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- Total of running jobs
- This number has less impact on JobScheduler than you might expect, but it affects the available resources like memory and CPU.
- Consider the information from the article How to determine the sizing of a JobScheduler environment for memory and CPU consumption.
- A common observation is the fact that a system behaves performant as long it's capacity is not used up. Exceeding e.g. the memory limit of a server will result in the operating system swapping the memory and will cause inacceptable performance penalties.
- Race Conditions
- Multiple jobs accessing the same resources, e.g. shared Locks or objects in a database or file system tend to cause race conditions.
- Analyze the resources used by your jobs, e.g. use of exclusive vs. shared Locks or access to database tables to identify possible bottlenecks that would force serialized execution for processes that are assumed to run in parallel.
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Performance Optimization
Parallelism
JobScheduler is designed for parallelism as the most effective means to improve performance.
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