docs(navigation): add nofollow attribute

docs/core/event_handler/appsync.md

@@ -9,15 +9,15 @@ Event handler for AWS AppSync Direct Lambda Resolver and Amplify GraphQL Transfo
 
 * Automatically parse API arguments to function arguments
 * Choose between strictly match a GraphQL field name or all of them to a function
-* Integrates with [Data classes utilities](../../utilities/data_classes.md){target="_blank"} to access resolver and identity information
+* Integrates with [Data classes utilities](../../utilities/data_classes.md){target="_blank" rel="nofollow"} to access resolver and identity information
 * Works with both Direct Lambda Resolver and Amplify GraphQL Transformer `@function` directive
 * Support async Python 3.8+ functions, and generators
 
 ## Terminology
 
-**[Direct Lambda Resolver](https://docs.aws.amazon.com/appsync/latest/devguide/direct-lambda-reference.html){target="_blank"}**. A custom AppSync Resolver to bypass the use of Apache Velocity Template (VTL) and automatically map your function's response to a GraphQL field.
+**[Direct Lambda Resolver](https://docs.aws.amazon.com/appsync/latest/devguide/direct-lambda-reference.html){target="_blank" rel="nofollow"}**. A custom AppSync Resolver to bypass the use of Apache Velocity Template (VTL) and automatically map your function's response to a GraphQL field.
 
-**[Amplify GraphQL Transformer](https://docs.amplify.aws/cli/graphql-transformer/function){target="_blank"}**. Custom GraphQL directives to define your application's data model using Schema Definition Language (SDL). Amplify CLI uses these directives to convert GraphQL SDL into full descriptive AWS CloudFormation templates.
+**[Amplify GraphQL Transformer](https://docs.amplify.aws/cli/graphql-transformer/function){target="_blank" rel="nofollow"}**. Custom GraphQL directives to define your application's data model using Schema Definition Language (SDL). Amplify CLI uses these directives to convert GraphQL SDL into full descriptive AWS CloudFormation templates.
 
 ## Getting started
 
@@ -28,7 +28,7 @@ You must have an existing AppSync GraphQL API and IAM permissions to invoke your
 This is the sample infrastructure we are using for the initial examples with a AppSync Direct Lambda Resolver.
 
 ???+ tip "Tip: Designing GraphQL Schemas for the first time?"
-    Visit [AWS AppSync schema documentation](https://docs.aws.amazon.com/appsync/latest/devguide/designing-your-schema.html){target="_blank"} for understanding how to define types, nesting, and pagination.
+    Visit [AWS AppSync schema documentation](https://docs.aws.amazon.com/appsync/latest/devguide/designing-your-schema.html){target="_blank" rel="nofollow"} for understanding how to define types, nesting, and pagination.
 
 === "getting_started_schema.graphql"
 
@@ -93,7 +93,7 @@ Here's an example with two separate functions to resolve `getTodo` and `listTodo
 
 ### Scalar functions
 
-When working with [AWS AppSync Scalar types](https://docs.aws.amazon.com/appsync/latest/devguide/scalars.html){target="_blank"}, you might want to generate the same values for data validation purposes.
+When working with [AWS AppSync Scalar types](https://docs.aws.amazon.com/appsync/latest/devguide/scalars.html){target="_blank" rel="nofollow"}, you might want to generate the same values for data validation purposes.
 
 For convenience, the most commonly used values are available as functions within `scalar_types_utils` module.
 
@@ -143,15 +143,15 @@ For Lambda Python3.8+ runtime, this utility supports async functions when you us
 
 ### Amplify GraphQL Transformer
 
-Assuming you have [Amplify CLI installed](https://docs.amplify.aws/cli/start/install){target="_blank"}, create a new API using `amplify add api` and use the following GraphQL Schema.
+Assuming you have [Amplify CLI installed](https://docs.amplify.aws/cli/start/install){target="_blank" rel="nofollow"}, create a new API using `amplify add api` and use the following GraphQL Schema.
 
 <!-- AppSync resolver decorator is a concise way to create lambda functions to handle AppSync resolvers for multiple `typeName` and `fieldName` declarations. -->
 
 ```typescript hl_lines="7 15 20 22" title="Example GraphQL Schema"
 --8<-- "examples/event_handler_graphql/src/amplify_graphql_transformer_schema.graphql"
 ```
 
-[Create two new basic Python functions](https://docs.amplify.aws/cli/function#set-up-a-function){target="_blank"} via `amplify add function`.
+[Create two new basic Python functions](https://docs.amplify.aws/cli/function#set-up-a-function){target="_blank" rel="nofollow"} via `amplify add function`.
 
 ???+ note
     Amplify CLI generated functions use `Pipenv` as a dependency manager. Your function source code is located at **`amplify/backend/function/your-function-name`**.
@@ -192,7 +192,7 @@ Use the following code for `merchantInfo` and `searchMerchant` functions respect
 
 ### Custom data models
 
-You can subclass [AppSyncResolverEvent](../../utilities/data_classes.md#appsync-resolver){target="_blank"} to bring your own set of methods to handle incoming events, by using `data_model` param in the `resolve` method.
+You can subclass [AppSyncResolverEvent](../../utilities/data_classes.md#appsync-resolver){target="_blank" rel="nofollow"} to bring your own set of methods to handle incoming events, by using `data_model` param in the `resolve` method.
 
 === "custom_models.py.py"
 
@@ -215,7 +215,7 @@ You can subclass [AppSyncResolverEvent](../../utilities/data_classes.md#appsync-
 ### Split operations with Router
 
 ???+ tip
-    Read the **[considerations section for trade-offs between monolithic and micro functions](./api_gateway.md#considerations){target="_blank"}**, as it's also applicable here.
+    Read the **[considerations section for trade-offs between monolithic and micro functions](./api_gateway.md#considerations){target="_blank" rel="nofollow"}**, as it's also applicable here.
 
 As you grow the number of related GraphQL operations a given Lambda function should handle, it is natural to split them into separate files to ease maintenance - That's when the `Router` feature comes handy.
 

docs/core/logger.md

@@ -15,7 +15,7 @@ Logger provides an opinionated logger with output structured as JSON.
 ## Getting started
 
 ???+ tip
-    All examples shared in this documentation are available within the [project repository](https://github.com/aws-powertools/powertools-lambda-python/tree/develop/examples){target="_blank"}.
+    All examples shared in this documentation are available within the [project repository](https://github.com/aws-powertools/powertools-lambda-python/tree/develop/examples){target="_blank" rel="nofollow"}.
 
 Logger requires two settings:
 
@@ -39,7 +39,7 @@ Your Logger will include the following keys to your structured logging:
 | **message**: `Any`         | `Collecting payment`                  | Unserializable JSON values are casted as `str`                                                                                       |
 | **timestamp**: `str`       | `2021-05-03 10:20:19,650+0200`        | Timestamp with milliseconds, by default uses local timezone                                                                          |
 | **service**: `str`         | `payment`                             | Service name defined, by default `service_undefined`                                                                                 |
-| **xray_trace_id**: `str`   | `1-5759e988-bd862e3fe1be46a994272793` | When [tracing is enabled](https://docs.aws.amazon.com/lambda/latest/dg/services-xray.html){target="_blank"}, it shows X-Ray Trace ID |
+| **xray_trace_id**: `str`   | `1-5759e988-bd862e3fe1be46a994272793` | When [tracing is enabled](https://docs.aws.amazon.com/lambda/latest/dg/services-xray.html){target="_blank" rel="nofollow"}, it shows X-Ray Trace ID |
 | **sampling_rate**: `float` | `0.1`                                 | When enabled, it shows sampling rate in percentage e.g. 10%                                                                          |
 | **exception_name**: `str`  | `ValueError`                          | When `logger.exception` is used and there is an exception                                                                            |
 | **exception**: `str`       | `Traceback (most recent call last)..` | When `logger.exception` is used and there is an exception                                                                            |
@@ -83,7 +83,7 @@ When debugging in non-production environments, you can instruct Logger to log th
 
 ### Setting a Correlation ID
 
-You can set a Correlation ID using `correlation_id_path` param by passing a [JMESPath expression](https://jmespath.org/tutorial.html){target="_blank"}.
+You can set a Correlation ID using `correlation_id_path` param by passing a [JMESPath expression](https://jmespath.org/tutorial.html){target="_blank" rel="nofollow"}.
 
 ???+ tip
 	You can retrieve correlation IDs via `get_correlation_id` method
@@ -108,7 +108,7 @@ You can set a Correlation ID using `correlation_id_path` param by passing a [JME
 
 #### set_correlation_id method
 
-You can also use `set_correlation_id` method to inject it anywhere else in your code. Example below uses [Event Source Data Classes utility](../utilities/data_classes.md){target="_blank"} to easily access events properties.
+You can also use `set_correlation_id` method to inject it anywhere else in your code. Example below uses [Event Source Data Classes utility](../utilities/data_classes.md){target="_blank" rel="nofollow"} to easily access events properties.
 
 === "set_correlation_id_method.py"
 
@@ -163,7 +163,7 @@ You can append additional keys using either mechanism:
 #### append_keys method
 
 ???+ warning
-	`append_keys` is not thread-safe, please see [RFC](https://github.com/aws-powertools/powertools-lambda-python/issues/991){target="_blank"}.
+	`append_keys` is not thread-safe, please see [RFC](https://github.com/aws-powertools/powertools-lambda-python/issues/991){target="_blank" rel="nofollow"}.
 
 You can append your own keys to your existing Logger via `append_keys(**additional_key_values)` method.
 
@@ -242,7 +242,7 @@ You can remove any additional key from Logger state using `remove_keys`.
 
 #### Clearing all state
 
-Logger is commonly initialized in the global scope. Due to [Lambda Execution Context reuse](https://docs.aws.amazon.com/lambda/latest/dg/runtimes-context.html){target="_blank"}, this means that custom keys can be persisted across invocations. If you want all custom keys to be deleted, you can use `clear_state=True` param in `inject_lambda_context` decorator.
+Logger is commonly initialized in the global scope. Due to [Lambda Execution Context reuse](https://docs.aws.amazon.com/lambda/latest/dg/runtimes-context.html){target="_blank" rel="nofollow"}, this means that custom keys can be persisted across invocations. If you want all custom keys to be deleted, you can use `clear_state=True` param in `inject_lambda_context` decorator.
 
 ???+ tip "Tip: When is this useful?"
     It is useful when you add multiple custom keys conditionally, instead of setting a default `None` value if not present. Any key with `None` value is automatically removed by Logger.
@@ -301,7 +301,7 @@ Logger can optionally log uncaught exceptions by setting `log_uncaught_exception
 
 ??? question "What are uncaught exceptions?"
 
-    It's any raised exception that wasn't handled by the [`except` statement](https://docs.python.org/3.9/tutorial/errors.html#handling-exceptions){target="_blank"}, leading a Python program to a non-successful exit.
+    It's any raised exception that wasn't handled by the [`except` statement](https://docs.python.org/3.9/tutorial/errors.html#handling-exceptions){target="_blank" rel="nofollow"}, leading a Python program to a non-successful exit.
 
     They are typically raised intentionally to signal a problem (`raise ValueError`), or a propagated exception from elsewhere in your code that you didn't handle it willingly or not (`KeyError`, `jsonDecoderError`, etc.).
 
@@ -323,10 +323,10 @@ Logger uses Python's standard logging date format with the addition of timezone:
 
 You can easily change the date format using one of the following parameters:
 
-* **`datefmt`**. You can pass any [strftime format codes](https://strftime.org/){target="_blank"}. Use `%F` if you need milliseconds.
+* **`datefmt`**. You can pass any [strftime format codes](https://strftime.org/){target="_blank" rel="nofollow"}. Use `%F` if you need milliseconds.
 * **`use_rfc3339`**. This flag will use a format compliant with both RFC3339 and ISO8601: `2022-10-27T16:27:43.738+02:00`
 
-???+ tip "Prefer using [datetime string formats](https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-codes){target="_blank"}?"
+???+ tip "Prefer using [datetime string formats](https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-codes){target="_blank" rel="nofollow"}?"
 	Use `use_datetime_directive` flag along with `datefmt` to instruct Logger to use `datetime` instead of `time.strftime`.
 
 === "date_formatting.py"
@@ -360,7 +360,7 @@ You can use any of the following built-in JMESPath expressions as part of [injec
 
 ### Reusing Logger across your code
 
-Similar to [Tracer](./tracer.md#reusing-tracer-across-your-code){target="_blank"}, a new instance that uses the same `service` name - env var or explicit parameter - will reuse a previous Logger instance. Just like `logging.getLogger("logger_name")` would in the standard library if called with the same logger name.
+Similar to [Tracer](./tracer.md#reusing-tracer-across-your-code){target="_blank" rel="nofollow"}, a new instance that uses the same `service` name - env var or explicit parameter - will reuse a previous Logger instance. Just like `logging.getLogger("logger_name")` would in the standard library if called with the same logger name.
 
 Notice in the CloudWatch Logs output how `payment_id` appeared as expected when logging in `collect.py`.
 
@@ -407,7 +407,7 @@ 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
-	Open a [feature request](https://github.com/aws-powertools/powertools-lambda-python/issues/new?assignees=&labels=feature-request%2C+triage&template=feature_request.md&title=){target="_blank"} if you want Logger to calculate sampling for every invocation
+	Open a [feature request](https://github.com/aws-powertools/powertools-lambda-python/issues/new?assignees=&labels=feature-request%2C+triage&template=feature_request.md&title=){target="_blank" rel="nofollow"} if you want Logger to calculate sampling for every invocation
 
 === "sampling_debug_logs.py"
 
@@ -447,9 +447,9 @@ If you prefer configuring it separately, or you'd want to bring this JSON Format
 
 ### Observability providers
 
-!!! note "In this context, an observability provider is an [AWS Lambda Partner](https://go.aws/3HtU6CZ){target="_blank"} offering a platform for logging, metrics, traces, etc."
+!!! note "In this context, an observability provider is an [AWS Lambda Partner](https://go.aws/3HtU6CZ){target="_blank" rel="nofollow"} offering a platform for logging, metrics, traces, etc."
 
-You can send logs to the observability provider of your choice via [Lambda Extensions](https://aws.amazon.com/blogs/compute/using-aws-lambda-extensions-to-send-logs-to-custom-destinations/){target="_blank"}. In most cases, you shouldn't need any custom Logger configuration, and logs will be shipped async without any performance impact.
+You can send logs to the observability provider of your choice via [Lambda Extensions](https://aws.amazon.com/blogs/compute/using-aws-lambda-extensions-to-send-logs-to-custom-destinations/){target="_blank" rel="nofollow"}. In most cases, you shouldn't need any custom Logger configuration, and logs will be shipped async without any performance impact.
 
 #### Built-in formatters
 
@@ -634,7 +634,7 @@ For exceptional cases where you want to completely replace our formatter logic,
 
 #### Bring your own JSON serializer
 
-By default, Logger uses `json.dumps` and `json.loads` as serializer and deserializer respectively. There could be scenarios where you are making use of alternative JSON libraries like [orjson](https://github.com/ijl/orjson){target="_blank"}.
+By default, Logger uses `json.dumps` and `json.loads` as serializer and deserializer respectively. There could be scenarios where you are making use of alternative JSON libraries like [orjson](https://github.com/ijl/orjson){target="_blank" rel="nofollow"}.
 
 As parameters don't always translate well between them, you can pass any callable that receives a `dict` and return a `str`:
 
@@ -664,7 +664,7 @@ This is a Pytest sample that provides the minimum information necessary for Logg
     ```
 
 ???+ 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
+	Check out the built-in [Pytest caplog fixture](https://docs.pytest.org/en/latest/how-to/logging.html){target="_blank" rel="nofollow"} to assert plain log messages
 
 ### Pytest live log feature
 
@@ -703,7 +703,7 @@ By default all registered loggers will be modified. You can change this behavior
 
 ### How can I add standard library logging attributes to a log record?
 
-The Python standard library log records contains a [large set of attributes](https://docs.python.org/3/library/logging.html#logrecord-attributes){target="_blank"}, however only a few are included in Powertools for AWS Lambda (Python) Logger log record by default.
+The Python standard library log records contains a [large set of attributes](https://docs.python.org/3/library/logging.html#logrecord-attributes){target="_blank" rel="nofollow"}, however only a few are included in Powertools for AWS Lambda (Python) Logger log record by default.
 
 You can include any of these logging attributes as key value arguments (`kwargs`) when instantiating `Logger` or `LambdaPowertoolsFormatter`.
 
@@ -744,4 +744,4 @@ Here's an example where we persist `payment_id` not `request_id`. Note that `pay
 <!-- markdownlint-disable MD013 -->
 ### How do I aggregate and search Powertools for AWS Lambda (Python) logs across accounts?
 
-As of now, ElasticSearch (ELK) or 3rd party solutions are best suited to this task. Please refer to this [discussion for more details](https://github.com/aws-powertools/powertools-lambda-python/issues/460){target="_blank"}
+As of now, ElasticSearch (ELK) or 3rd party solutions are best suited to this task. Please refer to this [discussion for more details](https://github.com/aws-powertools/powertools-lambda-python/issues/460){target="_blank" rel="nofollow"}