Job Management Dashboard for Cloud Resource Optimization
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Solution Overview
Problem
In multi-instance cloud architectures, the finite allocation of computing resources leads to job execution delays due to resource competition, resulting in slower job performance at certain times, as hundreds or thousands of jobs execute simultaneously, competing for shared resources.
Innovation Solution
A job management dashboard is provided that allows users to visualize, manage, and optimize scheduled, executed, and executing jobs across a customizable time period, enabling efficient scheduling and resource allocation by displaying job information in a calendar view, allowing for adjustments to execution times based on historical trends and resource availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple jobs execute simultaneously in parallel on a customer instance, then job throughput increases, but resource availability per job decreases causing slower execution
Solution Approach 1:
The system performs preliminary analysis of historical job execution data to identify patterns and predict future resource availability. This allows the system to proactively schedule jobs during periods when resources are predicted to be available, preventing execution delays before they occur. The predictive scheduling mechanism analyzes past execution times, resource consumption patterns, and system load trends to optimize future job scheduling decisions.
2Adaptability or versatility
If computing resources are allocated to a customer instance, then the instance can execute jobs, but the finite resource allocation causes competition and delays when many jobs are scheduled
Solution Approach 1:
The system dynamically adjusts job scheduling based on real-time and historical resource availability patterns. Instead of static scheduling, the system continuously monitors execution performance, resource consumption, and system load to adaptively optimize job placement. This dynamic approach allows the system to respond to changing conditions and minimize execution delays by rescheduling jobs to optimal time slots based on learned patterns.
Solution Approach 2:
The system implements a feedback mechanism that continuously monitors job execution outcomes, resource utilization, and timing patterns. This feedback is used to refine scheduling decisions, identifying optimal execution windows and adjusting future schedules to avoid periods of resource contention. The feedback loop enables continuous improvement of scheduling efficiency and reduction of execution delays.
3Ease of operation
If users manually manage job schedules, then execution timing can be optimized, but the complexity of managing hundreds or thousands of jobs increases
Solution Approach 1:
The system implements self-service automated scheduling that eliminates the need for manual intervention in managing large numbers of jobs. The automated scheduler independently analyzes job requirements, historical performance data, and resource availability to generate optimized schedules. This self-service capability allows the system to autonomously handle the complexity of coordinating hundreds or thousands of jobs while providing users with simplified interfaces for monitoring and high-level control.
Data Source
AI summary
A system has a processor and a memory accessible by the processor and storing instructions, that when executed by the processor, cause the processor to generate a graphical user interface (GUI) for display on a display device. The GUI may include a job management dashboard that has multiple graphical icons that are representative of respective jobs associated with a client instance. The processor may receive one or more user inputs indicative of a selection of a particular graphical icon in the job management dashboard and transmit an update to GUI to the display device. The updated GUI may include a job overview window associated with a particular job, and the job overview window may display a graph of multiple run times associated with the particular job over a period of time.