Scalability Test and Cluster Management Doc #511
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Signed-off-by: Gao Hongtao <[email protected]>
Signed-off-by: Gao Hongtao <[email protected]>
Signed-off-by: Gao Hongtao <[email protected]>
hanahmily
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documentation
wankai123
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Aug 14, 2024
wu-sheng
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Aug 14, 2024
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| The cluster's availability is also improved by increasing the number of data nodes, as active data nodes need to handle a lower additional workload when some data nodes become unavailable. For example, if one node out of 2 nodes is unavailable, then 50% of the load is re-distributed across the remaining node, resulting in a 100% per-node workload increase. If one node out of 10 nodes is unavailable, then 10% of the load is re-distributed across the 9 remaining nodes, resulting in only an 11% per-node workload increase. | ||
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| Increasing the number of etcd nodes can increase the cluster's metadata capacity and improve the cluster's metadata query performance. It can also improve the cluster's metadata availability, as the metadata is replicated across all the etcd nodes. However, the cluster size should be odd to avoid split-brain situations. |
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etcd could be a potential risk when we run larger scale deployment, I believe.
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Absolutely.
During the test, I used 10 data nodes and only 1 etcd node in a medium-sized cluster. Moving forward, we need to include more extensive and complex scenarios in the scale testing.
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Yes, and when we meet Lenovo team next month, we need to verify the scale with them.
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Others are good, please fix menu structure for operation docs. |
Signed-off-by: Gao Hongtao <[email protected]>
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Why your yaml is so different? |
Signed-off-by: Gao Hongtao <[email protected]>
wu-sheng
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Aug 14, 2024
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