Resolve "Update license headers for Release 4"

Closes #220 (closed)

src/analytics/README.md

@@ -4,29 +4,25 @@
 The following requirements should be fulfilled before the execuation of Analytics service.
 
 1. A virtual enviornment exist with all the required packages listed in [requirements.in](https://labs.etsi.org/rep/tfs/controller/-/blob/develop/src/analytics/frontend/requirements.in) sucessfully  installed.
-2. Verify the creation of required database and table. The 
-[Analytics DB test](https://labs.etsi.org/rep/tfs/controller/-/blob/develop/src/analytics/tests/test_analytics_db.py) python file lists the functions to create tables and the database.
-3. The Analytics backend service should be running.
-
-4. All required Kafka topics must exist. Call `create_all_topics` from the [Kafka class](https://labs.etsi.org/rep/tfs/controller/-/blob/develop/src/common/tools/kafka/Variables.py) to create any topics that do not already exist.
+2. The Analytics backend service should be running.
+3. All required Kafka topics must exist. Call `create_all_topics` from the [Kafka class](https://labs.etsi.org/rep/tfs/controller/-/blob/develop/src/common/tools/kafka/Variables.py) to create any topics that do not already exist.
 ```
 from common.tools.kafka.Variables import KafkaTopic
 KafkaTopic.create_all_topics()
 ```
 
-5. There will be an input stream on the Kafka topic that the Spark Streamer will consume and apply a defined thresholds.
+4. There will be an input stream on the Kafka topic that the Streamer class will consume and apply a defined thresholds.
 - A JSON encoded string should be generated in the following format:
 ```
 '{"time_stamp": "2024-09-03T12:36:26Z", "kpi_id": "6e22f180-ba28-4641-b190-2287bf448888", "kpi_value": 44.22}'
 ```
-- `kpi_value` should be float or int.
 - The Kafka producer key should be the UUID of the Analyzer used when creating it.
-- Use the following Kafka topic to generate the stream: `KafkaTopic.ANALYTICS_RESPONSE.value`.
+- Generate the stream on the following Kafka topic: `KafkaTopic.ANALYTICS_RESPONSE.value`.
 
 ## Steps to create and start Analyzer
 The analyzer can be declared as below but there are many other ways to declare:
 
-The given object creation process for `_create_analyzer` involves defining an instance of the `Analyzer` message from the [gRPC definition](https://labs.etsi.org/rep/tfs/controller/-/blob/feat/194-unable-to-correctly-extract-the-aggregation-function-names-from-the-dictionary-received-as/proto/analytics_frontend.proto) and populating its fields.
+The given object creation process for `_create_analyzer` involves defining an instance of the `Analyzer` message from the [gRPC definition](https://labs.etsi.org/rep/tfs/controller/-/blob/develop/proto/analytics_frontend.proto) and populating its fields.
 
 ```
 from common.proto.analytics_frontend_pb2 import AnalyzerId
@@ -101,18 +97,5 @@ analytics_client_object = AnalyticsFrontendClient()
 analytics_client_object.StartAnalyzer(_create_analyzer_id)
 ```
 
-### **How to Receive Analyzer Responses**
-   - There is a non-gRPC method in the analyzer frontend called `StartResponseListener(<analyzer_uuid>)`. The `analyzer_uuid` is the UUID of the analyzer provided when calling `StartAnalyzer()`. The following code will log the responses:
-```python
-from analytics.frontend.service.AnalyticsFrontendServiceServicerImpl import AnalyticsFrontendServiceServicerImpl
-
-analytic_frontend_service_object = AnalyticsFrontendServiceServicerImpl()
-for response in analytic_frontend_service_object.StartResponseListener(<analyzer_uuid>):
-    LOGGER.debug(response)
-```
-
-### **Understanding the Output of the Analyzer**
-- **Output Column Names**: The output JSON string will include two keys for each defined threshold. For example, the `min_latency` threshold will generate two keys: `min_latency_THRESHOLD_FAIL` and `min_latency_THRESHOLD_RAISE`.
-  - `min_latency_THRESHOLD_FAIL` is triggered if the average latency calculated within the defined window size is less than the specified threshold range.
-  - `min_latency_THRESHOLD_RAISE` is triggered if the average latency calculated within the defined window size exceeds the specified threshold range.
-- The thresholds `min_latency_THRESHOLD_FAIL` and `min_latency_THRESHOLD_RAISE` will have a value of `TRUE` if activated; otherwise, they will be set to `FALSE`.
+### **How to Receive Analyzer Response**
+   - `GetAlarms(<kpi_id>) -> KpiAlarms` is a method in the `KPI Value Api` that retrieves alarms for a given KPI ID. This method returns a stream of alarms associated with the specified KPI.