diff --git a/aws_lambda_powertools/metrics/base.py b/aws_lambda_powertools/metrics/base.py
index 48a6f019e40..fde191a8d94 100644
--- a/aws_lambda_powertools/metrics/base.py
+++ b/aws_lambda_powertools/metrics/base.py
@@ -178,7 +178,8 @@ def serialize_metric_set(
             metadata = self.metadata_set
 
         if self.service and not self.dimension_set.get("service"):
-            self.dimension_set["service"] = self.service
+            # self.service won't be a float
+            self.add_dimension(name="service", value=self.service)  # type: ignore[arg-type]
 
         if len(metrics) == 0:
             raise SchemaValidationError("Must contain at least one metric.")
diff --git a/docs/core/metrics.md b/docs/core/metrics.md
index 99ee17106b3..713ae874fe6 100644
--- a/docs/core/metrics.md
+++ b/docs/core/metrics.md
@@ -30,10 +30,10 @@ If you're new to Amazon CloudWatch, there are two terminologies you must be awar
 
 Metric has two global settings that will be used across all metrics emitted:
 
-Setting | Description | Environment variable | Constructor parameter
-------------------------------------------------- | ------------------------------------------------- | ------------------------------------------------- | -------------------------------------------------
-**Metric namespace** | Logical container where all metrics will be placed e.g. `ServerlessAirline` |  `POWERTOOLS_METRICS_NAMESPACE` | `namespace`
-**Service** | Optionally, sets **service** metric dimension across all metrics e.g. `payment` | `POWERTOOLS_SERVICE_NAME` | `service`
+| Setting              | Description                                                                     | Environment variable           | Constructor parameter |
+| -------------------- | ------------------------------------------------------------------------------- | ------------------------------ | --------------------- |
+| **Metric namespace** | Logical container where all metrics will be placed e.g. `ServerlessAirline`     | `POWERTOOLS_METRICS_NAMESPACE` | `namespace`           |
+| **Service**          | Optionally, sets **service** metric dimension across all metrics e.g. `payment` | `POWERTOOLS_SERVICE_NAME`      | `service`             |
 
 ???+ tip
     Use your application or main service as the metric namespace to easily group all metrics.
@@ -191,7 +191,7 @@ This decorator also **validates**, **serializes**, and **flushes** all your metr
 ???+ tip "Tip: Metric validation"
     If metrics are provided, and any of the following criteria are not met, **`SchemaValidationError`** exception will be raised:
 
-    * Maximum of 9 dimensions
+    * Maximum of 8 user-defined dimensions
     * Namespace is set, and no more than one
     * Metric units must be [supported by CloudWatch](https://docs.aws.amazon.com/AmazonCloudWatch/latest/APIReference/API_MetricDatum.html)
 
diff --git a/tests/functional/test_metrics.py b/tests/functional/test_metrics.py
index 4a5df151dd1..4dbefd34603 100644
--- a/tests/functional/test_metrics.py
+++ b/tests/functional/test_metrics.py
@@ -319,9 +319,11 @@ def test_schema_no_metrics(service, namespace):
         my_metrics.serialize_metric_set()
 
 
-def test_exceed_number_of_dimensions(metric, namespace):
+def test_exceed_number_of_dimensions(metric, namespace, monkeypatch):
     # GIVEN we we have more dimensions than CloudWatch supports
-    dimensions = [{"name": f"test_{i}", "value": "test"} for i in range(11)]
+    # and that service dimension is injected like a user-defined dimension (N+1)
+    monkeypatch.setenv("POWERTOOLS_SERVICE_NAME", "test_service")
+    dimensions = [{"name": f"test_{i}", "value": "test"} for i in range(9)]
 
     # WHEN we attempt to serialize them into a valid EMF object
     # THEN it should fail validation and raise SchemaValidationError