Add additional-guest-memory-overhead-ratio setting #615
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
w13915984028
force-pushed
the
doc5768
branch
from
3b14d7a to
910a451
Compare
w13915984028
changed the title
This was referenced Sep 2, 2024
|
@jillian-maroket The original PR was titled with |
Signed-off-by: Jian Wang <[email protected]>
w13915984028
force-pushed
the
doc5768
branch
from
910a451 to
3a7366d
Compare
Signed-off-by: Jian Wang <[email protected]>
Signed-off-by: Jian Wang <[email protected]>
w13915984028
force-pushed
the
doc5768
branch
from
5950392 to
02e8da3
Compare
|
The comment from code review by @bk201 is worthy to check, it is better to have some benchmarks to support our suggestions on the document. |
w13915984028
force-pushed
the
doc5768
branch
from
9c89919 to
7374f9f
Compare
Signed-off-by: Jian Wang <[email protected]>
w13915984028
force-pushed
the
doc5768
branch
from
7374f9f to
d1f89cc
Compare
Signed-off-by: Jian Wang <[email protected]>
|
|
||
| **Definition**: The ratio to futher tune the VM `memory overhead`. | ||
|
|
||
| Each VM is configured with a memory value, this memory is targeted for the VM guest OS to see and use. In Harvester, the VM is carried by a Kubernetes POD. The memory limitation is achieved by Kubernetes [Resource requests and limits of Pod and container](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/#resource-requests-and-limits-of-pod-and-container). Certain amount of memory is required to simulate and manage the `CPU/Memory/Storage/Network/...` for the VM to run. Harvester and KubeVirt summarize such additional memory as the VM `Memory Overhead`. The `Memory Overhead` is computed by a complex formula formula. However, sometimes the OOM(Out Of Memory) can still happen and the related VM is killed by the Harvester OS, the direct cause is that the whole POD/Container exceeds its memory limits. From practice, the `Memory Overhead` varies on different kinds of VM, different kinds of VM operating system, and also depends on the running workloads on the VM. |
There was a problem hiding this comment.
Suggested change
| Each VM is configured with a memory value, this memory is targeted for the VM guest OS to see and use. In Harvester, the VM is carried by a Kubernetes POD. The memory limitation is achieved by Kubernetes [Resource requests and limits of Pod and container](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/#resource-requests-and-limits-of-pod-and-container). Certain amount of memory is required to simulate and manage the `CPU/Memory/Storage/Network/...` for the VM to run. Harvester and KubeVirt summarize such additional memory as the VM `Memory Overhead`. The `Memory Overhead` is computed by a complex formula formula. However, sometimes the OOM(Out Of Memory) can still happen and the related VM is killed by the Harvester OS, the direct cause is that the whole POD/Container exceeds its memory limits. From practice, the `Memory Overhead` varies on different kinds of VM, different kinds of VM operating system, and also depends on the running workloads on the VM. | |
| Each VM is configured with a memory value, this memory is targeted for the VM guest OS to see and use. In Harvester, the VM is run in a virt-launcher pod. CPU/VM resource limits are translated and applied to the launcher pod[Resource requests and limits of Pod and container](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/#resource-requests-and-limits-of-pod-and-container). Kubevirt ensures certain amount of memory is reserved in the pod for managing the virtualisation process. Harvester and KubeVirt summarize such additional memory as the VM `Memory Overhead`. The `Memory Overhead` is computed by a complex formula formula. However, sometimes the OOM(Out Of Memory) can still happen and the related VM is killed by the Harvester OS, the direct cause is that the whole POD/Container exceeds its memory limits. From practice, the `Memory Overhead` varies on different kinds of VM, different kinds of VM operating system, and also depends on the running workloads on the VM. |
| A VM that is configured to have `1 CPU, 2 Gi Memory, 1 Volume and 1 NIC` will get around `240 Mi` `Memory Overhead` when the ratio is `"1.0"`. When the ratio is `"1.5"`, the `Memory Overhead` is `360 Mi`. When the ratio is `"3"`, the `Memory Overhead` is `720 Mi`. | ||
|
|
||
| A VM that is configured to have `1 CPU, 64 Gi Memory, 1 Volume and 1 NIC` will get around `250 Mi` `Memory Overhead` when the ratio is `"1.0"`. The VM memory size does not have a big influence on the computing of `Memory Overhead`. | ||
|
|
There was a problem hiding this comment.
can we please also explain why with a 64G VM the mem reserved is still 250M when users may wonder it would be higher considering a 2G VM got 240M
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Issue:
harvester/harvester#5768
harvester/harvester#6293 (about the influence of memory overhead against resource quota)