Integration with Datadog

Datadog (opens in a new tab) is a popular fully managed observability service. This guide demonstrates how to set up Cube Cloud to export logs and metrics to Datadog.

Configuration

First, enable monitoring integrations in Cube Cloud.

Exporting logs

To export logs to Datadog, go to Organization Settings → API Keys obtain an API key:

Then, configure the datadog_logs (opens in a new tab) sink in your vector.toml configuration file.

Example configuration:

[sinks.datadog_logs]
type = "datadog_logs"
inputs = [
  "cubejs-server",
  "refresh-scheduler",
  "warmup-job",
  "cubestore"
]
default_api_key = "$CUBE_CLOUD_MONITORING_DATADOG_API_KEY"
site = "datadoghq.eu"
compression = "gzip"
healthcheck = false

Note that Datadog accounts belong to specific sites (opens in a new tab) throughout the world. Use the site option to configure the sink appropriately. When miscofigured, Vector agent outputs the following error: Client request was forbidden.

Commit the configuration for Vector, it should take effect in a minute. Then, navigate to Logs in Datadog and watch the logs coming:

Exporting metrics

To export metrics to Datadog, use the same API key from Organization Settings → API Keys as configured for logs.

Then, configure the datadog_metrics (opens in a new tab) sink in your vector.toml configuration file.

Example configuration:

[sinks.datadog_metrics]
type = "datadog_metrics"
inputs = [
  "metrics"
]
default_api_key = "$CUBE_CLOUD_MONITORING_DATADOG_API_KEY"
site = "datadoghq.eu"

Again, upon commit the configuration for Vector should take effect in a minute. Then, navigate to Metrics → Summary in Datadog and explore the available metrics. Cube metrics are prefixed with cube_, such as cube_cpu_usage_ratio, cube_memory_usage_ratio, and cube_requests_total.