# PromQL querying
When you ingest OpenTelemetry metrics into CloudWatch through the [Metrics endpoint](CloudWatch-OTLPEndpoint.md#CloudWatch-MetricsEndpoint), the hierarchical OTLP data model is flattened into PromQL-compatible labels. This section describes the label structure, the PromQL syntax for querying these labels, and the UTF-8 support in PromQL.
**Note**
PromQL in Prometheus 3 supports full UTF-8 characters in metric names and label names. This is particularly important for OTLP metrics, because OpenTelemetry semantic conventions use dots in attribute names such as `service.name`. Previously, these dots were replaced with underscores during translation, causing discrepancies between what was defined in OTel conventions and what was queryable in Prometheus.
When using PromQL in CloudWatch, the `@` prefix convention distinguishes OTLP-scoped labels from standard Prometheus labels. Fields within each scope use a double-`@` prefix (for example, `@resource.@schema_url`), while attributes use a single-`@` scope prefix, for example, `@resource.service.name`. Datapoint attributes also support bare (un-prefixed) access for backward compatibility with standard PromQL queries, for example, `{"http.server.active_requests"}` and `{"@datapoint.@name"="http.server.active_requests"}` are equivalent.
A PromQL expression is enclosed in curly braces, specifying the metric name and an optional set of label matchers. The following example selects all time series for the `http.server.active_requests` metric:
```
{"http.server.active_requests"}
```
The following example selects all time series for the metric `http.server.active_requests` where the OpenTelemetry resource attribute `service.name` equals `myservice`:
```
{"http.server.active_requests", "@resource.service.name"="myservice"}
```
You can combine multiple label matchers in a single query. The following example selects all time series for the `http.server.active_requests` metric where the OpenTelemetry resource attribute `service.name` equals `myservice` across all US regions:
```
{"http.server.active_requests",
"@resource.service.name"="myservice",
"@aws.region"=~"us-.*"}
```
The following example shows a range query. It calculates the average value of all datapoints within a specified time range for each time series:
```
avg_over_time(
{"http.server.active_requests",
"@resource.service.name"="myservice"}[5m]
)
```
The following table summarizes the prefix conventions for each OTLP scope:
| OTLP scope | Fields prefix | Attributes prefix | Example |
| --- | --- | --- | --- |
| Resource | `@resource.@` | `@resource.` | `@resource.service.name="myservice"` |
| Instrumentation Scope | `@instrumentation.@` | `@instrumentation.` | `@instrumentation.@name="otel-go/metrics"` |
| Datapoint | `@datapoint.@` | `@datapoint.` or bare | `cpu="cpu0"` or `@datapoint.cpu="cpu0"` |
| AWS-reserved | N/A | `@aws.` | `@aws.account_id="123456789"` |
## Querying vended AWS metrics with PromQL
To be able to query vended AWS metrics in PromQL, you first need to enable OTel enrichment of vended metrics. See: [AWS vended metrics in OpenTelemetry format](CloudWatch-OTelEnrichment.md).
After you enable OTel enrichment, vended AWS metrics become queryable through PromQL with additional labels. The metric name is the same as the original CloudWatch metric name, and the original CloudWatch dimensions are available as datapoint attributes. The following labels are available (the example below is for an EC2 instance):
| PromQL Label | Description | Example |
| --- | --- | --- |
| `InstanceId` | Original CloudWatch dimension, as a datapoint attribute | `i-0123456789abcdef0` |
| `"@resource.cloud.resource_id"` | Full ARN of the resource | `arn:aws:ec2:us-east-1:123456789012:instance/i-0123456789abcdef0` |
| `"@resource.cloud.provider"` | Cloud provider | `aws` |
| `"@resource.cloud.region"` | AWS Region where this metric originated | `us-east-1` |
| `"@resource.cloud.account.id"` | AWS account ID where this metric originated | `123456789012` |
| `"@instrumentation.@name"` | Instrumentation scope name identifying the source service | `cloudwatch.aws/ec2` |
| `"@instrumentation.cloudwatch.source"` | Source service identifier | `aws.ec2` |
| `"@instrumentation.cloudwatch.solution"` | Enrichment solution identifier | `CloudWatchOTelEnrichment` |
| `"@aws.tag.Environment"` | AWS resource tag | `production` |
| `"@aws.account"` | AWS account where this metric was ingested (system label) | `123456789012` |
| `"@aws.region"` | AWS Region where this metric was ingested (system label) | `us-east-1` |
The following example selects `Invocations` for a specific Lambda function:
```
{Invocations, FunctionName="my-api-handler"}
```
The following example selects Lambda `Errors` for all functions tagged with a specific team:
```
{Errors, "@instrumentation.@name"="cloudwatch.aws/lambda", "@aws.tag.Team"="backend"}
```
The following example computes the total Lambda `Invocations` grouped by team:
```
sum by ("@aws.tag.Team")(
{Invocations, "@instrumentation.@name"="cloudwatch.aws/lambda"}
)
```
The following example selects all time series for the EC2 `CPUUtilization` metric. The usage of `"@instrumentation.@name"="cloudwatch.aws/ec2"` is to exclusively match CPUUtilization from EC2 and not from other AWS services such as Amazon Relational Database Service:
```
histogram_avg({CPUUtilization, "@instrumentation.@name"="cloudwatch.aws/ec2"})
```
## Querying with MCP tools
The [CloudWatch MCP Server](https://awslabs.github.io/mcp/servers/cloudwatch-mcp-server/) provides Model Context Protocol (MCP) tools that let AI assistants and development tools query CloudWatch PromQL data on your behalf. The MCP tools handle authentication and request formatting automatically, so you can focus on writing PromQL queries rather than managing HTTP requests and SigV4 signing.
The following PromQL tools are available in the CloudWatch MCP Server:
| Tool | Description |
| --- | --- |
| `execute_promql_query` | Runs an instant PromQL query, returning metric values at a single point in time. |
| `execute_promql_range_query` | Runs a PromQL range query over a time window, returning time series data for trend analysis and graphing. |
| `get_promql_label_values` | Retrieves values for a specific PromQL label, such as `__name__` for metric names or `@resource.service.name` for services. |
| `get_promql_series` | Finds time series matching PromQL label selectors and returns the full label set of each matching series. |
| `get_promql_labels` | Lists all available PromQL label names to help discover the label structure of your metrics. |
For full details on parameters, configuration, and setup instructions, see [Tools for CloudWatch PromQL](https://awslabs.github.io/mcp/servers/cloudwatch-mcp-server#tools-for-cloudwatch-promql) in the CloudWatch MCP Server documentation.
## Querying with the HTTP API
You can also query CloudWatch PromQL data programmatically by calling the Prometheus-compatible HTTP endpoints directly. Requests must be signed with [AWS Signature Version 4](https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_sigv.html) using `monitoring` as the service name.
The PromQL endpoint follows the pattern `https://monitoring.{{AWS Region}}.amazonaws.com/api/v1/{{operation}}`. For example, for the US East (N. Virginia) (us-east-1) Region, the endpoint for an instant query is `https://monitoring.us-east-1.amazonaws.com/api/v1/query`.
For the full API reference, including supported operations, request parameters, and response formats, see [Prometheus-compatible APIs](CloudWatch-PromQL-APIs.md). For the list of AWS Regions where PromQL querying is available, see [Supported AWS Regions](CloudWatch-PromQL.md#CloudWatch-PromQL-Regions). For the IAM actions required for each operation, see [IAM permissions for PromQL](CloudWatch-PromQL.md#CloudWatch-PromQL-IAM).