feat: realtime user analytics

[vsrivatsa-juspay]

Type of Change

• Bugfix
• New feature
• Enhancement
• Refactoring
• Dependency updates
• Documentation
• CI/CD

Description

This PR introduces a real-time analytics feature that allows merchants to track distinct payment IDs on their dashboards. The key components of this feature include a script to create a ClickHouse table with a 1-minute Time-To-Live (TTL) for the data, and an analytics service that counts distinct payment IDs.
Also add the the http server for vector to collect and push logs to kafka in this PR.

Changes:

ClickHouse Table Creation Script:
Added a script to create a ClickHouse table with a 1-minute TTL. This table will store payment events and automatically purge entries older than 1 minute, ensuring that only recent data is kept for real-time analytics.

Analytics Service:
Implemented an analytics service that queries the ClickHouse table to count distinct payment IDs. This provides real-time insights into the number of unique payments processed within the last minute.

Additional Changes

• This PR modifies the API contract
• This PR modifies the database schema
• This PR modifies application configuration/environment variables

Motivation and Context

How did you test it?

1. Start the necessary services using Docker Compose

docker compose up -d kafka-ui clickhouse-server

2. Load the SDK and simulate payments
3. Verify Real-Time Analytics

curl --location 'localhost:8080/analytics/v1/metrics/active_payments' \
--header 'Content-Type: application/json' \
--header 'Accept: application/json' \
--header 'Authorization: Bearer {token}' \
--data '[
    {
        "timeRange": {
            "startTime": "2024-06-24T18:30:00Z",
            "endTime": "2024-06-24T18:31:00Z"
        },
        "metrics": [
            "active_payments"
        ]
    }
]'

{
    "queryData": [
        {
            "active_payments": 2
        }
    ],
    "metaData": [
        {
            "current_time_range": {
              "start_time": "2024-06-24T18:30:00Z",
              "end_time": "2024-06-24T18:31:00Z"
            }
        }
    ]
}

Checklist

• I formatted the code cargo +nightly fmt --all
• I addressed lints thrown by cargo clippy
• I reviewed the submitted code
• I added unit tests for my changes where possible