Backend:
- Updated the `StartSparkStreamer` function call to send `Analyzer_uuid` as the key for messages produced on the Kafka topic.
- Updated the `SparkStream` definition to receive the key and added the key to the `streamwriter` object.

Frontend:
- Integrated APScheduler to manage `StreamListener`.
- Added `ResponseListener` to consume messages from the `analytics_response_topic` and process them.
- Added APScheduler to manage StreamListener.
- Added "ResponseListener" to consumer messages from analytics response_topic and process it.

Proto:
- Added `Duration_s` field to the proto file.

Frontend:
- Added `SelectAnalyzer` logic.
- Improved message formatting in the `create_analyzer_filter()` function.
- Added a test case: `test_SelectAnalytics`.

Backend:
- Renamed the `RunSparkStreamer` method to `StartSparkStreamer`.
- Updated the `StartRequestListener` method to return `(thread, stop_event)`.
- Added a `StopRequestListener` method to stop the listener.

Database:
- Added the `select_with_filter` method with actual logic implementation.
- Updated the `ConvertRowToAnalyzer` method to correctly read the `operation_mode` ENUM value.

- Updated the position of the `stop_event` parameter.
- Added confirmation for pySpark checkpoint deletion.
- Added a PySpark termination script to handle the `StopCollector` event.

- Thresholds, window_size, window_slider is added in Frontend and Backend.

- UNSPECIFIED option added in the "AnalyzerOperationMode" enum as a best practice.
- In SparkStreamer, changed the thresholds parameter from optional to compulsory.

- Updated function names.

- In the BackendService.py:
     + Updated SparkStreamer call with new parameters.
- In SparkStreaming.py:
   + Added 'GetAggregerations' and 'ApplyThresholds' methods
   + Added 'window_size', 'win_slide_duration', 'time_stamp_col' and 'thresholds' parameters.
- Added new messages.
- Updated the 'RunSparkStreamer' call wth new parameters.

- SparkStreamer write Stream to Kafka topic ANALYTICS_RESPONSE.

- Added Kafka Request Listener to listen for requests from the Analytics Frontend.
- Updated `SparkStreamer.py` to consume and process streams from VALUE topics, and further filter rows based on KPIs in the `input_kpis` list.
- Updated the frontend TOPIC from `VALUE` to `ANALYTICS_REQUEST`.
- Updated messages to keep the KPI UUID consistent with the one generated by the Telemetry Backend service.

- Added CRDB secret.
- Added test script.
- Added `main` and `__init__.py` files.
- Added Backend Service file.
- Added Spark Streamer file (successfully consuming streams from Kafka Topics).
- Added Tests folder and files.
- Added requirements file.
- Added ANALYTICS Kafka topics in `common.tools.kafka.variables` file.