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# Monitoring Integrations

Cube Cloud allows exporting logs and metrics to external monitoring tools so you
can leverage your existing monitoring stack and retain logs and metrics for the
long term.

<InfoBox>

Available on [Enterprise and above plans](https://cube.dev/pricing).
You can also choose a [Monitoring Integrations tier](/product/administration/pricing#monitoring-integrations-tiers).

</InfoBox>

<WarningBox>

Monitoring integrations suspend their work when a deployment goes to [auto-suspension][ref-autosuspend].

</WarningBox>

Monitoring integrations are only available for [production environments][ref-prod-env].

Under the hood, Cube Cloud uses [Vector][vector], an open-source tool for
collecting and delivering monitoring data. It supports a [wide range of
destinations][vector-docs-sinks], also known as _sinks_.

<Diagram src="https://ucarecdn.com/17dbc263-2be4-4b7d-9f34-270cd66e878b/" />

<YouTubeVideo
  url="https://www.youtube.com/embed/iPD0axEYU6k"
  aspectRatio={4/2.87}
/>

## Guides

Monitoring integrations work with various popular monitoring tools. Check the
following guides and configuration examples to get tool-specific instructions:

<Grid imageSize={[56, 56]}>
  <GridItem
    url="monitoring/cloudwatch"
    imageUrl="https://static.cube.dev/icons/aws.svg"
    title="Amazon CloudWatch"
  />
  <GridItem
    url="monitoring/s3"
    imageUrl="https://static.cube.dev/icons/aws.svg"
    title="Amazon S3"
  />
  <GridItem
    url="monitoring/datadog"
    imageUrl="https://static.cube.dev/icons/datadog.svg"
    title="Datadog"
  />
  <GridItem
    url="monitoring/grafana-cloud"
    imageUrl="https://static.cube.dev/icons/grafana.svg"
    title="Grafana Cloud"
  />
  <GridItem
    url="monitoring/new-relic"
    imageUrl="https://static.cube.dev/icons/new-relic.svg"
    title="New Relic"
  />
</Grid>

## Configuration

To enable monitoring integrations, navigate to <Btn>Settings → Monitoring
Integrations</Btn> and click <Btn>Enable Vector</Btn> to add a Vector agent to
your deployment. You can use the dropdown to select a [Monitoring Integrations
tier](/product/administration/pricing#monitoring-integrations-tiers).

<Screenshot src="https://ucarecdn.com/bf05182f-bbb0-4c20-a95e-ca7aeb03829e/" />

Under <Btn>Metrics export</Btn>, you will see credentials for the
`prometheus_exporter` sink, in case you'd like to setup [metrics
export][self-sinks-for-metrics].

Additionally, create a [`vector.toml` configuration file][vector-docs-config]
next to your `cube.js` file. This file is used to keep sinks configuration. You
have to commit this file to the main branch of your deployment for Vector
configuration to take effect.

### Environment variables

You can use environment variables prefixed with `CUBE_CLOUD_MONITORING_` to
reference configuration parameters securely in the `vector.toml` file.

Example configuration for exporting logs to
[Datadog][vector-docs-sinks-datadog]:

```toml
[sinks.datadog]
type = "datadog_logs"
default_api_key = "$CUBE_CLOUD_MONITORING_DATADOG_API_KEY"
```

### Inputs for logs

Sinks accept the `inputs` option that allows to specify which components of a
Cube Cloud deployment should export their logs:

| Input name | Description |
| --- | --- |
| `cubejs-server` | Logs of API instances |
| `refresh-scheduler` | Logs of the refresh worker |
| `warmup-job` | Logs of the [pre-aggregation warm-up][ref-preagg-warmup] |
| `cubestore` | Logs of Cube Store |
| `query-history` | [Query History export](#query-history-export) |

Example configuration for exporting logs to
[Datadog][vector-docs-sinks-datadog]:

```toml
[sinks.datadog]
type = "datadog_logs"
inputs = [
  "cubejs-server",
  "refresh-scheduler",
  "warmup-job",
  "cubestore"
]
default_api_key = "da8850ce554b4f03ac50537612e48fb1"
compression = "gzip"
```

When exporting Cube Store logs using the `cubestore` input, you can filter logs
by providing an array of their severity levels via the `levels` option. If not
specified, only `error` and `info` logs will be exported.

| Level   | Exported by default? |
| ------- | -------------------- |
| `error` | ✅ Yes               |
| `info`  | ✅ Yes               |
| `debug` | ❌ No                |
| `trace` | ❌ No                |

<InfoBox>

If you'd like to adjust severity levels of logs from API instances and the
refresh scheduler, use the <EnvVar>CUBEJS_LOG_LEVEL</EnvVar> environment variable.

</InfoBox>

### Sinks for logs

You can use a [wide range of destinations][vector-docs-sinks] for logs,
including the following ones:

- [AWS Cloudwatch][vector-docs-sinks-cloudwatch]
- [AWS S3][vector-docs-sinks-s3], [Google Cloud Storage][vector-docs-sinks-gcs],
  and [Azure Blob Storage][vector-docs-sinks-azureblob]
- [Datadog][vector-docs-sinks-datadog]

Example configuration for exporting all logs, including all Cube Store logs to
[Azure Blob Storage][vector-docs-sinks-azureblob]:

```toml
[sinks.azure]
type = "azure_blob"
container_name = "my-logs"
connection_string = "DefaultEndpointsProtocol=https;AccountName=mylogstorage;AccountKey=storageaccountkeybase64encoded;EndpointSuffix=core.windows.net"
inputs = [
  "cubejs-server",
  "refresh-scheduler",
  "warmup-job",
  "cubestore"
]

[sinks.azure.cubestore]
levels = [
  "trace",
  "info",
  "debug",
  "error"
]
```

### Inputs for metrics

Metrics are exported using the `metrics` input. Metrics will have their respective
metric names and_types: [`gauge`][vector-docs-metrics-gauge] or
[`counter`][vector-docs-metrics-counter].

All metrics of the `counter` type reset to zero at the midnight (UTC) and increment
during the next 24 hours.

You can filter metrics by providing an array of _input names_ via the `list` option.

| Input name | Metric name, type | Description |
| --- | --- | --- |
| `cpu` | `cube_cpu_usage_ratio`, `gauge` | CPU usage of a particular node in the deployment. Usually, a number in the 0—100 range. May exceed 100 if the node is under load  |
| `memory` | `cube_memory_usage_ratio`, `gauge` | Memory usage of a particular node in the deployment. Usually, a number in the 0—100 range. May exceed 100 if the node is under load |
| `requests-count` | `cube_requests_total`, `counter` | Number of API requests to the deployment |
| `requests-success-count` | `cube_requests_success_total`, `counter` | Number of successful API requests to the deployment |
| `requests-errors-count` | `cube_requests_errors_total`, `counter` | Number of errorneous API requests to the deployment |
| `requests-duration` | `cube_requests_duration_ms_total`, `counter` | Total time taken to process API requests, milliseconds |
| `requests-success-duration` | `cube_requests_duration_ms_success`, `counter` | Total time taken to process successful API requests, milliseconds |
| `requests-errors-duration` | `cube_requests_duration_ms_errors`, `counter` | Total time taken to process errorneous API requests, milliseconds |

You can further filter exported metrics by providing an array of `inputs`. It applies to
metics only.

Example configuration for exporting all metrics from `cubejs-server` to
[Prometheus][vector-docs-sinks-prometheus] using the `prometheus_remote_write`
sink:

```toml
[sinks.prometheus]
type = "prometheus_remote_write"
inputs = [
  "metrics"
]
endpoint = "https://prometheus.example.com:8087/api/v1/write"

[sinks.prometheus.auth]
# Strategy, credentials, etc.

[sinks.prometheus.metrics]
list = [
  "cpu",
  "memory",
  "requests-count",
  "requests-errors-count",
  "requests-success-count",
  "requests-duration"
]
inputs = [
  "cubejs-server"
]
```

### Sinks for metrics

Metrics are exported in the Prometheus format which is compatible with the
following sinks:

- [`prometheus_exporter`][vector-docs-sinks-prometheus-exporter] (native to
  [Prometheus][prometheus], compatible with [Mimir][mimir])
- [`prometheus_remote_write`][vector-docs-sinks-prometheus] (compatible with
  [Grafana Cloud][grafana-cloud])

Example configuration for exporting all metrics from `cubejs-server` to
[Prometheus][vector-docs-sinks-prometheus-exporter] using the
`prometheus_exporter` sink:

```toml
[sinks.prometheus]
type = "prometheus_exporter"
inputs = [
  "metrics"
]

[sinks.prometheus.metrics]
list = [
  "cpu",
  "memory",
  "requests-count",
  "requests-errors-count",
  "requests-success-count",
  "requests-duration"
]
inputs = [
  "cubejs-server"
]
```

Navigate to <Btn>Settings → Monitoring Integrations</Btn> to take the
credentials `prometheus_exporter` under <Btn>Metrics export</Btn>:

<Screenshot src="https://ucarecdn.com/7db3949b-83b9-48ae-b4b6-bd2afeda5001/" />

You can also customize the user name and password for `prometheus_exporter` by
setting `CUBE_CLOUD_MONITORING_METRICS_USER` and
`CUBE_CLOUD_MONITORING_METRICS_PASSWORD` environment variables, respectively.

## Query History export

With Query History export, you can bring [Query History][ref-query-history] data to an
external monitoring solution for further analysis, for example:
* Detect queries that do not hit pre-aggregations.
* Set up alerts for queries that exceed a certain duration.
* Attribute usage to specific users and implement chargebacks.

<InfoBox>

Requires the [M tier](/product/administration/pricing#monitoring-integrations-tiers)
of Monitoring Integrations.

</InfoBox>

<YouTubeVideo
  url="https://www.youtube.com/embed/6Xf2ayeQZC8"
  aspectRatio={4/3}
/>

To configure Query History export, add the `query-history` input to the `inputs`
option of the sink configuration. Example configuration for exporting Query History data
to the standard output of the Vector agent:

```toml
[sinks.my_console]
type = "console"
inputs = [
  "query-history"
]
target = "stdout"
encoding = { codec = "json" }
```

Exported data includes the following fields:

| Field | Description |
| --- | --- |
| `trace_id` | Unique identifier of the API request. |
| `account_name` | Name of the Cube Cloud account. |
| `deployment_id` | Identifier of the [deployment][ref-deployments]. |
| `environment_name` | Name of the [environment][ref-environments], `NULL` for production. |
| `api_type` | Type of [data API][ref-apis] used (`rest`, `sql`, etc.), `NULL` for errors. |
| `api_query` | Query executed by the API, represented as string. |
| `security_context` | [Security context][ref-security-context] of the request, represented as a string. |
| `status` | Status of the request: `success` or `error`. |
| `error_message` | Error message, if any. |
| `start_time_unix_ms` | Start time of the execution, Unix timestamp in milliseconds. |
| `end_time_unix_ms` | End time of the execution, Unix timestamp in milliseconds. |
| `api_response_duration_ms` | Duration of the execution in milliseconds. |
| `cache_type` | [Cache type][ref-cache-type]: `no_cache`, `pre_aggregations_in_cube_store`, etc. |

<ReferenceBox>

See [this recipe][ref-query-history-export-recipe] for an example of analyzing data from
Query History export. 

</ReferenceBox>


[ref-autosuspend]: /product/deployment/cloud/auto-suspension#effects-on-experience
[self-sinks-for-metrics]: #configuration-sinks-for-metrics
[vector]: https://vector.dev/
[vector-docs-config]: https://vector.dev/docs/reference/configuration/
[vector-docs-sinks]: https://vector.dev/docs/reference/configuration/sinks/
[vector-docs-sinks-cloudwatch]:
  https://vector.dev/docs/reference/configuration/sinks/aws_cloudwatch_logs/
[vector-docs-sinks-s3]:
  https://vector.dev/docs/reference/configuration/sinks/aws_s3/
[vector-docs-sinks-azureblob]:
  https://vector.dev/docs/reference/configuration/sinks/azure_blob/
[vector-docs-sinks-gcs]:
  https://vector.dev/docs/reference/configuration/sinks/gcp_cloud_storage/
[vector-docs-sinks-datadog]:
  https://vector.dev/docs/reference/configuration/sinks/datadog_logs/
[vector-docs-sinks-prometheus]:
  https://vector.dev/docs/reference/configuration/sinks/prometheus_remote_write/
[vector-docs-sinks-prometheus-exporter]:
  https://vector.dev/docs/reference/configuration/sinks/prometheus_exporter/
[vector-docs-metrics-gauge]:
  https://vector.dev/docs/about/under-the-hood/architecture/data-model/metric/#gauge
[vector-docs-metrics-counter]:
  https://vector.dev/docs/about/under-the-hood/architecture/data-model/metric/#counter
[prometheus]: https://prometheus.io
[mimir]: https://grafana.com/oss/mimir/
[grafana-cloud]: https://grafana.com/products/cloud/
[ref-prod-env]: /product/administration/deployment/environments#production-environment
[ref-preagg-warmup]: /product/deployment/cloud/warm-up#pre-aggregation-warm-up
[ref-query-history]: /product/administration/monitoring/query-history
[ref-deployments]: /product/deployment/cloud/deployments
[ref-environments]: /product/administration/deployment/environments
[ref-apis]: /product/apis-integrations
[ref-security-context]: /product/auth/context
[ref-cache-type]: /product/caching#cache-type
[ref-query-history-export-recipe]: /product/administration/monitoring/query-history-export