diff --git a/README.md b/README.md
index 134578b..645679f 100644
--- a/README.md
+++ b/README.md
@@ -412,7 +412,7 @@ The orchestrator includes an advanced notification filtering system that prevent
 #### **Utilities (`orchestrator/utils/`)**
 - **Connectors Configuration**: Database and service configuration management
 - **Email Builder**: HTML email template generation and formatting using Jinja2 templates
-- **Orchestrator Functions**: Pipeline configuration transformation utilities for scouter, predictions_batch, and minimal_retrain workflows
+- **Orchestrator Functions**: Pipeline configuration transformation utilities for scouter, predictions_batch, minimal_retrain, drift, and simple_metrics workflows
 - **Converters**: Data type conversion and validation utilities including frequency parsing
 - **Templates**: HTML email templates for alerts and reports
 
diff --git a/orchestrator/activities/email.py b/orchestrator/activities/email.py
index bbad1a0..ab30c78 100644
--- a/orchestrator/activities/email.py
+++ b/orchestrator/activities/email.py
@@ -71,6 +71,8 @@ class Email(SientiaMonitoring):
     def close(self):
         """
         Close the Email connection and clean up resources.
+
+        Closes the SMTP server connection and shuts down the SientiaMonitoring instance.
         """
         self.server.quit()
         SientiaMonitoring.shutdown(self)
@@ -120,15 +122,23 @@ class Email(SientiaMonitoring):
 
     def handle_attachments(self, attachments: list[dict], msg: MIMEMultipart) -> MIMEMultipart:
         """
-        Attaches a list of attachments to an email message.
+        Attach a list of attachments to an email message.
+
+        Processes notification attachments and adds them to the email message
+        as base64-encoded MIME parts. Each attachment contains error details
+        or additional context for the notification.
+
         Args:
-            attachments (List[Dict]): A list of dictionaries where each dictionary contains
-                the keys 'filename' and 'content' representing the attachment details.
-            msg (MIMEMultipart): The email message object to which the attachments will be added.
+            attachments (list[dict]): A list of dictionaries where each dictionary contains:
+                - filename (str): Name of the attachment file
+                - attachment_content (str): Content of the attachment
+            msg (MIMEMultipart): The email message object to which the attachments will be added
+
         Returns:
-            MIMEMultipart: The email message object with the attachments added.
+            MIMEMultipart: The email message object with the attachments added
+
         Raises:
-            Exception: If an attachment cannot be added, an error is logged.
+            Exception: If an attachment cannot be added, an error is logged and raised
         """
 
         for attachment in attachments:
@@ -149,14 +159,17 @@ class Email(SientiaMonitoring):
 
     def try_send_email(self, msg: MIMEMultipart, receivers: str):
         """
-        Sends an email to the receivers with automatic reconnection handling.
+        Send an email to the receivers with automatic reconnection handling.
+
+        Attempts to send an email and automatically reconnects to the SMTP server
+        if a disconnection occurs during transmission.
 
         Args:
-            msg (MIMEMultipart): The email message to send.
-            receivers (str): Comma-separated list of email addresses to send to.
+            msg (MIMEMultipart): The email message to send
+            receivers (str): Comma-separated list of email addresses to send to
 
         Raises:
-            Exception: If email sending fails after reconnection attempts.
+            Exception: If email sending fails after reconnection attempts
         """
         try:
             self.server.sendmail(self.sender_email, receivers, msg.as_string())
diff --git a/orchestrator/activities/formatters.py b/orchestrator/activities/formatters.py
index cb45d57..9b7ce92 100644
--- a/orchestrator/activities/formatters.py
+++ b/orchestrator/activities/formatters.py
@@ -15,10 +15,12 @@ with workflow.unsafe.imports_passed_through():
 
     from orchestrator.utils.orchestrator_functions import (
         build_tag_config,
+        drift,
         gather_read_tags,
         minimal_retrain,
         predictions_batch,
         scouter,
+        simple_metrics,
     )
 
 topic_separator = '\n ========== \n'
@@ -34,7 +36,7 @@ class Formatters(SientiaMonitoring):
     scheduled reports.
 
     Key features:
-    - Pipeline schedule configuration formatting ("scouter", "predictions_batch", "minimal_retrain")
+    - Pipeline schedule configuration formatting ("scouter", "predictions_batch", "minimal_retrain", "drift")
     - OPC slot distribution across active ingestors
     - Notification filtering for comprehensive scheduled reports
     - Group-based report filtering with ignore list support
@@ -67,6 +69,8 @@ class Formatters(SientiaMonitoring):
     def close(self):
         """
         Close the Formatters connection and clean up resources.
+
+        Shuts down the SientiaMonitoring instance and releases all resources.
         """
         SientiaMonitoring.shutdown(self)
 
@@ -132,6 +136,20 @@ class Formatters(SientiaMonitoring):
                         'updated_at', now().strftime(DATETIME_FORMAT_MS_WITH_TZ)
                     ),
                 }
+            elif pipeline['workflow_type'] == 'drift':
+                schedule_config[self.laborious_namespace][pipeline['schedule_name']] = {
+                    **drift(pipeline),
+                    'updated_at': pipeline.get(
+                        'updated_at', now().strftime(DATETIME_FORMAT_MS_WITH_TZ)
+                    ),
+                }
+            elif pipeline['workflow_type'] == 'simple_metrics':
+                schedule_config[self.laborious_namespace][pipeline['schedule_name']] = {
+                    **simple_metrics(pipeline),
+                    'updated_at': pipeline.get(
+                        'updated_at', now().strftime(DATETIME_FORMAT_MS_WITH_TZ)
+                    ),
+                }
 
         self.info('Processed schedules', metadata=metadata)
         self.debug(json.dumps(schedule_config, indent=4, sort_keys=True), metadata=metadata)
@@ -213,14 +231,18 @@ class Formatters(SientiaMonitoring):
     @activity.defn(name='format_schedule_config')
     async def format_schedule_config(self, input_data: dict[str, Any]) -> dict[str, Any]:
         """
-        Formats the schedule config to a dictionary with the schedule name as the key.
+        Format the schedule config to a dictionary with the schedule name as the key.
+
+        Transforms a list of schedule configurations into a nested dictionary structure
+        organized by namespace and schedule name for efficient lookup and comparison.
 
         Args:
-            input_data (dict[str, Any]): The input data containing the schedule config to format.
-                - schedule_config (list[dict[str, Any]]): The schedule config to format.
+            input_data (dict[str, Any]): The input data containing:
+                - schedule_config (list[dict[str, Any]]): The schedule config to format
+                - metadata (dict): Metadata for logging purposes
 
         Returns:
-            dict[str, Any]: The formatted schedule config.
+            dict[str, Any]: The formatted schedule config organized by namespace and schedule name
         """
         metadata = input_data['metadata']
 
@@ -256,13 +278,16 @@ class Formatters(SientiaMonitoring):
         """
         Compare new and current schedules to determine which should be updated or created.
 
+        Compares schedule timestamps to identify schedules that need updating (newer timestamp)
+        or creating (schedule doesn't exist). Results are accumulated in the provided dictionaries.
+
         Args:
-            schedules (dict[str, Any]): New schedules to compare.
-            current_schedules (dict[str, Any]): Existing schedules to compare against.
-            to_update (dict[str, Any]): Output accumulator for schedules that need updating.
-            to_create (dict[str, Any]): Output accumulator for schedules that need creating.
-            namespace (str): Namespace for the schedules being compared.
-            metadata (dict[str, Any]): Metadata for logging purposes.
+            schedules (dict[str, Any]): New schedules to compare
+            current_schedules (dict[str, Any]): Existing schedules to compare against
+            to_update (dict[str, Any]): Output accumulator for schedules that need updating
+            to_create (dict[str, Any]): Output accumulator for schedules that need creating
+            namespace (str): Namespace for the schedules being compared
+            metadata (dict[str, Any]): Metadata for logging purposes
         """
         for schedule_name, schedule in schedules.items():
             if schedule_name in current_schedules:
@@ -283,19 +308,23 @@ class Formatters(SientiaMonitoring):
     @activity.defn(name='create_schedule_config')
     async def create_schedule_config(self, input_data: dict[str, Any]) -> dict[str, Any]:
         """
-        Creates a schedule config dictionary based on the input data.
-        Checks the existing schedule config and updates it with the new schedule config,
-        deleting unnecessary schedules, creating new schedules and updating existing schedules.
+        Create a schedule config dictionary based on the input data.
+
+        Compares the current schedule configuration in Temporal with the new schedule
+        configuration to determine which schedules need to be created, updated, or deleted.
+        Uses timestamp comparison to identify schedules that have changed.
 
         Args:
-            - input_data (dict[str, Any]): The input data containing
-              the schedules to process.
-                - current_schedule_config (dict[str, Any]): The current schedule
-                config in Temporal server.
-                - schedule_config (dict[str, Any]): The schedule config to process.
+            input_data (dict[str, Any]): The input data containing:
+                - current_schedule_config (dict[str, Any]): The current schedule config in Temporal server
+                - schedule_config (dict[str, Any]): The schedule config to process
+                - metadata (dict): Metadata for logging purposes
 
         Returns:
-            - dict[str, Any]: A dictionary with keys 'to_update', 'to_create', and 'to_delete'
+            dict[str, Any]: A dictionary with keys:
+                - to_update (dict): Schedules that need updating
+                - to_create (dict): Schedules that need creating
+                - to_delete (dict): Schedules that need deleting
         """
 
         metadata = input_data.get('metadata', {})
@@ -339,19 +368,22 @@ class Formatters(SientiaMonitoring):
     @activity.defn(name='create_slot_config')
     async def create_slot_config(self, input_data: dict[str, Any]) -> dict[str, Any]:
         """
-        Creates a slot config dictionary based on the input data.
-        Checks the existing slot config and updates it with the new slot config,
-        deleting unnecessary slots.
+        Create a slot config dictionary based on the input data.
+
+        Compares the current slot configuration in Redis with the new slot configuration
+        to determine which slots need to be inserted or deleted. Slots are identified
+        by numeric IDs, and excess slots are marked for deletion.
 
         Args:
-            - input_data (dict[str, Any]): The input data containing
-              the slots to process.
-                - current_slot_config (dict[str, Any]): The current slot
-                config in Temporal server.
-                - slot_config (dict[str, Any]): The slot config to process.
+            input_data (dict[str, Any]): The input data containing:
+                - current_slot_config (dict[str, Any]): The current slot config in Redis
+                - slot_config (dict[str, Any]): The slot config to process
+                - metadata (dict): Metadata for logging purposes
 
         Returns:
-            - dict[str, Any]: A dictionary containing 'to_insert' and 'to_delete'
+            dict[str, Any]: A dictionary containing:
+                - to_insert (dict): Slots that need to be inserted/updated
+                - to_delete (list[str]): Slot IDs that need to be deleted
         """
 
         metadata = input_data.get('metadata', {})
@@ -383,13 +415,16 @@ class Formatters(SientiaMonitoring):
         attachment: Any | None = None,
     ) -> None:
         """
-        Sends a success notification report.
+        Send a success notification report.
+
+        Sends an INFO-level notification to the notification handler with success
+        details about orchestration operations.
 
         Args:
-            metadata (dict[str, Any]): Metadata for the notification.
-            message (str): The success message to send.
-            notification_id (str): The ID of the notification to send.
-            attachment (Any | None, optional): Optional attachment content to include.
+            metadata (dict[str, Any]): Metadata for the notification
+            message (str): The success message to send
+            notification_id (str): The ID of the notification to send
+            attachment (Any | None, optional): Optional attachment content to include
         """
         await self.send_notification_async(
             metadata=metadata,
@@ -404,13 +439,16 @@ class Formatters(SientiaMonitoring):
         self, metadata: dict[str, Any], message: str, notification_id: str, attachment: str
     ) -> None:
         """
-        Sends an error notification report.
+        Send an error notification report.
+
+        Sends an ERROR-level notification to the notification handler with error
+        details about orchestration operation failures.
 
         Args:
-            metadata (dict[str, Any]): Metadata for the notification.
-            message (str): The error message to send.
-            notification_id (str): The ID of the notification.
-            attachment (str): The attachment content for the notification.
+            metadata (dict[str, Any]): Metadata for the notification
+            message (str): The error message to send
+            notification_id (str): The ID of the notification
+            attachment (str): The attachment content for the notification
         """
         await self.send_notification_async(
             metadata=metadata,
@@ -425,12 +463,15 @@ class Formatters(SientiaMonitoring):
         self, input_data: list[dict[str, Any]]
     ) -> tuple[list[str], dict[str, Any]]:
         """
-        Parses the report schedule data to extract success and error information.
+        Parse the report schedule data to extract success and error information.
+
+        Processes schedule operation reports and separates successful operations
+        from failed ones, formatting keys as "namespace/schedule_name" for consistency.
 
         Args:
             input_data (list[dict[str, Any]]): The schedule reports. Each item must
                 contain 'namespace', 'schedule_name', 'success', 'message', and optionally
-                'attachment'.
+                'attachment'
 
         Returns:
             tuple[list[str], dict[str, Any]]: A tuple of:
@@ -456,11 +497,14 @@ class Formatters(SientiaMonitoring):
 
     def parse_report(self, input_data: dict[str, dict[str, Any]]) -> tuple[list[str], list[str]]:
         """
-        Parses the report data to extract success and error keys.
+        Parse the report data to extract success and error keys.
+
+        Processes operation reports and separates successful operations from failed ones
+        based on the 'success' field in each report item.
 
         Args:
-            input_data (dict[str, Any]): The input data containing report items.
-                Each item should have a 'success' field indicating success/failure.
+            input_data (dict[str, dict[str, Any]]): The input data containing report items.
+                Each item should have a 'success' field indicating success/failure
 
         Returns:
             tuple[list[str], list[str]]: A tuple containing:
@@ -482,14 +526,17 @@ class Formatters(SientiaMonitoring):
         schedule_data: dict[str, Any],
     ):
         """
-        Manages and sends success and error reports based on the provided keys and data.
+        Manage and send success and error reports based on the provided keys and data.
+
+        Sends separate notifications for successful and failed operations, formatting
+        error messages with attachments when available.
 
         Args:
-            metadata (dict[str, Any]): Metadata for logging and notifications.
-            success_keys (list[str]): List of keys that were successful.
-            error_keys (dict[str, Any]): Dictionary of error keys mapped to error details.
-            schedule_type (str): The type of schedule being reported (e.g., 'created schedules').
-            schedule_data (dict[str, Any]): The schedule data containing items and notification ID.
+            metadata (dict[str, Any]): Metadata for logging and notifications
+            success_keys (list[str]): List of keys that were successful
+            error_keys (dict[str, Any]): Dictionary of error keys mapped to error details
+            schedule_type (str): The type of schedule being reported (e.g., 'created schedules')
+            schedule_data (dict[str, Any]): The schedule data containing items and notification ID
         """
         if len(success_keys) > 0:
             await self.send_success_report(
@@ -517,14 +564,17 @@ class Formatters(SientiaMonitoring):
     @activity.defn(name='report_schedule_orchestration')
     async def report_schedule_orchestration(self, input_data: dict[str, Any]) -> None:
         """
-        Reports the orchestration result to the notification handler.
+        Report the orchestration result to the notification handler.
+
+        Processes schedule orchestration results and sends notifications for
+        created, updated, and deleted schedules with success and error details.
 
         Args:
-            - input_data (dict[str, Any]): The input data containing
-              the orchestration result.
-                - created_schedules (dict[str, Any]): The created schedules.
-                - updated_schedules (dict[str, Any]): The updated schedules.
-                - deleted_schedules (list[str]): The deleted schedules.
+            input_data (dict[str, Any]): The input data containing:
+                - created_schedules (list[dict[str, Any]]): The created schedules
+                - updated_schedules (list[dict[str, Any]]): The updated schedules
+                - deleted_schedules (list[dict[str, Any]]): The deleted schedules
+                - metadata (dict): Metadata for logging purposes
         """
         metadata = input_data.get('metadata', {})
 
@@ -564,13 +614,16 @@ class Formatters(SientiaMonitoring):
     @activity.defn(name='report_slot_orchestration')
     async def report_slot_orchestration(self, input_data: dict[str, Any]) -> None:
         """
-        Reports the orchestration result to the notification handler.
+        Report the slot orchestration result to the notification handler.
+
+        Processes slot orchestration results and sends notifications for
+        inserted and deleted slots with success and error details.
 
         Args:
-            - input_data (dict[str, Any]): The input data containing
-              the orchestration result.
-                - inserted_slots (dict[str, Any]): The inserted slots.
-                - deleted_slots (list[str]): The deleted slots.
+            input_data (dict[str, Any]): The input data containing:
+                - inserted_slots (dict[str, Any]): The inserted slots
+                - deleted_slots (dict[str, Any]): The deleted slots
+                - metadata (dict): Metadata for logging purposes
         """
 
         metadata = input_data.get('metadata', {})
@@ -619,16 +672,19 @@ class Formatters(SientiaMonitoring):
     @activity.defn(name='format_log_report')
     async def format_log_report(self, input_data: dict[str, Any]) -> dict[Hashable, Any]:
         """
-        Formats the receiver_groups status to a dataframe to be stored in the database.
+        Format the receiver_groups status to a dataframe to be stored in the database.
+
+        Transforms receiver group notification data into a structured format suitable
+        for database storage, aggregating notifications by unique notification ID and trigger.
 
         Args:
             input_data (dict[str, Any]): The input data containing:
-                - receiver_groups (dict): The receiver groups configuration.
-                - mail_type (str): The type of mail for the report.
-                - metadata (dict): Metadata for logging purposes.
+                - receiver_groups (dict): The receiver groups configuration with notifications
+                - mail_type (str): The type of mail for the report (Alerts/Reports)
+                - metadata (dict): Metadata for logging purposes
 
         Returns:
-            dict[str, Any]: The formatted log report as a dictionary representation of a DataFrame.
+            dict[Hashable, Any]: The formatted log report as a dictionary representation of a DataFrame
         """
         metadata = input_data['metadata']
         mail_type = input_data['mail_type']
diff --git a/orchestrator/activities/mongo_db.py b/orchestrator/activities/mongo_db.py
index 16dbb2d..0339ab5 100644
--- a/orchestrator/activities/mongo_db.py
+++ b/orchestrator/activities/mongo_db.py
@@ -69,6 +69,8 @@ class MongoDB(SientiaMonitoring):
     def close(self):
         """
         Shutdown the MongoDB client and clean up resources.
+
+        Closes the MongoDB repository connection and shuts down the SientiaMonitoring instance.
         """
         self.mongo_db_repository.close()
         SientiaMonitoring.shutdown(self)
@@ -220,8 +222,13 @@ class MongoDB(SientiaMonitoring):
         """
         Update `updated_at` timestamps for successfully updated pipelines.
 
-        input_data:
-            - updated_pipelines (list[dict]): Pipelines with success flags to consider.
+        Updates the `updated_at` field in the `orchestrated_schedules` collection
+        for all pipelines that were successfully updated in Temporal.
+
+        Args:
+            input_data (dict[str, Any]): Input data containing:
+                - updated_pipelines (list[dict]): Pipelines with success flags to consider
+                - metadata (dict): Metadata for logging purposes
         """
         updated_pipelines = input_data.get('updated_pipelines', [])
         metadata = input_data.get('metadata', {})
@@ -263,8 +270,13 @@ class MongoDB(SientiaMonitoring):
         """
         Insert `updated_at` timestamps for newly created pipelines.
 
-        input_data:
-            - created_pipelines (list[dict]): Pipelines with success flags to consider.
+        Inserts new documents into the `orchestrated_schedules` collection
+        for all pipelines that were successfully created in Temporal.
+
+        Args:
+            input_data (dict[str, Any]): Input data containing:
+                - created_pipelines (list[dict]): Pipelines with success flags to consider
+                - metadata (dict): Metadata for logging purposes
         """
         created_pipelines = input_data.get('created_pipelines', [])
         metadata = input_data.get('metadata', {})
@@ -312,8 +324,13 @@ class MongoDB(SientiaMonitoring):
         """
         Delete timestamp rows for successfully deleted pipelines.
 
-        input_data:
-            - deleted_pipelines (list[dict]): Pipelines with success flags to consider.
+        Removes documents from the `orchestrated_schedules` collection
+        for all pipelines that were successfully deleted from Temporal.
+
+        Args:
+            input_data (dict[str, Any]): Input data containing:
+                - deleted_pipelines (list[dict]): Pipelines with success flags to consider
+                - metadata (dict): Metadata for logging purposes
         """
         deleted_pipelines = input_data.get('deleted_pipelines', [])
         metadata = input_data.get('metadata', {})
@@ -352,10 +369,15 @@ class MongoDB(SientiaMonitoring):
     @activity.defn(name='create_collection_with_ttl_index')
     async def create_collection_with_ttl_index(self, input_data: dict[str, Any]) -> None:
         """
-        Create a collection with a TTL index.
-        input_data:
-            - collection_name (str): The name of the collection to create.
-            - ttl_index (str): The name of the TTL index to create.
+        Create collections with TTL indexes for pipeline topics.
+
+        Creates MongoDB collections for scouter pipeline topics and sets up
+        TTL indexes on the `inserted_at` field to automatically expire old documents.
+
+        Args:
+            input_data (dict[str, Any]): Input data containing:
+                - pipelines (dict[str, Any]): Pipeline configurations with topic names
+                - metadata (dict): Metadata for logging purposes
         """
         pipelines = input_data.get('pipelines', {})
         metadata = input_data.get('metadata', {})
diff --git a/orchestrator/activities/slot_manager.py b/orchestrator/activities/slot_manager.py
index 953c3a6..26b6813 100644
--- a/orchestrator/activities/slot_manager.py
+++ b/orchestrator/activities/slot_manager.py
@@ -71,6 +71,8 @@ class SlotManager(SientiaMonitoring):
     def close(self):
         """
         Close the SlotManager connection and clean up resources.
+
+        Closes the Redis repository connection and shuts down the SientiaMonitoring instance.
         """
         self.redis_repository.close()
         SientiaMonitoring.shutdown(self)
@@ -142,10 +144,16 @@ class SlotManager(SientiaMonitoring):
     @activity.defn(name='load_active_ingestors')
     async def load_active_ingestors(self, input_data: dict[str, Any]) -> list[str]:
         """
-        Load all active ingestors from Redis
+        Load all active ingestors from Redis.
+
+        Retrieves all active ingestor heartbeat keys from Redis to determine
+        which ingestors are currently available for slot assignment.
+
+        Args:
+            input_data (dict[str, Any]): Activity input containing metadata
 
         Returns:
-            list[str]: A list of active ingestors
+            list[str]: A list of active ingestor keys from Redis
         """
 
         metadata = input_data.get('metadata', {})
@@ -259,15 +267,19 @@ class SlotManager(SientiaMonitoring):
     @activity.defn(name='get_last_data_timestamp')
     async def get_last_data_timestamp(self, input_data: dict[str, Any]) -> str | None:
         """
-        Gets the last data timestamp from redis.
+        Get the last data timestamp from Redis.
+
+        Retrieves the last processed timestamp for a specific mail type from Redis.
+        This timestamp is used for incremental data loading to avoid reprocessing
+        already processed notifications.
 
         Args:
             input_data (dict[str, Any]): The input data containing:
-                - metadata (dict): Metadata for logging purposes.
-                - mail_type (str): The type of mail to get timestamp for.
+                - metadata (dict): Metadata for logging purposes
+                - mail_type (str): The type of mail to get timestamp for (Alerts/Reports)
 
         Returns:
-            str | None: The last data timestamp as a string, or None if no timestamp exists.
+            str | None: The last data timestamp as a string, or None if no timestamp exists
         """
         metadata = input_data['metadata']
         key = f'notification_last_timestamp:{input_data["mail_type"]}'
@@ -293,18 +305,22 @@ class SlotManager(SientiaMonitoring):
         return data_hold
 
     @activity.defn(name='put_last_data_timestamp')
-    async def put_last_data_timestamp(self, input_data: dict[str, Any]):
+    async def put_last_data_timestamp(self, input_data: dict[str, Any]) -> str | None:
         """
-        Puts the last data timestamp into redis.
+        Store the last data timestamp in Redis.
+
+        Extracts the maximum timestamp from the provided data and stores it in Redis
+        with a TTL for the specified mail type. This enables incremental processing
+        in subsequent workflow executions.
 
         Args:
             input_data (dict[str, Any]): The input data containing:
-                - metadata (dict): Metadata for logging purposes.
-                - data (list[dict]): The data to extract timestamp from.
-                - mail_type (str): The type of mail to store timestamp for.
+                - metadata (dict): Metadata for logging purposes
+                - data (list[dict]): The data to extract timestamp from
+                - mail_type (str): The type of mail to store timestamp for (Alerts/Reports)
 
         Returns:
-            str | None: The last data timestamp that was stored, or None if no data exists.
+            str | None: The last data timestamp that was stored, or None if no data exists
         """
         metadata = input_data['metadata']
         key = f'notification_last_timestamp:{input_data["mail_type"]}'
@@ -426,11 +442,14 @@ class SlotManager(SientiaMonitoring):
         """
         Store notification cache in Redis to track recently sent notifications.
 
+        Stores successfully sent notifications in Redis with a TTL to prevent
+        duplicate alert delivery. Only notifications with status 'sent' are cached.
+
         Args:
             input_data (dict[str, Any]): The input data containing:
-                - metadata (dict): Metadata for logging purposes.
-                - log_report (list[dict]): The log report containing notification statuses.
-                - sent_ttl (int): Time to live for sent notification cache in seconds.
+                - metadata (dict): Metadata for logging purposes
+                - log_report (list[dict]): The log report containing notification statuses
+                - sent_ttl (int): Time to live for sent notification cache in seconds
         """
         metadata = input_data['metadata']
         log_report = DataFrame(input_data['log_report'])
diff --git a/orchestrator/activities/temporal_manager.py b/orchestrator/activities/temporal_manager.py
index 6c423f5..6b0932a 100644
--- a/orchestrator/activities/temporal_manager.py
+++ b/orchestrator/activities/temporal_manager.py
@@ -68,6 +68,8 @@ class TemporalManager(SientiaMonitoring):
     def close(self):
         """
         Close the TemporalManager connection and clean up resources.
+
+        Shuts down the SientiaMonitoring instance and releases all resources.
         """
         SientiaMonitoring.shutdown(self)
 
@@ -80,7 +82,9 @@ class TemporalManager(SientiaMonitoring):
     async def connect_to_temporal(self):
         """
         Connect to Temporal server namespaces used by scouter and laborious workflows.
+
         Creates and caches `Client` connections for both namespaces for later use.
+        The connections are stored in `temporal_clients` dictionary for efficient access.
         """
         self.logger.info(f'Connecting to Temporal side namespaces at {self.temporal_host}')
         self.logger.info(f'Scouter namespace: {self.scouter_namespace}')
@@ -108,8 +112,9 @@ class TemporalManager(SientiaMonitoring):
         Any schedule marked with search attribute `orchestrated=true` that does not
         exist in MongoDB collection `orchestrated_schedules` will be deleted.
 
-        input_data:
-            - orchestrated_schedules (dict[str, Any]): Current orchestrated schedules from MongoDB.
+        Args:
+            input_data (dict[str, Any]): Input data containing:
+                - orchestrated_schedules (dict[str, Any]): Current orchestrated schedules from MongoDB.
         """
         metadata = input_data['metadata']
 
@@ -320,8 +325,10 @@ class TemporalManager(SientiaMonitoring):
 
                         input_data.description.schedule.spec.intervals = [
                             ScheduleIntervalSpec(
-                                every=timedelta(seconds=parse_frequency(
-                                    schedule.get('frequency', '1m')))
+                                every=timedelta(
+                                    seconds=parse_frequency(schedule.get('frequency', '1m'))),
+                                offset=timedelta(
+                                    seconds=parse_frequency(schedule.get('offset', '0m'))),
                             )
                         ]
 
diff --git a/orchestrator/utils/email_builder.py b/orchestrator/utils/email_builder.py
index db67591..c6e4d23 100644
--- a/orchestrator/utils/email_builder.py
+++ b/orchestrator/utils/email_builder.py
@@ -32,12 +32,15 @@ class EmailBuilder:
         """
         Replace parameters in a Jinja2 template with provided values.
 
+        Renders a Jinja2 template string with the provided parameter dictionary,
+        replacing all template variables with their corresponding values.
+
         Args:
-            template (str): The Jinja2 template string.
-            parameters (dict): Dictionary of parameters to replace in the template.
+            template (str): The Jinja2 template string
+            parameters (dict): Dictionary of parameters to replace in the template
 
         Returns:
-            str: The rendered template with parameters replaced.
+            str: The rendered template with parameters replaced
         """
         # Create a Jinja2 template from the provided string
         template_obj = Template(template)
@@ -48,13 +51,16 @@ class EmailBuilder:
         """
         Build parameters dictionary for email templates based on general events and mail type.
 
+        Processes notification events organized by level and model, rendering HTML
+        sections for each notification level using the general template.
+
         Args:
             general_events (dict): Dictionary containing events categorized by level (ERROR, WARNING, INFO).
-                Each level contains a 'models' key with model-specific event data.
-            mail_type (str): The type of email being sent.
+                Each level contains a 'models' key with model-specific event data
+            mail_type (str): The type of email being sent (Alerts/Reports)
 
         Returns:
-            dict: Dictionary with mail_type and rendered event sections for each notification level.
+            dict: Dictionary with mail_type and rendered event sections for each notification level
         """
         error_events = general_events.get('ERROR', {})
         warning_events = general_events.get('WARNING', {})
@@ -79,16 +85,20 @@ class EmailBuilder:
 
     def build_email(self, report_data: list[dict[str, Any]], mail_type: str) -> str:
         """
-        Builds the email HTML by organizing report data by notification level and model.
+        Build the email HTML by organizing report data by notification level and model.
+
+        Organizes notification data by level and model, then renders the complete
+        HTML email using the report template with all event sections.
 
         Args:
-            report_data (List[Dict[str, Any]]): List of notification reports, each containing:
+            report_data (list[dict[str, Any]]): List of notification reports, each containing:
                 - level (str): Notification level (ERROR, WARNING, INFO)
                 - model_name (str): Name of the model
                 - Additional notification details
+            mail_type (str): The type of email being built (Alerts/Reports)
 
         Returns:
-            str: Complete HTML email content ready for sending.
+            str: Complete HTML email content ready for sending
         """
         general_events: dict[str, dict[str, Any]] = {}
 
diff --git a/orchestrator/utils/orchestrator_functions.py b/orchestrator/utils/orchestrator_functions.py
index 02371a1..b8e7eec 100644
--- a/orchestrator/utils/orchestrator_functions.py
+++ b/orchestrator/utils/orchestrator_functions.py
@@ -32,6 +32,63 @@ def common_config(config: dict[str, Any]):
     }
 
 
+def drift(config: dict[str, Any]):
+    """
+    Build drift configuration from pipeline config.
+
+    Creates a drift detection workflow configuration with database table mappings
+    and drift metric specifications for monitoring data distribution changes.
+
+    Args:
+        config (dict[str, Any]): Pipeline configuration containing:
+            - interval_minutes (int, optional): Detection interval in minutes (default: 60)
+            - drift_metrics (list[str], optional): List of drift metrics to compute
+                (default: ['kolmogorov_smirnov', 'jensen_shannon', 'wasserstein'])
+            - Additional fields from common_config
+
+    Returns:
+        dict[str, Any]: Drift configuration with workflow type set to 'drift'
+    """
+    return {
+        **common_config(config),
+        'schema': 'sientia_data',
+        'source_table_name': 'laborious_data',
+        'target_table_name': 'drift_metrics',
+        'interval': config.get('interval_minutes', 60),
+        'drift_metrics': config.get(
+            'drift_metrics', ['kolmogorov_smirnov', 'jensen_shannon', 'wasserstein']
+        ),
+    }
+
+
+def simple_metrics(config: dict[str, Any]):
+    """
+    Build simple metrics configuration from pipeline config.
+
+    Creates a simple metrics computation workflow configuration for calculating
+    model performance metrics like RMSE, MSE, MAE, and R².
+
+    Args:
+        config (dict[str, Any]): Pipeline configuration containing:
+            - interval_minutes (int, optional): Computation interval in minutes (default: 60)
+            - metrics (list[str], optional): List of metrics to compute
+                (default: ['rmse', 'mse', 'mae', 'r2'])
+            - Additional fields from common_config
+
+    Returns:
+        dict[str, Any]: Simple metrics configuration with workflow type set to 'simple_metrics'
+    """
+    return {
+        **common_config(config),
+        'schema': 'sientia_data',
+        'predictions_table_name': 'predictions',
+        'data_table_name': 'laborious_data',
+        'target_table_name': 'simple_metrics',
+        'interval_minutes': config.get('interval_minutes', 60),
+        'metrics': config.get('metrics', ['rmse', 'mse', 'mae', 'r2']),
+    }
+
+
 def minimal_retrain(config: dict[str, Any]):
     """
     Build minimal retrain configuration from pipeline config.
@@ -47,8 +104,6 @@ def minimal_retrain(config: dict[str, Any]):
     """
     return {
         **common_config(config),
-        'workflow_type': 'minimal_retrain',
-        'schedule_name': config['schedule_name'],
         'query': config['query'],
         'schema': 'sientia_data',
         'table_name': 'log_retrain',
@@ -193,6 +248,8 @@ def predictions_batch(config: dict[str, Any]):
         'datetime_columns': config.get('datetime_columns', []),
         'schema': 'sientia_data',
         'table_name': 'predictions',
+        'save_transform': config.get('save_transform', True),
+        'transform_table_name': 'transformed_data',
         'retention_time': config.get('model_retention_minutes', 60) * 60,
         'opc_output_config': tags,
         'input_filters': overlap_filter_config(
@@ -216,13 +273,17 @@ def predictions_batch(config: dict[str, Any]):
 
 def gather_read_tags(pipelines: list[dict[str, Any]]) -> dict[str, Any]:
     """
-    Gathers all read tags from input pipelines.
+    Gather all read tags from input pipelines.
+
+    Collects all read tags from scouter pipelines and organizes them by
+    server_id and tag_address, tracking which topics each tag is associated with.
 
     Args:
-        - pipelines (list[dict[str, Any]]): The schedules to process.
+        pipelines (list[dict[str, Any]]): The pipeline configurations to process
 
     Returns:
-        - dict[str, Any]: The read tags dictionary
+        dict[str, Any]: Dictionary of read tags keyed by "server_id:tag_address",
+            each containing tag configuration and associated topics
     """
 
     tags = {}
@@ -245,19 +306,24 @@ def build_tag_config(
     """
     Build tag configuration for a specific slot and OPC server.
 
+    Organizes tags by OPC server and calculates the minimum subscription period
+    based on tag frequencies. Validates that all server IDs exist in the OPC
+    servers configuration.
+
     Args:
         tags (list[dict[str, Any]]): List of tag configurations containing:
             - server_id (str): ID of the OPC server
             - tag_address (str): Address of the tag
-        slot_config (dict[str, Any]): Current slot configuration to update.
-        opc_servers (dict[str, Any]): Dictionary of OPC server configurations.
-        i (int): Slot number to configure.
+            - frequency (int): Tag read frequency in milliseconds
+        opc_servers (dict[str, Any]): Dictionary of OPC server configurations
 
     Returns:
-        dict[str, Any]: Updated slot configuration with the new tag.
+        tuple[dict[str, Any], list]: A tuple containing:
+            - Slot configuration dictionary organized by server name
+            - List of server IDs that were not found in opc_servers
 
     Raises:
-        ValueError: If the specified server_id is not found in opc_servers.
+        ValueError: If the specified server_id is not found in opc_servers
     """
 
     slot_config = {}
diff --git a/orchestrator/worker/worker.py b/orchestrator/worker/worker.py
index 6283cbd..fe65d4f 100644
--- a/orchestrator/worker/worker.py
+++ b/orchestrator/worker/worker.py
@@ -39,7 +39,8 @@ async def main():
 
     Sets up MongoDB connection, notification handler, Temporal client, and starts
     multiple workers for different task queues (orchestrator, alerts, reports).
-    Handles graceful shutdown and error handling.
+    Handles graceful shutdown and error handling. Initializes Prometheus metrics
+    server and SDK metrics for monitoring.
     """
     host = os.getenv('TEMPORAL_HOST', 'localhost:7233')
     namespace = os.getenv('TEMPORAL_NAMESPACE', 'default')
@@ -206,7 +207,11 @@ def start_prometheus_server():
     Start the Prometheus metrics server on the configured port.
 
     Sets up HTTP server for metrics collection and marks the application as UP.
-    Exits the application if the server fails to start.
+    Exits the application if the server fails to start. The metrics server
+    exposes application metrics on the port specified by HTTP_METRICS_PORT.
+
+    Raises:
+        SystemExit: If the metrics server fails to start
     """
     try:
         port = int(os.getenv('HTTP_METRICS_PORT', 9090))
diff --git a/requirements.txt b/requirements.txt
index 4c94dc5..cadaefb 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -4,5 +4,5 @@ sqlalchemy
 redis
 pymongo
 jinja2
-git+ssh://git@github.com/Aignosi/sientia-dataops-library.git@1.5.3
+git+ssh://git@github.com/Aignosi/sientia-dataops-library.git@1.6.1
 prometheus-client
diff --git a/test.ipynb b/test.ipynb
index 1843727..a101c3c 100644
--- a/test.ipynb
+++ b/test.ipynb
@@ -617,13 +617,2049 @@
     "        print(f\"Chave: {key}, Valor: {value}\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "e8025cbb",
+   "metadata": {},
+   "source": [
+    "## Model Monitoring"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "87a9dc89",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "from sientia.ModelAnalysis import ModelAnalysis\n",
+    "\n",
+    "config = {\n",
+    "    \"target\": \"Square\",\n",
+    "    \"prediction\": \"prediction\",\n",
+    "    \"timestamp\": \"timestamp\",\n",
+    "    \"features\": [\"Counter\", \"Rollout\"]\n",
+    "}\n",
+    "\n",
+    "model = ModelAnalysis(config=config)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "2a74ad2f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sientia_do.temporal.activities.postgres import Postgres\n",
+    "from unittest.mock import AsyncMock\n",
+    "from pandas import DataFrame\n",
+    "\n",
+    "postgres = Postgres(\n",
+    "    host=\"localhost\",\n",
+    "    port=5432,\n",
+    "    dbname=\"sientia\",\n",
+    "    user=\"sientia\",\n",
+    "    password=\"sientia\",\n",
+    "    min_connections=1,\n",
+    "    max_connections=10,\n",
+    "    logger=AsyncMock(),\n",
+    "    notification_handler=AsyncMock(),\n",
+    "    metrics_controller=AsyncMock()\n",
+    ")\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "938cecbd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/grezewave/Documents/projects/sientia/sientia-dataops-orchestrator_temporal/venv/lib/python3.11/site-packages/sientia_do/observability/sientia_monitoring.py:83: RuntimeWarning: coroutine 'AsyncMockMixin._execute_mock_call' was never awaited\n",
+      "  self.logger.custom_info(message, metadata)\n",
+      "/home/grezewave/Documents/projects/sientia/sientia-dataops-orchestrator_temporal/venv/lib/python3.11/site-packages/sientia_do/observability/sientia_monitoring.py:59: RuntimeWarning: coroutine 'AsyncMockMixin._execute_mock_call' was never awaited\n",
+      "  self.metrics_controller.start()\n",
+      "/home/grezewave/Documents/projects/sientia/sientia-dataops-orchestrator_temporal/venv/lib/python3.11/site-packages/sientia_do/observability/sientia_monitoring.py:83: RuntimeWarning: coroutine 'AsyncMockMixin._execute_mock_call' was never awaited\n",
+      "  self.logger.custom_info(message, metadata)\n",
+      "/home/grezewave/Documents/projects/sientia/sientia-dataops-orchestrator_temporal/venv/lib/python3.11/site-packages/sientia_do/observability/sientia_monitoring.py:95: RuntimeWarning: coroutine 'AsyncMockMixin._execute_mock_call' was never awaited\n",
+      "  self.logger.custom_debug(message, metadata)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>value</th>\n",
+       "      <th>prediction</th>\n",
+       "      <th>timestamp</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>42.2950</td>\n",
+       "      <td>-3.018465</td>\n",
+       "      <td>2025-11-12 12:44:50+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>1.8610</td>\n",
+       "      <td>-3.018465</td>\n",
+       "      <td>2025-11-12 12:44:50+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-45.0980</td>\n",
+       "      <td>-3.018465</td>\n",
+       "      <td>2025-11-12 12:44:50+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>0.3970</td>\n",
+       "      <td>2.341423</td>\n",
+       "      <td>2025-11-12 12:44:20+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-40.0260</td>\n",
+       "      <td>2.341423</td>\n",
+       "      <td>2025-11-12 12:44:20+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>43.3190</td>\n",
+       "      <td>2.341423</td>\n",
+       "      <td>2025-11-12 12:44:20+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>-0.2645</td>\n",
+       "      <td>4.696591</td>\n",
+       "      <td>2025-11-12 12:42:15+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>42.1850</td>\n",
+       "      <td>4.696591</td>\n",
+       "      <td>2025-11-12 12:42:15+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-37.8385</td>\n",
+       "      <td>4.696591</td>\n",
+       "      <td>2025-11-12 12:42:15+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>2.8880</td>\n",
+       "      <td>-70.845157</td>\n",
+       "      <td>2025-11-11 23:00:48+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>18.7945</td>\n",
+       "      <td>-70.845157</td>\n",
+       "      <td>2025-11-11 23:00:48+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-12.6565</td>\n",
+       "      <td>-70.845157</td>\n",
+       "      <td>2025-11-11 23:00:48+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>17.7415</td>\n",
+       "      <td>-71.894590</td>\n",
+       "      <td>2025-11-11 23:00:18+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-11.1570</td>\n",
+       "      <td>-71.894590</td>\n",
+       "      <td>2025-11-11 23:00:18+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>2.1610</td>\n",
+       "      <td>-71.894590</td>\n",
+       "      <td>2025-11-11 23:00:18+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>-2.0490</td>\n",
+       "      <td>-67.033953</td>\n",
+       "      <td>2025-11-11 22:59:48+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>16.5365</td>\n",
+       "      <td>-67.033953</td>\n",
+       "      <td>2025-11-11 22:59:48+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-15.2205</td>\n",
+       "      <td>-67.033953</td>\n",
+       "      <td>2025-11-11 22:59:48+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-11.7930</td>\n",
+       "      <td>-70.514462</td>\n",
+       "      <td>2025-11-11 22:59:18+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>-4.3350</td>\n",
+       "      <td>-70.514462</td>\n",
+       "      <td>2025-11-11 22:59:18+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>16.3065</td>\n",
+       "      <td>-70.514462</td>\n",
+       "      <td>2025-11-11 22:59:18+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>0.6840</td>\n",
+       "      <td>-72.523279</td>\n",
+       "      <td>2025-11-11 22:58:48+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-9.2570</td>\n",
+       "      <td>-72.523279</td>\n",
+       "      <td>2025-11-11 22:58:48+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>14.9965</td>\n",
+       "      <td>-72.523279</td>\n",
+       "      <td>2025-11-11 22:58:48+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>1.1700</td>\n",
+       "      <td>-72.831684</td>\n",
+       "      <td>2025-11-11 22:58:18+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-7.0635</td>\n",
+       "      <td>-72.831684</td>\n",
+       "      <td>2025-11-11 22:58:18+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>10.9875</td>\n",
+       "      <td>-72.831684</td>\n",
+       "      <td>2025-11-11 22:58:18+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-2.0110</td>\n",
+       "      <td>-77.865944</td>\n",
+       "      <td>2025-11-11 22:57:48+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>10.4545</td>\n",
+       "      <td>-77.865944</td>\n",
+       "      <td>2025-11-11 22:57:48+00:00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>-0.2070</td>\n",
+       "      <td>-77.865944</td>\n",
+       "      <td>2025-11-11 22:57:48+00:00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   variable    value  prediction                 timestamp\n",
+       "0    Square  42.2950   -3.018465 2025-11-12 12:44:50+00:00\n",
+       "1   Rollout   1.8610   -3.018465 2025-11-12 12:44:50+00:00\n",
+       "2   Counter -45.0980   -3.018465 2025-11-12 12:44:50+00:00\n",
+       "3   Rollout   0.3970    2.341423 2025-11-12 12:44:20+00:00\n",
+       "4   Counter -40.0260    2.341423 2025-11-12 12:44:20+00:00\n",
+       "5    Square  43.3190    2.341423 2025-11-12 12:44:20+00:00\n",
+       "6   Rollout  -0.2645    4.696591 2025-11-12 12:42:15+00:00\n",
+       "7    Square  42.1850    4.696591 2025-11-12 12:42:15+00:00\n",
+       "8   Counter -37.8385    4.696591 2025-11-12 12:42:15+00:00\n",
+       "9    Square   2.8880  -70.845157 2025-11-11 23:00:48+00:00\n",
+       "10  Rollout  18.7945  -70.845157 2025-11-11 23:00:48+00:00\n",
+       "11  Counter -12.6565  -70.845157 2025-11-11 23:00:48+00:00\n",
+       "12  Rollout  17.7415  -71.894590 2025-11-11 23:00:18+00:00\n",
+       "13  Counter -11.1570  -71.894590 2025-11-11 23:00:18+00:00\n",
+       "14   Square   2.1610  -71.894590 2025-11-11 23:00:18+00:00\n",
+       "15   Square  -2.0490  -67.033953 2025-11-11 22:59:48+00:00\n",
+       "16  Rollout  16.5365  -67.033953 2025-11-11 22:59:48+00:00\n",
+       "17  Counter -15.2205  -67.033953 2025-11-11 22:59:48+00:00\n",
+       "18  Counter -11.7930  -70.514462 2025-11-11 22:59:18+00:00\n",
+       "19   Square  -4.3350  -70.514462 2025-11-11 22:59:18+00:00\n",
+       "20  Rollout  16.3065  -70.514462 2025-11-11 22:59:18+00:00\n",
+       "21   Square   0.6840  -72.523279 2025-11-11 22:58:48+00:00\n",
+       "22  Counter  -9.2570  -72.523279 2025-11-11 22:58:48+00:00\n",
+       "23  Rollout  14.9965  -72.523279 2025-11-11 22:58:48+00:00\n",
+       "24   Square   1.1700  -72.831684 2025-11-11 22:58:18+00:00\n",
+       "25  Counter  -7.0635  -72.831684 2025-11-11 22:58:18+00:00\n",
+       "26  Rollout  10.9875  -72.831684 2025-11-11 22:58:18+00:00\n",
+       "27  Counter  -2.0110  -77.865944 2025-11-11 22:57:48+00:00\n",
+       "28  Rollout  10.4545  -77.865944 2025-11-11 22:57:48+00:00\n",
+       "29   Square  -0.2070  -77.865944 2025-11-11 22:57:48+00:00"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>value</th>\n",
+       "      <th>prediction</th>\n",
+       "      <th>timestamp</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>42.2950</td>\n",
+       "      <td>-3.018465</td>\n",
+       "      <td>2025-11-12 12:44:50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>1.8610</td>\n",
+       "      <td>-3.018465</td>\n",
+       "      <td>2025-11-12 12:44:50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-45.0980</td>\n",
+       "      <td>-3.018465</td>\n",
+       "      <td>2025-11-12 12:44:50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>0.3970</td>\n",
+       "      <td>2.341423</td>\n",
+       "      <td>2025-11-12 12:44:20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-40.0260</td>\n",
+       "      <td>2.341423</td>\n",
+       "      <td>2025-11-12 12:44:20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>43.3190</td>\n",
+       "      <td>2.341423</td>\n",
+       "      <td>2025-11-12 12:44:20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>-0.2645</td>\n",
+       "      <td>4.696591</td>\n",
+       "      <td>2025-11-12 12:42:15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>42.1850</td>\n",
+       "      <td>4.696591</td>\n",
+       "      <td>2025-11-12 12:42:15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-37.8385</td>\n",
+       "      <td>4.696591</td>\n",
+       "      <td>2025-11-12 12:42:15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>2.8880</td>\n",
+       "      <td>-70.845157</td>\n",
+       "      <td>2025-11-11 23:00:48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>18.7945</td>\n",
+       "      <td>-70.845157</td>\n",
+       "      <td>2025-11-11 23:00:48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-12.6565</td>\n",
+       "      <td>-70.845157</td>\n",
+       "      <td>2025-11-11 23:00:48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>17.7415</td>\n",
+       "      <td>-71.894590</td>\n",
+       "      <td>2025-11-11 23:00:18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-11.1570</td>\n",
+       "      <td>-71.894590</td>\n",
+       "      <td>2025-11-11 23:00:18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>2.1610</td>\n",
+       "      <td>-71.894590</td>\n",
+       "      <td>2025-11-11 23:00:18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>-2.0490</td>\n",
+       "      <td>-67.033953</td>\n",
+       "      <td>2025-11-11 22:59:48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>16.5365</td>\n",
+       "      <td>-67.033953</td>\n",
+       "      <td>2025-11-11 22:59:48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-15.2205</td>\n",
+       "      <td>-67.033953</td>\n",
+       "      <td>2025-11-11 22:59:48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-11.7930</td>\n",
+       "      <td>-70.514462</td>\n",
+       "      <td>2025-11-11 22:59:18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>-4.3350</td>\n",
+       "      <td>-70.514462</td>\n",
+       "      <td>2025-11-11 22:59:18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>16.3065</td>\n",
+       "      <td>-70.514462</td>\n",
+       "      <td>2025-11-11 22:59:18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>0.6840</td>\n",
+       "      <td>-72.523279</td>\n",
+       "      <td>2025-11-11 22:58:48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-9.2570</td>\n",
+       "      <td>-72.523279</td>\n",
+       "      <td>2025-11-11 22:58:48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>14.9965</td>\n",
+       "      <td>-72.523279</td>\n",
+       "      <td>2025-11-11 22:58:48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>1.1700</td>\n",
+       "      <td>-72.831684</td>\n",
+       "      <td>2025-11-11 22:58:18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-7.0635</td>\n",
+       "      <td>-72.831684</td>\n",
+       "      <td>2025-11-11 22:58:18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>10.9875</td>\n",
+       "      <td>-72.831684</td>\n",
+       "      <td>2025-11-11 22:58:18</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>Counter</td>\n",
+       "      <td>-2.0110</td>\n",
+       "      <td>-77.865944</td>\n",
+       "      <td>2025-11-11 22:57:48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>10.4545</td>\n",
+       "      <td>-77.865944</td>\n",
+       "      <td>2025-11-11 22:57:48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Square</td>\n",
+       "      <td>-0.2070</td>\n",
+       "      <td>-77.865944</td>\n",
+       "      <td>2025-11-11 22:57:48</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   variable    value  prediction            timestamp\n",
+       "0    Square  42.2950   -3.018465  2025-11-12 12:44:50\n",
+       "1   Rollout   1.8610   -3.018465  2025-11-12 12:44:50\n",
+       "2   Counter -45.0980   -3.018465  2025-11-12 12:44:50\n",
+       "3   Rollout   0.3970    2.341423  2025-11-12 12:44:20\n",
+       "4   Counter -40.0260    2.341423  2025-11-12 12:44:20\n",
+       "5    Square  43.3190    2.341423  2025-11-12 12:44:20\n",
+       "6   Rollout  -0.2645    4.696591  2025-11-12 12:42:15\n",
+       "7    Square  42.1850    4.696591  2025-11-12 12:42:15\n",
+       "8   Counter -37.8385    4.696591  2025-11-12 12:42:15\n",
+       "9    Square   2.8880  -70.845157  2025-11-11 23:00:48\n",
+       "10  Rollout  18.7945  -70.845157  2025-11-11 23:00:48\n",
+       "11  Counter -12.6565  -70.845157  2025-11-11 23:00:48\n",
+       "12  Rollout  17.7415  -71.894590  2025-11-11 23:00:18\n",
+       "13  Counter -11.1570  -71.894590  2025-11-11 23:00:18\n",
+       "14   Square   2.1610  -71.894590  2025-11-11 23:00:18\n",
+       "15   Square  -2.0490  -67.033953  2025-11-11 22:59:48\n",
+       "16  Rollout  16.5365  -67.033953  2025-11-11 22:59:48\n",
+       "17  Counter -15.2205  -67.033953  2025-11-11 22:59:48\n",
+       "18  Counter -11.7930  -70.514462  2025-11-11 22:59:18\n",
+       "19   Square  -4.3350  -70.514462  2025-11-11 22:59:18\n",
+       "20  Rollout  16.3065  -70.514462  2025-11-11 22:59:18\n",
+       "21   Square   0.6840  -72.523279  2025-11-11 22:58:48\n",
+       "22  Counter  -9.2570  -72.523279  2025-11-11 22:58:48\n",
+       "23  Rollout  14.9965  -72.523279  2025-11-11 22:58:48\n",
+       "24   Square   1.1700  -72.831684  2025-11-11 22:58:18\n",
+       "25  Counter  -7.0635  -72.831684  2025-11-11 22:58:18\n",
+       "26  Rollout  10.9875  -72.831684  2025-11-11 22:58:18\n",
+       "27  Counter  -2.0110  -77.865944  2025-11-11 22:57:48\n",
+       "28  Rollout  10.4545  -77.865944  2025-11-11 22:57:48\n",
+       "29   Square  -0.2070  -77.865944  2025-11-11 22:57:48"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pandas import DataFrame, to_datetime\n",
+    "\n",
+    "query_data = \"\"\"\n",
+    "select ld.variable, ld.value, p.prediction, p.\"timestamp\"\n",
+    "from sientia_data.laborious_data ld\n",
+    "    right join sientia_data.predictions p \n",
+    "        on ld.timestamp = p.timestamp\n",
+    "        and ld.model_id = p.model_id\n",
+    "    where\n",
+    "        ld.model_id = '1'\n",
+    "    order by\n",
+    "        ld.created_at desc limit 30;\n",
+    "\"\"\"\n",
+    "\n",
+    "input_data = {\n",
+    "    \"query\": query_data,\n",
+    "    \"metadata\": {}\n",
+    "}\n",
+    "\n",
+    "\n",
+    "raw_data = DataFrame(await postgres.load_custom_query(\n",
+    "    input_data))\n",
+    "\n",
+    "raw_data['timestamp'] = to_datetime(raw_data['timestamp'])\n",
+    "raw_data['timestamp'] = raw_data['timestamp'].dt.strftime('%Y-%m-%d %H:%M:%S')\n",
+    "\n",
+    "display(raw_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "297f648f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>timestamp</th>\n",
+       "      <th>prediction</th>\n",
+       "      <th>Counter</th>\n",
+       "      <th>Rollout</th>\n",
+       "      <th>Square</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2025-11-11 22:57:48</td>\n",
+       "      <td>-77.865944</td>\n",
+       "      <td>-2.0110</td>\n",
+       "      <td>10.4545</td>\n",
+       "      <td>-0.207</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2025-11-11 22:58:18</td>\n",
+       "      <td>-72.831684</td>\n",
+       "      <td>-7.0635</td>\n",
+       "      <td>10.9875</td>\n",
+       "      <td>1.170</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2025-11-11 22:58:48</td>\n",
+       "      <td>-72.523279</td>\n",
+       "      <td>-9.2570</td>\n",
+       "      <td>14.9965</td>\n",
+       "      <td>0.684</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2025-11-11 22:59:18</td>\n",
+       "      <td>-70.514462</td>\n",
+       "      <td>-11.7930</td>\n",
+       "      <td>16.3065</td>\n",
+       "      <td>-4.335</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2025-11-11 22:59:48</td>\n",
+       "      <td>-67.033953</td>\n",
+       "      <td>-15.2205</td>\n",
+       "      <td>16.5365</td>\n",
+       "      <td>-2.049</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2025-11-11 23:00:18</td>\n",
+       "      <td>-71.894590</td>\n",
+       "      <td>-11.1570</td>\n",
+       "      <td>17.7415</td>\n",
+       "      <td>2.161</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2025-11-11 23:00:48</td>\n",
+       "      <td>-70.845157</td>\n",
+       "      <td>-12.6565</td>\n",
+       "      <td>18.7945</td>\n",
+       "      <td>2.888</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2025-11-12 12:42:15</td>\n",
+       "      <td>4.696591</td>\n",
+       "      <td>-37.8385</td>\n",
+       "      <td>-0.2645</td>\n",
+       "      <td>42.185</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2025-11-12 12:44:20</td>\n",
+       "      <td>2.341423</td>\n",
+       "      <td>-40.0260</td>\n",
+       "      <td>0.3970</td>\n",
+       "      <td>43.319</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2025-11-12 12:44:50</td>\n",
+       "      <td>-3.018465</td>\n",
+       "      <td>-45.0980</td>\n",
+       "      <td>1.8610</td>\n",
+       "      <td>42.295</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             timestamp  prediction  Counter  Rollout  Square\n",
+       "0  2025-11-11 22:57:48  -77.865944  -2.0110  10.4545  -0.207\n",
+       "1  2025-11-11 22:58:18  -72.831684  -7.0635  10.9875   1.170\n",
+       "2  2025-11-11 22:58:48  -72.523279  -9.2570  14.9965   0.684\n",
+       "3  2025-11-11 22:59:18  -70.514462 -11.7930  16.3065  -4.335\n",
+       "4  2025-11-11 22:59:48  -67.033953 -15.2205  16.5365  -2.049\n",
+       "5  2025-11-11 23:00:18  -71.894590 -11.1570  17.7415   2.161\n",
+       "6  2025-11-11 23:00:48  -70.845157 -12.6565  18.7945   2.888\n",
+       "7  2025-11-12 12:42:15    4.696591 -37.8385  -0.2645  42.185\n",
+       "8  2025-11-12 12:44:20    2.341423 -40.0260   0.3970  43.319\n",
+       "9  2025-11-12 12:44:50   -3.018465 -45.0980   1.8610  42.295"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pandas import merge, pivot\n",
+    "\n",
+    "raw_data.drop_duplicates(subset=[\"timestamp\", \"prediction\", \"variable\"], inplace=True, keep=\"first\")\n",
+    "data = raw_data.pivot(index=[\"timestamp\", \"prediction\"], columns=\"variable\", values=\"value\")\n",
+    "\n",
+    "data.columns.name = None\n",
+    "data.reset_index(inplace=True)\n",
+    "display(data)\n",
+    "\n",
+    "\n",
+    "drift_methods = ['kolmogorov_smirnov']#, 'jensen_shannon', 'wasserstein']\n",
+    "chunk_period = 's'\n",
+    "target_col = \"Square\"\n",
+    "timestamp_col = \"timestamp\"\n",
+    "\n",
+    "data.to_csv(\"data.csv\", index=False)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "9ab4774a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mlflow.tracking import MlflowClient\n",
+    "from os import environ\n",
+    "\n",
+    "environ['MLFLOW_TRACKING_USERNAME'] = 'aignosi'\n",
+    "environ['MLFLOW_TRACKING_PASSWORD'] = '1L0FP50j3ncp123'\n",
+    "environ['MLFLOW_TRACKING_URI'] = 'http://localhost:5080'\n",
+    "mlflow_client = MlflowClient()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "e8427625",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "run_id = '9e9fa748822c44ab92dd769d6a45c4f4'\n",
+    "output_dir = './tmp/model'\n",
+    "\n",
+    "artifacts = mlflow_client.list_artifacts(run_id)\n",
+    "paths = [artifact.path for artifact in artifacts]\n",
+    "\n",
+    "any(artifact.path == 'retrain_data.csv' for artifact in artifacts)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "cf4ddf41",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>timestamp</th>\n",
+       "      <th>Counter</th>\n",
+       "      <th>Rollout</th>\n",
+       "      <th>Square</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2025-11-10 18:58:39</td>\n",
+       "      <td>13.5970</td>\n",
+       "      <td>-52.4500</td>\n",
+       "      <td>43.381</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2025-11-10 18:58:49</td>\n",
+       "      <td>15.0660</td>\n",
+       "      <td>-50.0240</td>\n",
+       "      <td>45.813</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2025-11-10 18:58:54</td>\n",
+       "      <td>14.2780</td>\n",
+       "      <td>-49.4810</td>\n",
+       "      <td>47.677</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2025-11-10 18:59:04</td>\n",
+       "      <td>14.2080</td>\n",
+       "      <td>-51.8015</td>\n",
+       "      <td>48.995</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2025-11-10 18:59:09</td>\n",
+       "      <td>16.3530</td>\n",
+       "      <td>-52.6850</td>\n",
+       "      <td>47.745</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2025-11-10 18:59:19</td>\n",
+       "      <td>15.5415</td>\n",
+       "      <td>-53.5625</td>\n",
+       "      <td>48.327</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2025-11-10 18:59:24</td>\n",
+       "      <td>16.8580</td>\n",
+       "      <td>-53.6960</td>\n",
+       "      <td>47.160</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2025-11-10 18:59:34</td>\n",
+       "      <td>14.9745</td>\n",
+       "      <td>-54.7510</td>\n",
+       "      <td>48.480</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2025-11-10 18:59:39</td>\n",
+       "      <td>12.3020</td>\n",
+       "      <td>-53.4330</td>\n",
+       "      <td>48.631</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2025-11-10 18:59:49</td>\n",
+       "      <td>12.5640</td>\n",
+       "      <td>-52.9805</td>\n",
+       "      <td>50.130</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             timestamp  Counter  Rollout  Square\n",
+       "0  2025-11-10 18:58:39  13.5970 -52.4500  43.381\n",
+       "1  2025-11-10 18:58:49  15.0660 -50.0240  45.813\n",
+       "2  2025-11-10 18:58:54  14.2780 -49.4810  47.677\n",
+       "3  2025-11-10 18:59:04  14.2080 -51.8015  48.995\n",
+       "4  2025-11-10 18:59:09  16.3530 -52.6850  47.745\n",
+       "5  2025-11-10 18:59:19  15.5415 -53.5625  48.327\n",
+       "6  2025-11-10 18:59:24  16.8580 -53.6960  47.160\n",
+       "7  2025-11-10 18:59:34  14.9745 -54.7510  48.480\n",
+       "8  2025-11-10 18:59:39  12.3020 -53.4330  48.631\n",
+       "9  2025-11-10 18:59:49  12.5640 -52.9805  50.130"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import mlflow\n",
+    "from io import StringIO\n",
+    "from pandas import read_csv\n",
+    "\n",
+    "if 'retrain_data.csv' in paths:\n",
+    "    artifact_path = 'retrain_data.csv'\n",
+    "elif 'train_data.csv' in paths:\n",
+    "    artifact_path = 'train_data.csv'\n",
+    "else:\n",
+    "    raise RuntimeError(\n",
+    "        f\"Could not find 'train_data.csv' or 'retrain_data.csv' for run_id '{run_id}'.\\n\"\n",
+    "    )\n",
+    "\n",
+    "# Carregar diretamente na memória como string\n",
+    "artifact_content = mlflow.artifacts.load_text(\n",
+    "    f\"runs:/{run_id}/{artifact_path}\"\n",
+    ")\n",
+    "\n",
+    "reference_df = read_csv(StringIO(artifact_content))\n",
+    "\n",
+    "reference_df.drop(columns=['timestamp.1'], inplace=True)\n",
+    "\n",
+    "reference_df['timestamp'] = to_datetime(reference_df['timestamp'])\n",
+    "reference_df['timestamp'] = reference_df['timestamp'].dt.strftime('%Y-%m-%d %H:%M:%S')\n",
+    "\n",
+    "display(reference_df)\n",
+    "\n",
+    "reference_df.to_csv(\"reference_df.csv\", index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "d375752b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas._libs.tslibs.timestamps.Timestamp'>\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/grezewave/Documents/projects/sientia/sientia-dataops-orchestrator_temporal/venv/lib/python3.11/site-packages/numpy/core/_methods.py:206: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
+      "  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n",
+      "/home/grezewave/Documents/projects/sientia/sientia-dataops-orchestrator_temporal/venv/lib/python3.11/site-packages/numpy/core/_methods.py:198: RuntimeWarning: invalid value encountered in scalar divide\n",
+      "  ret = ret.dtype.type(ret / rcount)\n",
+      "/home/grezewave/Documents/projects/sientia/sientia-dataops-orchestrator_temporal/venv/lib/python3.11/site-packages/numpy/core/_methods.py:206: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
+      "  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n",
+      "/home/grezewave/Documents/projects/sientia/sientia-dataops-orchestrator_temporal/venv/lib/python3.11/site-packages/numpy/core/_methods.py:198: RuntimeWarning: invalid value encountered in scalar divide\n",
+      "  ret = ret.dtype.type(ret / rcount)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>timestamp</th>\n",
+       "      <th>feature</th>\n",
+       "      <th>metric</th>\n",
+       "      <th>statistic</th>\n",
+       "      <th>p_value</th>\n",
+       "      <th>alert</th>\n",
+       "      <th>chunk_index</th>\n",
+       "      <th>chunk_start_date</th>\n",
+       "      <th>chunk_end_date</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2025-11-10 18:58:00+0000</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>3.000000e-01</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2025-11-10 18:58</td>\n",
+       "      <td>2025-11-10 18:58:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2025-11-10 18:59:00+0000</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.285714e-01</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2025-11-10 18:59</td>\n",
+       "      <td>2025-11-10 18:59:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2025-11-11 22:57:00+0000</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2025-11-11 22:57</td>\n",
+       "      <td>2025-11-11 22:57:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2025-11-11 22:58:00+0000</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2025-11-11 22:58</td>\n",
+       "      <td>2025-11-11 22:58:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2025-11-11 22:59:00+0000</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2025-11-11 22:59</td>\n",
+       "      <td>2025-11-11 22:59:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2025-11-11 23:00:00+0000</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2025-11-11 23:00</td>\n",
+       "      <td>2025-11-11 23:00:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2025-11-12 12:42:00+0000</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2025-11-12 12:42</td>\n",
+       "      <td>2025-11-12 12:42:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>2025-11-12 12:44:00+0000</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2025-11-12 12:44</td>\n",
+       "      <td>2025-11-12 12:44:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2025-11-10 18:58:00+0000</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>6.000000e-01</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2025-11-10 18:58</td>\n",
+       "      <td>2025-11-10 18:58:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2025-11-10 18:59:00+0000</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>2.571429e-01</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2025-11-10 18:59</td>\n",
+       "      <td>2025-11-10 18:59:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2025-11-11 22:57:00+0000</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2025-11-11 22:57</td>\n",
+       "      <td>2025-11-11 22:57:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2025-11-11 22:58:00+0000</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2025-11-11 22:58</td>\n",
+       "      <td>2025-11-11 22:58:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2025-11-11 22:59:00+0000</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2025-11-11 22:59</td>\n",
+       "      <td>2025-11-11 22:59:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2025-11-11 23:00:00+0000</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2025-11-11 23:00</td>\n",
+       "      <td>2025-11-11 23:00:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2025-11-12 12:42:00+0000</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2025-11-12 12:42</td>\n",
+       "      <td>2025-11-12 12:42:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2025-11-12 12:44:00+0000</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2025-11-12 12:44</td>\n",
+       "      <td>2025-11-12 12:44:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2025-11-10 18:58:00+0000</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>2.015043e-16</td>\n",
+       "      <td>3.748123e-17</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2025-11-10 18:58</td>\n",
+       "      <td>2025-11-10 18:58:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2025-11-10 18:59:00+0000</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>2.493220e-16</td>\n",
+       "      <td>3.998584e-17</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2025-11-10 18:59</td>\n",
+       "      <td>2025-11-10 18:59:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2025-11-11 22:57:00+0000</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.432145e-14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2025-11-11 22:57</td>\n",
+       "      <td>2025-11-11 22:57:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2025-11-11 22:58:00+0000</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.234840e-14</td>\n",
+       "      <td>2.299811e-15</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2025-11-11 22:58</td>\n",
+       "      <td>2025-11-11 22:58:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>2025-11-11 22:59:00+0000</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>7.944109e-15</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>True</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2025-11-11 22:59</td>\n",
+       "      <td>2025-11-11 22:59:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>2025-11-11 23:00:00+0000</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>7.524768e-15</td>\n",
+       "      <td>4.193410e-16</td>\n",
+       "      <td>True</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2025-11-11 23:00</td>\n",
+       "      <td>2025-11-11 23:00:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>2025-11-12 12:42:00+0000</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.004859e-14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2025-11-12 12:42</td>\n",
+       "      <td>2025-11-12 12:42:59.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>2025-11-12 12:44:00+0000</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.004859e-14</td>\n",
+       "      <td>0.000000e+00</td>\n",
+       "      <td>True</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2025-11-12 12:44</td>\n",
+       "      <td>2025-11-12 12:44:59.999999999</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                   timestamp       feature              metric     statistic  \\\n",
+       "0   2025-11-10 18:58:00+0000       Counter  kolmogorov_smirnov  3.000000e-01   \n",
+       "1   2025-11-10 18:59:00+0000       Counter  kolmogorov_smirnov  1.285714e-01   \n",
+       "2   2025-11-11 22:57:00+0000       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "3   2025-11-11 22:58:00+0000       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "4   2025-11-11 22:59:00+0000       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "5   2025-11-11 23:00:00+0000       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "6   2025-11-12 12:42:00+0000       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "7   2025-11-12 12:44:00+0000       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "8   2025-11-10 18:58:00+0000       Rollout  kolmogorov_smirnov  6.000000e-01   \n",
+       "9   2025-11-10 18:59:00+0000       Rollout  kolmogorov_smirnov  2.571429e-01   \n",
+       "10  2025-11-11 22:57:00+0000       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "11  2025-11-11 22:58:00+0000       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "12  2025-11-11 22:59:00+0000       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "13  2025-11-11 23:00:00+0000       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "14  2025-11-12 12:42:00+0000       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "15  2025-11-12 12:44:00+0000       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "16  2025-11-10 18:58:00+0000  multivariate        multivariate  2.015043e-16   \n",
+       "17  2025-11-10 18:59:00+0000  multivariate        multivariate  2.493220e-16   \n",
+       "18  2025-11-11 22:57:00+0000  multivariate        multivariate  1.432145e-14   \n",
+       "19  2025-11-11 22:58:00+0000  multivariate        multivariate  1.234840e-14   \n",
+       "20  2025-11-11 22:59:00+0000  multivariate        multivariate  7.944109e-15   \n",
+       "21  2025-11-11 23:00:00+0000  multivariate        multivariate  7.524768e-15   \n",
+       "22  2025-11-12 12:42:00+0000  multivariate        multivariate  1.004859e-14   \n",
+       "23  2025-11-12 12:44:00+0000  multivariate        multivariate  1.004859e-14   \n",
+       "\n",
+       "         p_value  alert  chunk_index  chunk_start_date  \\\n",
+       "0            NaN  False            0  2025-11-10 18:58   \n",
+       "1            NaN  False            1  2025-11-10 18:59   \n",
+       "2            NaN   True            0  2025-11-11 22:57   \n",
+       "3            NaN   True            1  2025-11-11 22:58   \n",
+       "4            NaN   True            2  2025-11-11 22:59   \n",
+       "5            NaN   True            3  2025-11-11 23:00   \n",
+       "6            NaN   True            4  2025-11-12 12:42   \n",
+       "7            NaN   True            5  2025-11-12 12:44   \n",
+       "8            NaN  False            0  2025-11-10 18:58   \n",
+       "9            NaN  False            1  2025-11-10 18:59   \n",
+       "10           NaN   True            0  2025-11-11 22:57   \n",
+       "11           NaN   True            1  2025-11-11 22:58   \n",
+       "12           NaN   True            2  2025-11-11 22:59   \n",
+       "13           NaN   True            3  2025-11-11 23:00   \n",
+       "14           NaN   True            4  2025-11-12 12:42   \n",
+       "15           NaN   True            5  2025-11-12 12:44   \n",
+       "16  3.748123e-17  False            0  2025-11-10 18:58   \n",
+       "17  3.998584e-17  False            1  2025-11-10 18:59   \n",
+       "18           NaN   True            0  2025-11-11 22:57   \n",
+       "19  2.299811e-15   True            1  2025-11-11 22:58   \n",
+       "20  0.000000e+00   True            2  2025-11-11 22:59   \n",
+       "21  4.193410e-16   True            3  2025-11-11 23:00   \n",
+       "22           NaN   True            4  2025-11-12 12:42   \n",
+       "23  0.000000e+00   True            5  2025-11-12 12:44   \n",
+       "\n",
+       "                  chunk_end_date  \n",
+       "0  2025-11-10 18:58:59.999999999  \n",
+       "1  2025-11-10 18:59:59.999999999  \n",
+       "2  2025-11-11 22:57:59.999999999  \n",
+       "3  2025-11-11 22:58:59.999999999  \n",
+       "4  2025-11-11 22:59:59.999999999  \n",
+       "5  2025-11-11 23:00:59.999999999  \n",
+       "6  2025-11-12 12:42:59.999999999  \n",
+       "7  2025-11-12 12:44:59.999999999  \n",
+       "8  2025-11-10 18:58:59.999999999  \n",
+       "9  2025-11-10 18:59:59.999999999  \n",
+       "10 2025-11-11 22:57:59.999999999  \n",
+       "11 2025-11-11 22:58:59.999999999  \n",
+       "12 2025-11-11 22:59:59.999999999  \n",
+       "13 2025-11-11 23:00:59.999999999  \n",
+       "14 2025-11-12 12:42:59.999999999  \n",
+       "15 2025-11-12 12:44:59.999999999  \n",
+       "16 2025-11-10 18:58:59.999999999  \n",
+       "17 2025-11-10 18:59:59.999999999  \n",
+       "18 2025-11-11 22:57:59.999999999  \n",
+       "19 2025-11-11 22:58:59.999999999  \n",
+       "20 2025-11-11 22:59:59.999999999  \n",
+       "21 2025-11-11 23:00:59.999999999  \n",
+       "22 2025-11-12 12:42:59.999999999  \n",
+       "23 2025-11-12 12:44:59.999999999  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "\n",
+    "from sientia_do.temporal.constants import DATETIME_FORMAT_WITH_TZ\n",
+    "\n",
+    "\n",
+    "univariate_drift = model.detect_univariate_drift(\n",
+    "    reference_df=reference_df,\n",
+    "    analysis_df=data,\n",
+    "    features=config['features'],\n",
+    "    timestamp_col=timestamp_col,\n",
+    "    methods=drift_methods,\n",
+    "    chunk_period=\"min\"\n",
+    ")\n",
+    "multivariate_drift = model.detect_multivariate_drift(\n",
+    "    reference_df=reference_df,\n",
+    "    analysis_df=data,\n",
+    "    features=config['features'],\n",
+    "    timestamp_col=timestamp_col,\n",
+    "    chunk_period=\"min\"\n",
+    ")\n",
+    "\n",
+    "drift = model.get_drift_metrics_dataframe(\n",
+    "    univariate_drift=univariate_drift,\n",
+    "    multivariate_drift=multivariate_drift\n",
+    ")\n",
+    "drift.drop_duplicates(subset=[\"timestamp\", \"feature\", \"metric\"], inplace=True, keep=\"first\")\n",
+    "drift.reset_index(drop=True, inplace=True)\n",
+    "\n",
+    "drift['timestamp'] = to_datetime(drift['timestamp'])\n",
+    "print(type(drift['timestamp'].iloc[0]))\n",
+    "\n",
+    "# Add timezone UTC to timestamp\n",
+    "drift['timestamp'] = drift['timestamp'].dt.tz_localize('UTC')\n",
+    "drift['timestamp'] = drift['timestamp'].dt.strftime(DATETIME_FORMAT_WITH_TZ)\n",
+    "\n",
+    "display(drift)\n",
+    "drift.to_csv(\"drift.csv\", index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "d30f6475",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>timestamp</th>\n",
+       "      <th>feature</th>\n",
+       "      <th>metric</th>\n",
+       "      <th>statistic</th>\n",
+       "      <th>p_value</th>\n",
+       "      <th>alert</th>\n",
+       "      <th>chunk_index</th>\n",
+       "      <th>chunk_start_date</th>\n",
+       "      <th>chunk_end_date</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2025-11-11 11:55:18</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2025-11-11 11:55:18</td>\n",
+       "      <td>2025-11-11 11:55:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>2025-11-11 11:55:48</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2025-11-11 11:55:48</td>\n",
+       "      <td>2025-11-11 11:55:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>2025-11-11 11:56:18</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2025-11-11 11:56:18</td>\n",
+       "      <td>2025-11-11 11:56:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>2025-11-11 11:56:48</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2025-11-11 11:56:48</td>\n",
+       "      <td>2025-11-11 11:56:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2025-11-11 11:57:18</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2025-11-11 11:57:18</td>\n",
+       "      <td>2025-11-11 11:57:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>2025-11-11 11:57:48</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2025-11-11 11:57:48</td>\n",
+       "      <td>2025-11-11 11:57:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>2025-11-11 11:58:18</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2025-11-11 11:58:18</td>\n",
+       "      <td>2025-11-11 11:58:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2025-11-11 11:58:48</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2025-11-11 11:58:48</td>\n",
+       "      <td>2025-11-11 11:58:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>2025-11-11 11:59:18</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>8</td>\n",
+       "      <td>2025-11-11 11:59:18</td>\n",
+       "      <td>2025-11-11 11:59:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>2025-11-11 11:59:48</td>\n",
+       "      <td>Counter</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>9</td>\n",
+       "      <td>2025-11-11 11:59:48</td>\n",
+       "      <td>2025-11-11 11:59:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>2025-11-11 11:55:18</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2025-11-11 11:55:18</td>\n",
+       "      <td>2025-11-11 11:55:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>2025-11-11 11:55:48</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2025-11-11 11:55:48</td>\n",
+       "      <td>2025-11-11 11:55:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>2025-11-11 11:56:18</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2025-11-11 11:56:18</td>\n",
+       "      <td>2025-11-11 11:56:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>2025-11-11 11:56:48</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2025-11-11 11:56:48</td>\n",
+       "      <td>2025-11-11 11:56:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>2025-11-11 11:57:18</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2025-11-11 11:57:18</td>\n",
+       "      <td>2025-11-11 11:57:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>2025-11-11 11:57:48</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2025-11-11 11:57:48</td>\n",
+       "      <td>2025-11-11 11:57:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>2025-11-11 11:58:18</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2025-11-11 11:58:18</td>\n",
+       "      <td>2025-11-11 11:58:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>2025-11-11 11:58:48</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2025-11-11 11:58:48</td>\n",
+       "      <td>2025-11-11 11:58:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>2025-11-11 11:59:18</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>8</td>\n",
+       "      <td>2025-11-11 11:59:18</td>\n",
+       "      <td>2025-11-11 11:59:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>2025-11-11 11:59:48</td>\n",
+       "      <td>Rollout</td>\n",
+       "      <td>kolmogorov_smirnov</td>\n",
+       "      <td>1.000000e+00</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>9</td>\n",
+       "      <td>2025-11-11 11:59:48</td>\n",
+       "      <td>2025-11-11 11:59:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>2025-11-11 11:55:18</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.517720e-14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2025-11-11 11:55:18</td>\n",
+       "      <td>2025-11-11 11:55:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>2025-11-11 11:55:48</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.588822e-14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2025-11-11 11:55:48</td>\n",
+       "      <td>2025-11-11 11:55:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>2025-11-11 11:56:18</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.432145e-14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2025-11-11 11:56:18</td>\n",
+       "      <td>2025-11-11 11:56:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>2025-11-11 11:56:48</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.421085e-14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2025-11-11 11:56:48</td>\n",
+       "      <td>2025-11-11 11:56:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>54</th>\n",
+       "      <td>2025-11-11 11:57:18</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.421085e-14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>4</td>\n",
+       "      <td>2025-11-11 11:57:18</td>\n",
+       "      <td>2025-11-11 11:57:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>55</th>\n",
+       "      <td>2025-11-11 11:57:48</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.776357e-15</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>5</td>\n",
+       "      <td>2025-11-11 11:57:48</td>\n",
+       "      <td>2025-11-11 11:57:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>56</th>\n",
+       "      <td>2025-11-11 11:58:18</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>7.324107e-15</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2025-11-11 11:58:18</td>\n",
+       "      <td>2025-11-11 11:58:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57</th>\n",
+       "      <td>2025-11-11 11:58:48</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.464821e-14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2025-11-11 11:58:48</td>\n",
+       "      <td>2025-11-11 11:58:48.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>58</th>\n",
+       "      <td>2025-11-11 11:59:18</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.551137e-14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>8</td>\n",
+       "      <td>2025-11-11 11:59:18</td>\n",
+       "      <td>2025-11-11 11:59:18.999999999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>59</th>\n",
+       "      <td>2025-11-11 11:59:48</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>multivariate</td>\n",
+       "      <td>1.427317e-14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>True</td>\n",
+       "      <td>9</td>\n",
+       "      <td>2025-11-11 11:59:48</td>\n",
+       "      <td>2025-11-11 11:59:48.999999999</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              timestamp       feature              metric     statistic  \\\n",
+       "10  2025-11-11 11:55:18       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "11  2025-11-11 11:55:48       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "12  2025-11-11 11:56:18       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "13  2025-11-11 11:56:48       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "14  2025-11-11 11:57:18       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "15  2025-11-11 11:57:48       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "16  2025-11-11 11:58:18       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "17  2025-11-11 11:58:48       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "18  2025-11-11 11:59:18       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "19  2025-11-11 11:59:48       Counter  kolmogorov_smirnov  1.000000e+00   \n",
+       "30  2025-11-11 11:55:18       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "31  2025-11-11 11:55:48       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "32  2025-11-11 11:56:18       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "33  2025-11-11 11:56:48       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "34  2025-11-11 11:57:18       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "35  2025-11-11 11:57:48       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "36  2025-11-11 11:58:18       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "37  2025-11-11 11:58:48       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "38  2025-11-11 11:59:18       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "39  2025-11-11 11:59:48       Rollout  kolmogorov_smirnov  1.000000e+00   \n",
+       "50  2025-11-11 11:55:18  multivariate        multivariate  1.517720e-14   \n",
+       "51  2025-11-11 11:55:48  multivariate        multivariate  1.588822e-14   \n",
+       "52  2025-11-11 11:56:18  multivariate        multivariate  1.432145e-14   \n",
+       "53  2025-11-11 11:56:48  multivariate        multivariate  1.421085e-14   \n",
+       "54  2025-11-11 11:57:18  multivariate        multivariate  1.421085e-14   \n",
+       "55  2025-11-11 11:57:48  multivariate        multivariate  1.776357e-15   \n",
+       "56  2025-11-11 11:58:18  multivariate        multivariate  7.324107e-15   \n",
+       "57  2025-11-11 11:58:48  multivariate        multivariate  1.464821e-14   \n",
+       "58  2025-11-11 11:59:18  multivariate        multivariate  1.551137e-14   \n",
+       "59  2025-11-11 11:59:48  multivariate        multivariate  1.427317e-14   \n",
+       "\n",
+       "   p_value  alert  chunk_index     chunk_start_date  \\\n",
+       "10    None  False            0  2025-11-11 11:55:18   \n",
+       "11    None  False            1  2025-11-11 11:55:48   \n",
+       "12    None  False            2  2025-11-11 11:56:18   \n",
+       "13    None  False            3  2025-11-11 11:56:48   \n",
+       "14    None  False            4  2025-11-11 11:57:18   \n",
+       "15    None  False            5  2025-11-11 11:57:48   \n",
+       "16    None  False            6  2025-11-11 11:58:18   \n",
+       "17    None  False            7  2025-11-11 11:58:48   \n",
+       "18    None  False            8  2025-11-11 11:59:18   \n",
+       "19    None  False            9  2025-11-11 11:59:48   \n",
+       "30    None  False            0  2025-11-11 11:55:18   \n",
+       "31    None  False            1  2025-11-11 11:55:48   \n",
+       "32    None  False            2  2025-11-11 11:56:18   \n",
+       "33    None  False            3  2025-11-11 11:56:48   \n",
+       "34    None  False            4  2025-11-11 11:57:18   \n",
+       "35    None  False            5  2025-11-11 11:57:48   \n",
+       "36    None  False            6  2025-11-11 11:58:18   \n",
+       "37    None  False            7  2025-11-11 11:58:48   \n",
+       "38    None  False            8  2025-11-11 11:59:18   \n",
+       "39    None  False            9  2025-11-11 11:59:48   \n",
+       "50     NaN   True            0  2025-11-11 11:55:18   \n",
+       "51     NaN   True            1  2025-11-11 11:55:48   \n",
+       "52     NaN   True            2  2025-11-11 11:56:18   \n",
+       "53     NaN   True            3  2025-11-11 11:56:48   \n",
+       "54     NaN   True            4  2025-11-11 11:57:18   \n",
+       "55     NaN   True            5  2025-11-11 11:57:48   \n",
+       "56     NaN   True            6  2025-11-11 11:58:18   \n",
+       "57     NaN   True            7  2025-11-11 11:58:48   \n",
+       "58     NaN   True            8  2025-11-11 11:59:18   \n",
+       "59     NaN   True            9  2025-11-11 11:59:48   \n",
+       "\n",
+       "                  chunk_end_date  \n",
+       "10 2025-11-11 11:55:18.999999999  \n",
+       "11 2025-11-11 11:55:48.999999999  \n",
+       "12 2025-11-11 11:56:18.999999999  \n",
+       "13 2025-11-11 11:56:48.999999999  \n",
+       "14 2025-11-11 11:57:18.999999999  \n",
+       "15 2025-11-11 11:57:48.999999999  \n",
+       "16 2025-11-11 11:58:18.999999999  \n",
+       "17 2025-11-11 11:58:48.999999999  \n",
+       "18 2025-11-11 11:59:18.999999999  \n",
+       "19 2025-11-11 11:59:48.999999999  \n",
+       "30 2025-11-11 11:55:18.999999999  \n",
+       "31 2025-11-11 11:55:48.999999999  \n",
+       "32 2025-11-11 11:56:18.999999999  \n",
+       "33 2025-11-11 11:56:48.999999999  \n",
+       "34 2025-11-11 11:57:18.999999999  \n",
+       "35 2025-11-11 11:57:48.999999999  \n",
+       "36 2025-11-11 11:58:18.999999999  \n",
+       "37 2025-11-11 11:58:48.999999999  \n",
+       "38 2025-11-11 11:59:18.999999999  \n",
+       "39 2025-11-11 11:59:48.999999999  \n",
+       "50 2025-11-11 11:55:18.999999999  \n",
+       "51 2025-11-11 11:55:48.999999999  \n",
+       "52 2025-11-11 11:56:18.999999999  \n",
+       "53 2025-11-11 11:56:48.999999999  \n",
+       "54 2025-11-11 11:57:18.999999999  \n",
+       "55 2025-11-11 11:57:48.999999999  \n",
+       "56 2025-11-11 11:58:18.999999999  \n",
+       "57 2025-11-11 11:58:48.999999999  \n",
+       "58 2025-11-11 11:59:18.999999999  \n",
+       "59 2025-11-11 11:59:48.999999999  "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# drop rows of drift with timestamp in reference data but not in analysis data\n",
+    "drift_filtered = drift[drift['timestamp'].isin(data['timestamp'])]\n",
+    "display(drift_filtered)\n",
+    "\n",
+    "drift_filtered.to_csv(\"drift_filtered.csv\", index=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "70671022",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "Target column 'Square' not found in DataFrames",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
+      "\u001b[31mValueError\u001b[39m                                Traceback (most recent call last)",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[36]\u001b[39m\u001b[32m, line 6\u001b[39m\n\u001b[32m      3\u001b[39m \u001b[38;5;66;03m# rename column square to prediction\u001b[39;00m\n\u001b[32m      4\u001b[39m performance_reference.rename(columns={\u001b[33m'\u001b[39m\u001b[33mSquare\u001b[39m\u001b[33m'\u001b[39m: \u001b[33m'\u001b[39m\u001b[33mprediction\u001b[39m\u001b[33m'\u001b[39m}, inplace=\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[32m----> \u001b[39m\u001b[32m6\u001b[39m real_performance = \u001b[43mmodel\u001b[49m\u001b[43m.\u001b[49m\u001b[43mcalculate_performance\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m      7\u001b[39m \u001b[43m    \u001b[49m\u001b[43mreference_df\u001b[49m\u001b[43m=\u001b[49m\u001b[43mperformance_reference\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m      8\u001b[39m \u001b[43m    \u001b[49m\u001b[43manalysis_df\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m      9\u001b[39m \u001b[43m    \u001b[49m\u001b[43mtarget_col\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtarget_col\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     10\u001b[39m \u001b[43m    \u001b[49m\u001b[43mtimestamp_col\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimestamp_col\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     11\u001b[39m \u001b[43m    \u001b[49m\u001b[43mchunk_period\u001b[49m\u001b[43m=\u001b[49m\u001b[43mchunk_period\u001b[49m\n\u001b[32m     12\u001b[39m \u001b[43m)\u001b[49m\n\u001b[32m     14\u001b[39m metrics_df = model.get_calculated_metrics_dataframe(real_performance)\n\u001b[32m     15\u001b[39m display(metrics_df)\n",
+      "\u001b[36mFile \u001b[39m\u001b[32m~/Documents/projects/sientia/sientia-dataops-orchestrator_temporal/venv/lib/python3.11/site-packages/sientia/ModelAnalysis.py:397\u001b[39m, in \u001b[36mModelAnalysis.calculate_performance\u001b[39m\u001b[34m(self, reference_df, analysis_df, target_col, timestamp_col, metrics, chunk_period)\u001b[39m\n\u001b[32m    395\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(DATAFRAMES_EMPTY_ERROR)\n\u001b[32m    396\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m target_col \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m reference_df.columns \u001b[38;5;129;01mor\u001b[39;00m target_col \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m analysis_df.columns:\n\u001b[32m--> \u001b[39m\u001b[32m397\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mTarget column \u001b[39m\u001b[33m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtarget_col\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m'\u001b[39m\u001b[33m not found in DataFrames\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m    398\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m timestamp_col \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m reference_df.columns \u001b[38;5;129;01mor\u001b[39;00m timestamp_col \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m analysis_df.columns:\n\u001b[32m    399\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mTimestamp column \u001b[39m\u001b[33m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtimestamp_col\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m'\u001b[39m\u001b[33m not found in DataFrames\u001b[39m\u001b[33m\"\u001b[39m)\n",
+      "\u001b[31mValueError\u001b[39m: Target column 'Square' not found in DataFrames"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "real_performance = model.calculate_performance(\n",
+    "    reference_df=data,\n",
+    "    analysis_df=data,\n",
+    "    target_col=target_col,\n",
+    "    timestamp_col=timestamp_col,\n",
+    "    chunk_period=chunk_period\n",
+    ")\n",
+    "\n",
+    "metrics_df = model.get_calculated_metrics_dataframe(real_performance)\n",
+    "display(metrics_df)\n",
+    "\n",
+    "metrics_df.to_csv(\"metrics_df.csv\", index=False)"
+   ]
   }
  ],
  "metadata": {
diff --git a/tests/orchestrator/activities/test_formatters.py b/tests/orchestrator/activities/test_formatters.py
index 223227e..51b0e08 100644
--- a/tests/orchestrator/activities/test_formatters.py
+++ b/tests/orchestrator/activities/test_formatters.py
@@ -44,8 +44,21 @@ metadata = {
     'orchestrator.activities.formatters.minimal_retrain',
     return_value={'test_minimal_retrain': 'test_minimal_retrain'},
 )
+@patch(
+    'orchestrator.activities.formatters.drift',
+    return_value={'test_drift': 'test_drift'},
+)
+@patch(
+    'orchestrator.activities.formatters.simple_metrics',
+    return_value={'test_simple_metrics': 'test_simple_metrics'},
+)
 async def test_process_schedules(
-    mock_minimal_retrain, mock_predictions_batch, mock_scouter, formatters
+    mock_simple_metrics,
+    mock_drift,
+    mock_minimal_retrain,
+    mock_predictions_batch,
+    mock_scouter,
+    formatters,
 ):
     input_data = {
         'pipelines': [
@@ -70,6 +83,20 @@ async def test_process_schedules(
                 'model_id': 'test_model_id',
                 'updated_at': '2021-01-03',
             },
+            {
+                'schedule_name': 'test_schedule_name4',
+                'workflow_type': 'drift',
+                'model_name': 'test_model_name',
+                'model_id': 'test_model_id',
+                'updated_at': '2021-01-04',
+            },
+            {
+                'schedule_name': 'test_schedule_name5',
+                'workflow_type': 'simple_metrics',
+                'model_name': 'test_model_name',
+                'model_id': 'test_model_id',
+                'updated_at': '2021-01-05',
+            },
         ]
     }
 
@@ -88,11 +115,22 @@ async def test_process_schedules(
                 'test_minimal_retrain': 'test_minimal_retrain',
                 'updated_at': '2021-01-03',
             },
+            'test_schedule_name4': {
+                'test_drift': 'test_drift',
+                'updated_at': '2021-01-04',
+            },
+            'test_schedule_name5': {
+                'test_simple_metrics': 'test_simple_metrics',
+                'updated_at': '2021-01-05',
+            },
         },
     }
 
     mock_scouter.assert_called_once_with(input_data['pipelines'][0])
     mock_predictions_batch.assert_called_once_with(input_data['pipelines'][1])
+    mock_minimal_retrain.assert_called_once_with(input_data['pipelines'][2])
+    mock_drift.assert_called_once_with(input_data['pipelines'][3])
+    mock_simple_metrics.assert_called_once_with(input_data['pipelines'][4])
 
 
 @mark.asyncio
diff --git a/tests/orchestrator/activities/test_temporal_manager.py b/tests/orchestrator/activities/test_temporal_manager.py
index e3add38..f5a7c13 100644
--- a/tests/orchestrator/activities/test_temporal_manager.py
+++ b/tests/orchestrator/activities/test_temporal_manager.py
@@ -18,8 +18,7 @@ metadata = {
 
 
 @fixture
-@patch('orchestrator.activities.temporal_manager.Client.connect')
-def temporal_manager(connect_mock):
+def temporal_manager():
     temporal_manager = TemporalManager(
         host='localhost:7233',
         scouter_namespace='scouter',
diff --git a/tests/orchestrator/utils/test_orchestrator_functions.py b/tests/orchestrator/utils/test_orchestrator_functions.py
index f74a936..4db42a8 100644
--- a/tests/orchestrator/utils/test_orchestrator_functions.py
+++ b/tests/orchestrator/utils/test_orchestrator_functions.py
@@ -3,12 +3,14 @@ from unittest.mock import call, patch
 from orchestrator.utils.orchestrator_functions import (
     build_tag_config,
     common_config,
+    drift,
     gather_read_tags,
     minimal_retrain,
     overlap_filter_config,
     predictions_batch,
     process_path_priority,
     scouter,
+    simple_metrics,
 )
 
 
@@ -35,6 +37,67 @@ def test_common_config():
     assert result == expected
 
 
+def test_drift():
+    config = {
+        'workflow_type': 'drift',
+        'schedule_name': 'test_schedule',
+        'model_id': 'test_model_id',
+        'model': {'name': 'test_model_name', 'model_config': {'test_config': 'test_config'}},
+        'interval_minutes': 120,
+        'drift_metrics': ['kolmogorov_smirnov', 'jensen_shannon'],
+    }
+    result = drift(config)
+    expected = {
+        'workflow_type': 'drift',
+        'schedule_name': 'test_schedule',
+        'frequency': '1m',
+        'offset': '0m',
+        'max_retry_policy': 1,
+        'model_id': 'test_model_id',
+        'model_name': 'test_model_name',
+        'model_config': {'test_config': 'test_config'},
+        'schema': 'sientia_data',
+        'source_table_name': 'laborious_data',
+        'target_table_name': 'drift_metrics',
+        'interval': 120,
+        'drift_metrics': ['kolmogorov_smirnov', 'jensen_shannon'],
+        'execution_timeout_seconds': 300,
+        'task_timeout_seconds': 300,
+    }
+    assert result == expected
+
+
+def test_simple_metrics():
+    config = {
+        'workflow_type': 'simple_metrics',
+        'schedule_name': 'test_schedule',
+        'model_id': 'test_model_id',
+        'model': {'name': 'test_model_name', 'model_config': {'test_config': 'test_config'}},
+        'interval_minutes': 120,
+        'metrics': ['rmse', 'mse'],
+    }
+    result = simple_metrics(config)
+    expected = {
+        'workflow_type': 'simple_metrics',
+        'schedule_name': 'test_schedule',
+        'frequency': '1m',
+        'offset': '0m',
+        'max_retry_policy': 1,
+        'model_id': 'test_model_id',
+        'model_name': 'test_model_name',
+        'model_config': {'test_config': 'test_config'},
+        'schema': 'sientia_data',
+        'predictions_table_name': 'predictions',
+        'data_table_name': 'laborious_data',
+        'target_table_name': 'simple_metrics',
+        'interval_minutes': 120,
+        'metrics': ['rmse', 'mse'],
+        'execution_timeout_seconds': 300,
+        'task_timeout_seconds': 300,
+    }
+    assert result == expected
+
+
 def test_minimal_retrain():
     config = {
         'workflow_type': 'minimal_retrain',
@@ -175,6 +238,8 @@ def test_predictions_batch(mock_process_path_priority, mock_overlap_filter_confi
         'query': 'test_query',
         'schema': 'sientia_data',
         'table_name': 'predictions',
+        'save_transform': True,
+        'transform_table_name': 'transformed_data',
         'retention_time': 60 * 60,
         'opc_output_config': {
             'test_server_id': {
diff --git a/values.yaml b/values.yaml
index 88f5342..a40c8c4 100644
--- a/values.yaml
+++ b/values.yaml
@@ -11,7 +11,7 @@ image:
   # This sets the pull policy for images.
   pullPolicy: Always
   # Overrides the image tag whose default is the chart appVersion.
-  tag: "0.5.0"
+  tag: "0.5.2"
 
 # This is for the secrets for pulling an image from a private repository more information can be found here: https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/
 imagePullSecrets:
@@ -151,7 +151,7 @@ env:
   - name: GITHUB_REPO_URL
     value: "git@github.com:Aignosi/sientia-dataops-orchestrator_temporal.git"
   - name: GITHUB_BRANCH
-    value: "feature/SIENTIAPDE-1325-adicionar-metricas-especificas-de-operacoes-externas"
+    value: "feature/SIENTIAPDE-1273"
   - name: PYTHON_APP
     value: "orchestrator.worker.worker"
 
@@ -237,7 +237,7 @@ ssh:
 
 # kubectl create secret docker-registry docker-hub-secret --namespace sientia --docker-server=http://aignosi.azurecr.io --docker-username=aignosi --docker-password=5I5zpQ6sRaHqX1hD3dr+2mo647yO3FRc359/wu6gsP+ACRDRz5mp
 
-# helm upgrade --install sientia-orchestrator-worker sientia/sientia-module -n sientia --create-namespace -f ./values.yaml --version 0.5.0
+# helm upgrade --install sientia-orchestrator-worker sientia/sientia-module -n sientia --create-namespace -f ./values.yaml --version 0.6.0
 
 # kubectl create secret generic git-ssh-key-sientia-orchestrator-worker \
 #   --namespace sientia \