SIENTIAPDE-1005

Implement workflows for fake data generation, scouter processing, and core scouter operations

- Added `FakeData` workflow to generate random data and send it to a Kafka topic.
- Implemented `Scouter` workflow to load data from Kafka and trigger the core scouter workflow.
- Created `CoreScouter` workflow to process data through quality gates, aggregation, and export to PostgreSQL.
- Developed comprehensive unit tests for activities and workflows, ensuring proper functionality and error handling.
- Enhanced Redis and Postgres activities with robust testing for data handling and error notifications.
- Introduced quality filters for data validation and implemented tests to verify their functionality.

scouter/utils/policies.py

@@ -0,0 +1,9 @@
+from temporalio.common import RetryPolicy
+from datetime import timedelta
+
+retry_policy = RetryPolicy(
+    initial_interval=timedelta(seconds=1),
+    backoff_coefficient=2.0,
+    maximum_interval=timedelta(minutes=1),
+    maximum_attempts=1
+)