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How long does it typically take a cluster to come up and be live?

Posted November 13, 2019 965 views
Ruby on RailsKubernetes

I have successfully launched my app using DO Kubernetes, but have noticed that from typing kubectl apply for the first time to the cluster being able to serve requests takes around 5 minutes. Is this typical? It seems long but I am not sure what to expect.

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scottmiller
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4 answers
jkwiatkoski November 14, 2019

Hi there!

Yes it can take anywhere from 3-10min for the cluster to come up. This is heavily dependent on the cluster size and how many nodes need to bootstrap as well as other factors such as the standard performance variability.

Let me know if you have any additional questions.

Regards,

John Kwiatkoski
Senior Developer Support Engineer

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bobbyiliev November 14, 2019

Hello,

I’ve just tested this, I deployed a new Cluster and it took about 4 minutes for the cluster to be up and running.

After that I tried deploying this test application with kubectl apply and it worked instantly.

Hope that this helps!
Regards,
Bobby

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  • scottmiller November 14, 2019

    Thanks Bobby, I also noticed that things worked instantly with a super simple “Hello World” application.

    I am guessing the time I am seeing after kubectl apply is probably because the container(s) take that long to install all of the dependencies and everything.

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scottmiller November 14, 2019

I found this great article that explains how to configure rolling updates (another place I was seeing downtime after kubectl apply…

https://medium.com/platformer-blog/enable-rolling-updates-in-kubernetes-with-zero-downtime-31d7ec388c81

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conradwt November 14, 2019

Yes, I agree with the other answers to your post. The cluster will definitely take several minutes to be up and operational. Also, kubectl apply is dependent on what you’re doing within the resource YAML.

For example, the size of your image(s) and what polices you’re using here to obtain the image. In general, this should be instant but it really depends what you’re doing in the YAML.

–

Think different and code well,

-Conrad

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