revert: one-line admonition for consistency

Author: heitorlessa

docs/core/logger.md

@@ -129,7 +129,8 @@ Key | Example
 
 When debugging in non-production environments, you can instruct Logger to log the incoming event with `log_event` param or via `POWERTOOLS_LOGGER_LOG_EVENT` env var.
 
-!!! warning "Warning: This is disabled by default to prevent sensitive info being logged"
+???+ warning
+	This is disabled by default to prevent sensitive info being logged
 
 === "log_handler_event.py"
 
@@ -147,7 +148,8 @@ When debugging in non-production environments, you can instruct Logger to log th
 
 You can set a Correlation ID using `correlation_id_path` param by passing a [JMESPath expression](https://jmespath.org/tutorial.html){target="_blank"}.
 
-!!! tip "Tip: You can retrieve correlation IDs via `get_correlation_id` method"
+???+ tip
+	You can retrieve correlation IDs via `get_correlation_id` method
 
 === "collect.py"
 
@@ -595,7 +597,8 @@ You can use values ranging from `0.0` to `1` (100%) when setting `POWERTOOLS_LOG
 
 Sampling decision happens at the Logger initialization. This means sampling may happen significantly more or less than depending on your traffic patterns, for example a steady low number of invocations and thus few cold starts.
 
-!!! note "Note: Open a [feature request](https://github.com/awslabs/aws-lambda-powertools-python/issues/new?assignees=&labels=feature-request%2C+triage&template=feature_request.md&title=) if you want Logger to calculate sampling for every invocation"
+???+ note
+	Open a [feature request](https://github.com/awslabs/aws-lambda-powertools-python/issues/new?assignees=&labels=feature-request%2C+triage&template=feature_request.md&title=) if you want Logger to calculate sampling for every invocation
 
 === "collect.py"
 
@@ -883,7 +886,8 @@ For **minor changes like remapping keys** after all log record processing has co
 
 For **replacing the formatter entirely**, you can subclass `BasePowertoolsFormatter`, implement `append_keys` method, and override `format` standard logging method. This ensures the current feature set of Logger like [injecting Lambda context](#capturing-lambda-context-info) and [sampling](#sampling-debug-logs) will continue to work.
 
-!!! info "Info: You might need to implement `remove_keys` method if you make use of the feature too."
+???+ info
+	You might need to implement `remove_keys` method if you make use of the feature too.
 
 === "collect.py"
 
@@ -1016,7 +1020,8 @@ This is a Pytest sample that provides the minimum information necessary for Logg
         your_lambda_handler(test_event, lambda_context)
     ```
 
-!!! tip "Tip: Check out the built-in [Pytest caplog fixture](https://docs.pytest.org/en/latest/how-to/logging.html){target="_blank"} to assert plain log messages"
+???+ tip
+	Check out the built-in [Pytest caplog fixture](https://docs.pytest.org/en/latest/how-to/logging.html){target="_blank"} to assert plain log messages
 
 ### Pytest live log feature
 

docs/core/metrics.md

@@ -70,7 +70,7 @@ Setting | Description | Environment variable | Constructor parameter
 
 You can create metrics using `add_metric`, and you can create dimensions for all your aggregate metrics using `add_dimension` method.
 
-!!! tip
+???+ tip
 	You can initialize Metrics in any other module too. It'll keep track of your aggregate metrics in memory to optimize costs (one blob instead of multiples).
 
 === "Metrics"
@@ -336,7 +336,8 @@ CloudWatch EMF uses the same dimensions across all your metrics. Use `single_met
 
 If you prefer not to use `log_metrics` because you might want to encapsulate additional logic when doing so, you can manually flush and clear metrics as follows:
 
-!!! warning "Warning: Metrics, dimensions and namespace validation still applies"
+???+ warning
+	Metrics, dimensions and namespace validation still applies
 
 === "manual_metric_serialization.py"
 
@@ -358,7 +359,7 @@ If you prefer not to use `log_metrics` because you might want to encapsulate add
 
 ### Environment variables
 
-!!! tip
+???+ tip
 	Ignore this section, if you are explicitly setting namespace/default dimension via `namespace` and `service` parameters.
 
 	For example, `Metrics(namespace=ApplicationName, service=ServiceName)`

docs/core/tracer.md

@@ -113,7 +113,8 @@ You can trace synchronous functions using the `capture_method` decorator.
 
 ### Asynchronous and generator functions
 
-!!! warning "Warning: We do not support asynchronous Lambda handler"
+???+ warning
+	We do not support asynchronous Lambda handler
 
 You can trace asynchronous functions and generator functions (including context managers) using `capture_method`.
 
@@ -235,7 +236,8 @@ Use **`capture_response=False`** parameter in both `capture_lambda_handler` and
 
 Use **`capture_error=False`** parameter in both `capture_lambda_handler` and `capture_method` decorators to instruct Tracer **not** to serialize exceptions as metadata.
 
-!!! info "Info: Useful when returning sensitive information in exceptions/stack traces you don't control"
+???+ info
+	Useful when returning sensitive information in exceptions/stack traces you don't control
 
 === "sensitive_data_exception.py"
 
@@ -249,7 +251,8 @@ Use **`capture_error=False`** parameter in both `capture_lambda_handler` and `ca
 
 ### Tracing aiohttp requests
 
-!!! info "Info: This snippet assumes you have aiohttp as a dependency"
+???+ info
+	This snippet assumes you have aiohttp as a dependency
 
 You can use `aiohttp_trace_config` function to create a valid [aiohttp trace_config object](https://docs.aiohttp.org/en/stable/tracing_reference.html). This is necessary since X-Ray utilizes aiohttp trace hooks to capture requests end-to-end.
 
@@ -293,7 +296,8 @@ This is useful when you need a feature available in X-Ray that is not available
 
 ### Concurrent asynchronous functions
 
-!!! warning "Warning: [X-Ray SDK will raise an exception](https://github.com/aws/aws-xray-sdk-python/issues/164) when async functions are run and traced concurrently"
+???+ warning
+	[X-Ray SDK will raise an exception](https://github.com/aws/aws-xray-sdk-python/issues/164) when async functions are run and traced concurrently
 
 A safe workaround mechanism is to use `in_subsegment_async` available via Tracer escape hatch (`tracer.provider`).
 

docs/index.md

@@ -201,7 +201,9 @@ Despite having more steps compared to the [public Layer ARN](#lambda-layer) opti
 ???+ warning
     **Layer-extras** does not support Python 3.6 runtime. This layer also includes all extra dependencies: `22.4MB zipped`, `~155MB unzipped`.
 
-!!! tip "Tip: You can create a shared Lambda Layers stack and make this along with other account level layers stack."
+???+ tip
+	You can create a shared Lambda Layers stack and make this along with other account level layers stack.
+
 
 If using SAM, you can include this SAR App as part of your shared Layers stack, and lock to a specific semantic version. Once deployed, it'll be available across the account this is deployed to.
 
@@ -434,7 +436,8 @@ You can fetch available versions via SAR API with:
 
 ## Environment variables
 
-???+ info "Info: Explicit parameters take precedence over environment variables"
+???+ info
+	Explicit parameters take precedence over environment variables
 
 | Environment variable | Description | Utility | Default |
 | ------------------------------------------------- | --------------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | ------------------------------------------------- |