(CTTC) New Analytics Component

See merge request !261

Merge branch 'develop' of ssh://gifrerenom_labs.etsi.org/tfs/controller into feat/188-cttc-new-analytics-component

- Corrected Liveness/Readiness probes

Deployment Script
- Analytics is added in new montioring component to be deployed with TFS.
- condition is added in analytics component TFS deployment script.
- Analytics show logs files are added.
Manifest
- modifed KAFKA_ADVERTISED_LISTENERS with internal kafka service address in kafka.yml
- analyticsservice.yml added.
Analytics
- grpc service is added in backend
- Docker file for backend and frontend is added.
- main file is updaed
- small changes in requirements.in files
Kafka Variables
- get_kafka_address method logic is updated.

Resolve "Re-designing of Telemetry"

See merge request !258

Merge branch 'develop' of ssh://gifrerenom_labs.etsi.org/tfs/controller into feat/179-re-designing-of-telemetry

Resolve "KPI Management Enhancements"

See merge request !255

Merge branch 'develop' of ssh://gifrerenom_labs.etsi.org/tfs/controller into feat/178-kpi-management-enhancements

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.

Resolve "(TID) Add inventory NBI to WebUI"

See merge request !251

Merge branch 'feat/tid-add-inventory-nbi-to-webui' of ssh://gifrerenom_labs.etsi.org/tfs/controller into feat/173-tid-add-inventory-nbi-to-webui

Merge branch 'develop' of ssh://gifrerenom_labs.etsi.org/tfs/controller into feat/tid-add-inventory-nbi-to-webui

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.

- Reverted an unintentional change made in the `tfs.sh` file.

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

**Frontend:**
- Deleted irrelevant lines.

**Backend:**
- Added `delete_db_row_by_id` in the Stop Collector method.

**Backend:**
- Added a dictionary to manage running analyzers.
- Implemented logic to manage running analyzers.
- Added the `TerminateAnalyzerBackend` method to handle analyzer termination.

**Frontend:**
- Modified and invoked the `PublishStopRequestOnKafka` method.

- 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.

- parameters col added in DB
- parameters field added in Analytics.proto
- AnalyzerModel class methods changes
- changes in messages file

- 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 the missing `map<string, string>` in the `analytics_frontend.proto` file.
- Removed `pyspark` and `java` from the `requirements.in` file, as they are not required for the Frontend.

- 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.

- Created the Analytic Engine, Model, and DB files.
- Added the DB connection.
- Added `add_row_to_db` in `StartCollector`.
- Added `delete_db_row_by_id` in `StopCollector`.
- Improved message formatting.
- Added a DB test file.

- Actul logic is added in StartAnalyzer method.
- Actual logic is added in StopAnalyzer method.
- Improvements in message formats.