Managing enterprise workloads requires more than just scheduling jobs. As batch processes become larger and more complex, operations teams need real-time visibility into workflow execution, resource usage, failures, and system performance.
WLOADCTL provides such an integrated monitoring platform. It helps administrators monitor running jobs and quickly respond to execution issues.
In general, the monitoring module provides three core capabilities:
Real-time Monitoring: Providing multi-dimensional visibility into platform operations and workload execution status.
Scheduling Management: Enabling centralized management, control of scheduling objects and job execution processes.
Operational Analysis: Providing statistical analysis of workflow execution data to improve operational efficiency.
This article introduces the key monitoring features that commonly used in daily work.
Graph Monitoring
After entering the Monitor module, you can access the monitoring dashboard, which provides an overview of current workflow execution status and operational statistics.
The graph view provides an intuitive visualization of workflow execution. You can quickly identify running nodes, completed tasks, failed jobs, and execution dependencies.
Reload Job Container
When a job container is stopped, you can click the Reload button in the toolbar to load the latest published workflow version.
After reloading, the latest workflow configuration will be applied and the job status will be reset to the initial state.
Restart Job Container
When a job container is not running, click the Exited button at the top of the monitoring page to open the container startup dialog.
WLOADCTL provides three startup modes:
Normal Mode：Runs the workflow sequentially from the start node to the end node.
Free Mode: Allows users to manually select specific nodes or branches to execute.
Virtual Mode: Simulates workflow execution without actually running jobs. Users can configure the simulation speed multiplier for testing and analysis.
Note: Timers only support Normal Mode. Platform variables cannot be modified after they have been set.
Job Properties Sidebar
You can open the job properties panel by either double-clicking a node in the workflow graph or clicking the expand button in the job status panel. And, the job information is categorized into two groups:
Dynamic Runtime Attributes
These attributes describe the current execution status, including:
Running status
Start and end time
Average execution duration
Recent execution duration
Estimated completion time
Generated execution nodes
Manual interventions (disable or lock operations)
Static Basic Attributes
These attributes define the workflow configuration, including:
Execution plan
Execution conditions
Fault tolerance settings
Loop configuration
Referenced parameters
Job code blocks
Statistical Monitoring
WLOADCTL provides monitoring statistics at three levels below:
Project Monitoring
Project Monitoring tracks job execution status by application project. You can:
View job status distribution
Drill down into detailed job monitoring
Open project information panels
Access related container pages, job lists, and project variables
Container Monitoring
Container Monitoring provides execution statistics for individual job containers. It has key capabilities include:
Filtering by project and container type
Viewing detailed job lists
Accessing container-level control operations
Reviewing container execution status through visual dashboards
Job Monitoring
By double-clicking a job opens the detailed job properties panel. This panel provides detailed real-time execution information in a list-based view. You can filter jobs by:
Project
Container
Job type
Agent
Execution status
Additional Monitoring Features
Node Monitoring
WLOADCTL also provides node-level monitoring for workflow execution environments.
By selecting a node, you can view basic node information, logical resource usage and physical resource utilization.
The detailed node properties panel provides additional operational information.
Message Monitoring
Message Monitoring provides centralized management of platform notifications and execution events.
Messages are organized by category, and each message type supports corresponding batch operations.
For example, when multiple job failure messages occur, you can perform batch actions such as skip failed jobs, retry execution and review failure details
After expanding a message group, you can view individual messages and open the message details panel, which includes:
Message content
Related job information
Available operation commands
Read messages are automatically archived and can be accessed through the message history list.
If you want more infomation about how the monitoring module works, click Monitoring Module Detailed Guide
Conclusion
Effective monitoring isn't just about dashboards — it's about reducing the cognitive load on your operations team. When batch jobs fail at 2 AM, every minute spent hunting through logs is a minute that could have been spent fixing the issue. That's why visibility matters.
In conclusion, combining workload orchestration with operational monitoring is a great way to help enterprises improve reliability, reduce troubleshooting time, and maintain stable production environments.
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