Java Workflow Overview¶

Introduction¶

Java Workflow is a scheduled binary that runs at predefined intervals to collect and process data from multiple platforms. It plays a crucial role in aggregating information required for various backend operations and analytics.

How It Works¶

Java Workflow is triggered at specific times based on a configured schedule.
It fetches data from multiple platforms via API calls, database queries, or message queues.
The collected data is processed and stored in the required format for downstream services.
Logging and monitoring ensure smooth execution and debugging in case of failures.

Data Sources¶

Java Workflow integrates with the following platforms: - Platform A – Provides user-related data. - Platform B – Supplies transaction records. - Platform C – Streams real-time event logs.

Common Challenges¶

Data from certain platforms may be missing.
API rate limits could affect data retrieval.
Workflow execution may fail due to service outages.

Logging & Monitoring¶

Logs are stored in /var/logs/java-workflow/ and can be accessed via Kibana.
Monitoring is done using Prometheus and Grafana dashboards.
Alerts are sent via GoAlert in case of failures.

Configuration & Deployment¶

Java Workflow is deployed as a containerized application in Kubernetes.
Configurations are managed through environment variables and config files.
Scheduled execution is managed using CronJobs.

Java Server API – Interacts with Java Workflow to request processed data.
Message Queues – Used for asynchronous processing.
Monitoring Tools – Tracks workflow execution and performance metrics.

This document provides a high-level understanding of Java Workflow. For specific issues and debugging steps, refer to the Common Issues section.