credentials for scraping (bearer token or basic auth).
The list of metric names and label conventions available for your project.

All metrics are scoped to your project — you only see metrics for pipelines in the project associated with your credentials.

Prerequisites

A Goldsky API key (generated via the Goldsky CLI or in the Dashboard under Settings → API Keys).
Your project must have Prometheus API access enabled — contact your Goldsky account manager.

Endpoint

Environment	URL
Production	`https://prometheus.goldsky.com`
Dev (internal use only)	`https://prometheus.dev.goldsky.com`

All requests require an Authorization header with your Goldsky API key:

Authorization: Bearer <your-goldsky-api-key>

Testing with curl

Instant query

Run a simple query to verify connectivity:

curl -s 'https://prometheus.goldsky.com/api/v1/query' \
  --data-urlencode 'query=streamling_input_rows_total' \
  -H 'Authorization: Bearer <your-goldsky-api-key>' | jq .

Expected response:

{
  "status": "success",
  "data": {
    "resultType": "vector",
    "result": [
      {
        "metric": {
          "__name__": "streamling_input_rows_total",
          "namespace": "streamling-prod",
          "...": "..."
        },
        "value": [1714800000, "1234567"]
      }
    ]
  }
}

Range query

Query metrics over a time range (last 1 hour, 5-minute steps):

curl -s 'https://prometheus.goldsky.com/api/v1/query_range' \
  --data-urlencode 'query=rate(streamling_input_rows_total[5m])' \
  --data-urlencode 'start='$(date -u -v-1H +%Y-%m-%dT%H:%M:%SZ) \
  --data-urlencode 'end='$(date -u +%Y-%m-%dT%H:%M:%SZ) \
  --data-urlencode 'step=300' \
  -H 'Authorization: Bearer <your-goldsky-api-key>' | jq .

List available metrics

Discover which label names are available:

curl -s 'https://prometheus.goldsky.com/api/v1/labels' \
  -H 'Authorization: Bearer <your-goldsky-api-key>' | jq .

Get all series matching a selector:

curl -s 'https://prometheus.goldsky.com/api/v1/series' \
  --data-urlencode 'match[]=streamling_input_rows_total' \
  -H 'Authorization: Bearer <your-goldsky-api-key>' | jq .

Available API endpoints

Endpoint	Description
`/api/v1/query`	Instant queries
`/api/v1/query_range`	Range queries
`/api/v1/series`	Series metadata
`/api/v1/labels`	Label names
`/api/v1/label/<name>/values`	Label values

Setting up in Grafana

Step 1: Add a Prometheus data source

In your Grafana instance, go to Connections → Data sources → Add data source.
Select Prometheus.

Step 2: Configure the connection

Fill in the following fields:

Field	Value
Name	`Goldsky Prometheus` (or any name you prefer)
Prometheus server URL	`https://prometheus.goldsky.com`

Step 3: Add an authentication header

Scroll down to the Custom HTTP Headers section:

Click Add header.
Set Header to: Authorization.
Set Value to: Bearer <your-goldsky-api-key>.

The value field is treated as a secret — it will be masked after saving.

Step 4: Save & Test

Click Save & Test. You should see:

✅ Successfully queried the Prometheus API.

If you see a 401 or 403 error, verify your API key is correct and that your project has Prometheus access enabled.

Step 5: Explore your metrics

Go to Explore in Grafana.
Select your Goldsky Prometheus data source.
Try a query like:
```
streamling_input_rows_total
```

You can use the metrics browser to discover all available metrics for your project.

Example PromQL queries

The exact metrics available depend on your pipeline type (Turbo, Edge, Subgraph, Compose).

Turbo pipelines

Input row throughput — rows ingested per second over the last 5 minutes:

rate(streamling_input_rows_total[5m])

Output row throughput — rows written to sinks per second:

rate(streamling_output_rows_total[5m])

Block lag — how far behind the chain head (seconds):

streamling_block_lag_max_seconds

Checkpoint epoch duration — time to complete a checkpoint epoch:

rate(streamling_checkpoint_epoch_duration_milliseconds_sum[5m]) / rate(streamling_checkpoint_epoch_duration_milliseconds_count[5m])

Failed checkpoints — checkpoint failures (should be 0):

rate(streamling_checkpoint_epochs_failed_total[5m])

General

CPU usage per pod:

rate(container_cpu_usage_seconds_total{namespace=~"turbo-prod|compose-prod"}[5m])

Memory usage per pod:

container_memory_working_set_bytes{namespace=~"turbo-prod|compose-prod"}

Alerting in Grafana

Once the data source is configured, you can set up alerts in Grafana:

Go to Alerting → Alert rules → New alert rule.
Select your Goldsky Prometheus data source.
Define your query and threshold condition.
Configure a contact point (Slack webhook, email, PagerDuty, etc.).
Save the alert rule.

Example: alert when input row throughput drops to zero for 5 minutes:

rate(streamling_input_rows_total[5m]) == 0

Troubleshooting

Issue	Solution
`401 Unauthorized`	Check that your API key is correct and includes the `Bearer` prefix.
`403 Forbidden`	Your project may not have Prometheus access enabled — contact your account manager.
No metrics returned	Your project may not have active pipelines emitting metrics. Try `curl .../api/v1/labels` to see what’s available.
Grafana Save & Test fails	Ensure the URL has no trailing slash and the `Authorization` header is set correctly under Custom HTTP Headers (not under Basic Auth).

Where the metrics can go

The endpoint uses the standard Prometheus exposition format, so it works with anything that speaks Prometheus. Common destinations fall into three categories:

Observability platforms (push-based)

These ingest the metrics and give you dashboards, monitors, and alerting on top.

Datadog — use the OpenMetrics / Prometheus check on the Datadog Agent. Metrics appear as Datadog metrics and can be used in monitors, dashboards, and SLOs.
New Relic — forward via the Prometheus OpenMetrics integration.
Splunk Observability Cloud / SignalFx — use the Splunk OpenTelemetry Collector with the Prometheus receiver.
AWS CloudWatch / Managed Prometheus — use the AWS Distro for OpenTelemetry to send metrics to Amazon Managed Service for Prometheus or CloudWatch.

Prometheus-compatible storage

If you already run Prometheus or a long-term-storage backend, point it at the endpoint as another scrape target.

Grafana Cloud — scrape via Grafana Alloy or a Grafana Agent.
Self-hosted Prometheus — add the endpoint as a scrape target in prometheus.yml.
VictoriaMetrics, Thanos, Cortex, Mimir — any Prometheus-compatible store can scrape the endpoint directly.

Alerting destinations (indirect)

Paging tools like PagerDuty, Opsgenie, or VictorOps don’t scrape metrics directly. Instead, define alert rules in whatever system is scraping the endpoint (Datadog monitors, Prometheus Alertmanager, Grafana alerts) and route those alerts into your paging tool via its native integration.

Example scrape config

A minimal Prometheus scrape configuration looks like this:

scrape_configs:
  - job_name: goldsky-turbo
    scrape_interval: 30s
    metrics_path: /metrics
    scheme: https
    static_configs:
      - targets:
          - metrics.goldsky.com # provided by support
    authorization:
      type: Bearer
      credentials: ${GOLDSKY_METRICS_TOKEN}

Exact host, path, and auth method will be confirmed when the endpoint is provisioned for your project.

Available metrics

The endpoint exposes the same streamling_* metrics used in the health dashboard. The most commonly alerted on:

Metric	Type	What it tells you
`streamling_block_lag_max_seconds`	Gauge	End-to-end lag behind the chain tip, in seconds.
`streamling_kafka_consumer_messages_lag`	Gauge	Kafka consumer lag per partition for Kafka-backed sources.
`streamling_output_rows_total`	Counter	Cumulative rows emitted by each node (filter by `topology_node_type="sink"` for sink throughput).
`streamling_input_rows_total`	Counter	Cumulative rows consumed by each node.
`streamling_elapsed_compute_milliseconds_bucket`	Histogram	Per-batch compute time, in milliseconds.
`streamling_checkpoint_epochs_failed_total`	Counter	Checkpoint epochs that failed to finalize. Any non-zero value is critical.
`streamling_checkpoint_epochs_succeeded_total`	Counter	Checkpoint epochs that finalized successfully.
`streamling_checkpoint_sink_flush_milliseconds_bucket`	Histogram	Per-sink flush latency on checkpoint markers.
`streamling_checkpoint_epoch_duration_milliseconds_bucket`	Histogram	End-to-end duration between consecutive checkpoint epochs.

Every metric carries these labels:

service_instance_id — unique pipeline identifier; use this to scope a query to a single pipeline.
project_id — your Goldsky project identifier.
id — the node’s reference_name (source, transform, or sink name from your pipeline YAML).
topology_node_type — source, transform, or sink.
operator_type — component implementation (e.g. kafka, postgres, clickhouse, sql).
image_tag — streamling engine version.

Solana sources additionally emit streamling_solana_blocks_per_sec, streamling_solana_buffer_len, streamling_solana_next_slot_to_serve, and streamling_solana_fetch_duration_bucket. Kafka nodes emit streamling_kafka_consumer_msg_decode_latency_bucket, streamling_kafka_producer_batch_send_latency_bucket, streamling_kafka_producer_msg_encode_latency_bucket, and streamling_kafka_consumer_row_kind_count_total (with a kind label of Insert, Update, or Delete). For concrete query examples, see the starter PromQL queries on the custom alerts page.

Next steps

Browse the available metrics inside the Goldsky-hosted Grafana workspace first — see the health dashboard guide.
If you don’t need to bring your own stack, use custom alerts in the Goldsky Grafana workspace for Slack or email notifications without additional setup.

Turbo

API

Reference

Prometheus integration

Overview

Getting access

Prerequisites

Endpoint

Testing with curl

Instant query

Range query

List available metrics

Available API endpoints

Setting up in Grafana

Step 1: Add a Prometheus data source

Step 2: Configure the connection

Step 3: Add an authentication header

Step 4: Save & Test

Step 5: Explore your metrics

Example PromQL queries

Turbo pipelines

General

Alerting in Grafana

Troubleshooting

Where the metrics can go

Observability platforms (push-based)

Prometheus-compatible storage

Alerting destinations (indirect)

Example scrape config

Available metrics

Next steps

Turbo

API

Reference

Documentation Index

​Overview

​Getting access

​Prerequisites

​Endpoint

​Testing with curl

​Instant query

​Range query

​List available metrics

​Available API endpoints

​Setting up in Grafana

​Step 1: Add a Prometheus data source

​Step 2: Configure the connection

​Step 3: Add an authentication header

​Step 4: Save & Test

​Step 5: Explore your metrics

​Example PromQL queries

​Turbo pipelines

​General

​Alerting in Grafana

​Troubleshooting

​Where the metrics can go

​Observability platforms (push-based)

​Prometheus-compatible storage

​Alerting destinations (indirect)

​Example scrape config

​Available metrics

​Next steps

Overview

Getting access

Prerequisites

Endpoint

Testing with curl

Instant query

Range query

List available metrics

Available API endpoints

Setting up in Grafana

Step 1: Add a Prometheus data source

Step 2: Configure the connection

Step 3: Add an authentication header

Step 4: Save & Test

Step 5: Explore your metrics

Example PromQL queries

Turbo pipelines

General

Alerting in Grafana

Troubleshooting

Where the metrics can go

Observability platforms (push-based)

Prometheus-compatible storage

Alerting destinations (indirect)

Example scrape config

Available metrics

Next steps