Answers: <p>Since Pod is running on single node it can use resources from this node only. And CPU/MEM can't be shared here. At least without special software for distributed computation.</p>
  <p>In your case you should consider using ActiveMQ Clustering (<a href="https://activemq.apache.org/clustering" rel="nofollow noreferrer">https://activemq.apache.org/clustering</a>). In that way you will be able to spread load across multiple k8s nodes with ActiveMQ pods running on them.</p>
  <p>So use k8s Deployment + pod affinity to be sure pods will be scheduled to different nodes.</p>
  
Answers: CC BY-SA 4.0
Answers: 2021-03-05T09:17:54.850Z
Answers: So far this look close to my requirements https://www.scalemp.com/products/vsmp-serverone/
Answers: ImranRazaKhan
Answers: CC BY-SA 4.0
Answers: 2021-03-03T15:35:59.723Z
Answers: 2021-03-03T15:35:59.723Z
Answers: Peter Salnikov
Body: <p><strong>Setup</strong>: I have 10 Photovoltaics based setup where IOT Gateway get data from sensors, devices and send to Kubernetes Cluster. K8S cluster exposed its ActiveMQ broker with NodePort.</p>
  <p><strong>Observation</strong>: AMQ has been scheduled on Node2 and i observed that CPU usage of this node is around 75%, As we are collecting lot of messages, But other nodes CPU usage is like 8% to 20%. If we put more load this CPU might reach to 100%.</p>
  <p>Although we have CPU resource available but we cant use it, How can I do optimal usage of resources?</p>
  <p>I read Apache Mesos and DC/OS but i think still its not possible to run a container workload which requests more cpu /memory than available on its single largest physical/virtul host.</p>
  <p>Any thoughts in this regard?</p>
  
Tags: <kubernetes>
Title: How to consolidate multiple servers for CPU and Memory with Kubernetes
UserDisplayName: ImranRazaKhan
ThreadText: # How to consolidate multiple servers for CPU and Memory with Kubernetes
  
  (Asked by: username_0 on 2021-03-02)
  
  **Setup**: I have 10 Photovoltaics based setup where IOT Gateway get data from sensors, devices and send to Kubernetes Cluster. K8S cluster exposed its ActiveMQ broker with NodePort.
  
  **Observation**: AMQ has been scheduled on Node2 and i observed that CPU usage of this node is around 75%, As we are collecting lot of messages, But other nodes CPU usage is like 8% to 20%. If we put more load this CPU might reach to 100%.
  
  Although we have CPU resource available but we cant use it, How can I do optimal usage of resources?
  
  I read Apache Mesos and DC/OS but i think still its not possible to run a container workload which requests more cpu /memory than available on its single largest physical/virtul host.
  
  Any thoughts in this regard?
  
  **Tags:** kubernetes
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2021-03-03. Score: 1
  
  Since Pod is running on single node it can use resources from this node only. And CPU/MEM can't be shared here. At least without special software for distributed computation.
  
  In your case you should consider using ActiveMQ Clustering (<https://activemq.apache.org/clustering>). In that way you will be able to spread load across multiple k8s nodes with ActiveMQ pods running on them.
  
  So use k8s Deployment + pod affinity to be sure pods will be scheduled to different nodes.
  
  > **Comments:**
  > **username_0**: So far this look close to my requirements https://www.scalemp.com/products/vsmp-serverone/  
  
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