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docs/tutorials/best-practices/scale-coder.md

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@@ -260,7 +260,7 @@ As you approach hard limits, consider deploying to additional cluster(s).
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### Workspaces per node
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Many development workloads are "spiky" in their CPU and memory requirements, for
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example, they peak during build/test and then ebb while editing code.
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example, they peak during build/test and then lower while editing code.
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This leads to an opportunity to efficiently use compute resources by packing multiple
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workspaces onto a single node. This can lead to better experience (more CPU and
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memory available during brief bursts) and lower cost.

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