Schedulung performance - CPU usage
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- Dominant language
- Go
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Description
I did a performance test in order to test the scheduling performance of Docker swarm. For this purpose I measured the time it takes to schedule and start 1000 containers on 100 worker nodes. A cluster of 3 Manager nodes is used.
The graphs show the cpu usage of the 3 manager nodes and one worker node during the scheduling process. The time 0 is the time where the scheduling action was started.
In the first graph no service was ever created or scheduled before (Fresh cluster).
In the second graph the experiment was repeated several times before.
While all 1000 containers were scheduled and started in under 2,5 seconds the cpu usage is higher during the scheduling and is still over 150% 60 seconds after the scheduling finished.
What is going on here? Why has the fresh cluster a lower cpu usage?
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Research direction
No source files, tests, or entry points are named. Start by reproducing the reported workload: 1,000 containers on 100 workers with three managers, comparing a fresh cluster with one reused across experiments. Done means identifying the cause of the sustained manager CPU usage and recording evidence that explains the difference.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- docker, go
- Domain
- distributed-systems, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100