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remove description about "scale jobs" (#7712)

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CaoShuFeng
2018-03-13 09:39:09 +08:00
committed by k8s-ci-robot
parent ded7723a69
commit 838b81120c
2 changed files with 1 additions and 7 deletions
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docs/concepts/workloads/controllers/jobs-run-to-completion.md
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@@ -257,8 +257,7 @@ The tradeoffs are:
- One Job object for each work item, vs. a single Job object for all work items. The latter is - One Job object for each work item, vs. a single Job object for all work items. The latter is
better for large numbers of work items. The former creates some overhead for the user and for the better for large numbers of work items. The former creates some overhead for the user and for the
system to manage large numbers of Job objects. Also, with the latter, the resource usage of the job system to manage large numbers of Job objects.
(number of concurrently running pods) can be easily adjusted using the `kubectl scale` command.
- Number of pods created equals number of work items, vs. each pod can process multiple work items. - Number of pods created equals number of work items, vs. each pod can process multiple work items.
The former typically requires less modification to existing code and containers. The latter The former typically requires less modification to existing code and containers. The latter
is better for large numbers of work items, for similar reasons to the previous bullet. is better for large numbers of work items, for similar reasons to the previous bullet.
docs/tasks/job/parallel-processing-expansion.md
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@@ -184,11 +184,6 @@ If you have a large number of job objects, you may find that:
- Even using labels, managing so many Job objects is cumbersome. - Even using labels, managing so many Job objects is cumbersome.
- You exceed resource quota when creating all the Jobs at once, - You exceed resource quota when creating all the Jobs at once,
and do not want to wait to create them incrementally. and do not want to wait to create them incrementally.
- You need a way to easily scale the number of pods running
concurrently. One reason would be to avoid using too many
compute resources. Another would be to limit the number of
concurrent requests to a shared resource, such as a database,
used by all the pods in the job.
- Very large numbers of jobs created at once overload the - Very large numbers of jobs created at once overload the
Kubernetes apiserver, controller, or scheduler. Kubernetes apiserver, controller, or scheduler.