From the course: Deploying Scalable Machine Learning for Data Science
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Scaling up a Kubernetes cluster
From the course: Deploying Scalable Machine Learning for Data Science
Scaling up a Kubernetes cluster
- [Instructor] Now let's talk about scaling up a Kubernetes Cluster. Let's consider what happens when the load on your cluster increases. Now we have a cluster running with two servers. If we believe that we'll have sustained demand for some extended period of time, we can manually add more nodes to the server. We do this by editing our deployment file. Notice that the replicas parameter indicates that we should be running two replicas. Let's change that to four so that we run four pods. Now let's save this out. And pop over to the terminal window. And you'll notice we are continuing where we left off at the end of the last video, which is, we have two pods running here. So let's just clear the screen. And let's verify by doing a cat deployment.yaml that yes, we did in fact save the change. So now we're going to have four replicas. So we've indicated that we want four replicas. And what we need to do is we need to use the apply command again. You may recall from the last video, we…
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