Observability Platform for Centralized Monitoring of Containerized Healthcare Management Applications

The user logs into the Healthcare Management Application using their registered credentials.

The application receives the login request, validates the user's credentials, and provides access to the appropriate application functions. The application runs as a containerized workload inside Kubernetes.

The healthcare staff registers a new patient or searches for an existing patient.

The application validates the patient information and stores new patient details in PostgreSQL. For existing patients, it retrieves the required information from the database. Application requests and database operations generate monitoring metrics and logs.

The user schedules, confirms, reschedules, or cancels a patient appointment.

The application validates the appointment details, records the selected date and time, and updates the appointment status in PostgreSQL. The application generates request, response-time, and error metrics during these operations.

The healthcare provider accesses patient information and records consultation details.

The application retrieves the patient's existing records and allows the authorized healthcare provider to add consultation details, diagnosis, treatment information, and other relevant records. Application events and errors are recorded in logs.

The application records healthcare services provided to the patient and generates the associated billing information.

The application records the services provided, calculates applicable charges, generates billing information, and stores the details in PostgreSQL. Processing time and application errors are monitored.

The payment is processed and the patient's billing status is updated.

The application sends the payment request to the payment service, receives the payment result, and updates the billing status as Paid, Pending, or Failed. Payment-related application events and errors are captured in the application logs.

The observability platform continuously monitors the application's health, performance, resource usage, and availability.

Prometheus collects application and Kubernetes metrics such as CPU usage, memory usage, request rate, response time, and error rate. Loki collects application and container logs for centralized analysis.

The team reviews application dashboards and alerts, investigates detected problems, and the user logs out after completing the required activities.

Grafana displays application metrics and logs through centralized dashboards. When predefined conditions such as high error rates, high response times, or application failures occur, Prometheus generates alerts and Alertmanager manages the alert notifications. After completing the application activities, the user logs out and the application session is terminated.