Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

docs: readme note for gke deployment configuration #185

Merged
merged 2 commits into from Feb 24, 2020
Merged

docs: readme note for gke deployment configuration #185

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
96c6831
docs: note for gke deployment
rahulKQL Jan 31, 2020
670381e
docs: rephrased the readme notes
rahulKQL Jan 31, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
19 changes: 19 additions & 0 deletions README.md
View file
Open in desktop
Expand Up @@ -345,6 +345,25 @@ Add the following to your project's pom.xml.
</dependencyManagement>
```

## Container Deployment

While deploying this client in [Google Kubernetes Engine(GKE)](https://cloud.google.com/kubernetes-engine) with [CoS](https://cloud.google.com/container-optimized-os/docs/). Please make sure to provide CPU configuration in your deployment file. With default configuration JVM detects only 1 CPU, which affects the number of channels with the client, resulting in performance repercussion.

Also, The number of `grpc-nio-worker-ELG-1-#` thread is same as number of CPUs. These are managed by a single `grpc-default-executor-#` thread, which is shared among multiple client instances.

For example:
```yaml
appVersion: v1
...
spec:
...
container:
resources:
requests:
cpu: "1" # Here 1 represents 100% of single node CPUs whereas other than 1 represents the number of CPU it would use from a node.
```
see [Assign CPU Resources to Containers](https://kubernetes.io/docs/tasks/configure-pod-container/assign-cpu-resource/#specify-a-cpu-request-and-a-cpu-limit) for more information.

## Troubleshooting

To get help, follow the instructions in the [shared Troubleshooting
Expand Down